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

Reverse phase protein array-based investigation of mitochondrial genes reveals alteration of glutaminolysis in the parahippocampal cortex of people who died by suicide

A moderating hub between resting state networks (RSNs) and the medial temporal lobe (MTL) is the parahippocampal cortex (PHC). Abnormal activity has been reported in depressed patients and suicide attempters in this region. Alterations in neuronal mitochondrial function may contribute to depression and suicidal behavior. However, little is known about the underlying molecular level changes in relevant structures. Specifically, expressional changes related to suicide have not been reported in the PHC. In this study, we compared the protein expression levels of genes encoding tricarboxylic acid (TCA) cycle enzymes in the PHC of adult individuals who died by suicide by reverse phase protein array (RPPA), which was corroborated by qRT-PCR at the mRNA level. Postmortem human brain samples were collected from 12 control and 10 suicidal individuals. The entorhinal cortex, which is topographically anterior to the PHC in the parahippocampal gyrus, and some other cortical brain regions were utilized for comparison. The results of the RPPA analysis revealed that the protein levels of DLD, OGDH, SDHB, SUCLA2, and SUCLG2 subunits were significantly elevated in the PHC but not in other cortical brain regions. In accordance with these findings, the mRNA levels of the respective subunits were also increased in the PHC. The subunits with altered levels are implicated in enzyme complexes involved in the oxidative decarboxylation branch of glutamine catabolism. These data suggest a potential role of glutaminolysis in the pathophysiology of suicidal behavior in the PHC.

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.

PI3K signaling through a biochemical systems lens

Following 3 decades of extensive research into PI3K signaling, it is now evidently clear that the underlying network does not equate to a simple ON/OFF switch. This is best illustrated by the multifaceted nature of the many diseases associated with aberrant PI3K signaling, including common cancers, metabolic disease, and rare developmental disorders. However, we are still far from a complete understanding of the fundamental control principles that govern the numerous phenotypic outputs that are elicited by activation of this well-characterized biochemical signaling network, downstream of an equally diverse set of extrinsic inputs. At its core, this is a question on the role of PI3K signaling in cellular information processing and decision making. Here, we review the determinants of accurate encoding and decoding of growth factor signals and discuss outstanding questions in the PI3K signal relay network. We emphasize the importance of quantitative biochemistry, in close integration with advances in single-cell time-resolved signaling measurements and mathematical modeling.

Discovery of pathway-independent protein signatures associated with clinical outcome in human cancer cohorts

Proteomic data provide a direct readout of protein function, thus constituting an information-rich resource for prognostic and predictive modeling. However, protein array data may not fully capture pathway activity due to the limited number of molecules and incomplete pathway coverage compared to other high-throughput technologies. For the present study, our aim was to improve clinical outcome prediction compared to published pathway-dependent prognostic signatures for The Cancer Genome Atlas (TCGA) cohorts using the least absolute shrinkage and selection operator (LASSO). RPPA data is particularly well-suited to the LASSO due to the relatively low number of predictors compared to larger genomic data matrices. Our approach selected predictors regardless of their pathway membership and optimally combined their RPPA measurements into a weighted risk score. Performance was assessed and compared to that of the published signatures using two unbiased approaches: 1) 10 iterations of threefold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Here, we demonstrate strong stratification of 445 renal clear cell carcinoma tumors from The Cancer Genome Atlas (TCGA) into high and low risk groups using LASSO regression on RPPA data. Median cross-validated difference in 5-year overall survival was 32.8%, compared to 25.2% using a published receptor tyrosine kinase (RTK) prognostic signature (median hazard ratios of 3.3 and 2.4, respectively). Applicability and performance of our approach was demonstrated in three additional TCGA cohorts: ovarian serous cystadenocarcinoma (OVCA), sarcoma (SARC), and cutaneous melanoma (SKCM). The data-driven LASSO-based approach is versatile and well-suited for discovery of new protein/disease associations.

A preliminary, prospective study of peripheral neuropathy and cognitive function in patients with breast cancer during taxane therapy

Dramatic improvements in cancer survival have occurred in the last decade, but the quality of life for many survivors is compromised due to severe, long-lasting, and often irreversible side effects of chemotherapy. The neurological side effects, chemotherapy induced peripheral neuropathy (CIPN) and cancer related/induced cognitive impairment (CRCI/CICI), are under-recognized and can occur after chemotherapy, immunotherapy, or radiation. The cellular mechanisms underlying these neurological side effects are poorly understood and there are no effective treatments or preventions, other than reduction or termination of cancer therapy. In our preliminary prospective, non-interventional study to examine the side effects of chemotherapy in patients with breast cancer (NCT03872141), patients with breast cancer who received standard of care single agent weekly taxane-based chemotherapy were assessed at baseline, midpoint, and end of treatment for neurological and cognitive changes and for blood levels of potential protein biomarkers (n = 13). CIPN and CRCI both showed an increase in severity with accumulating taxane and these changes were compared to protein alternations over the course of treatment. Using peripheral blood collected from patients (n = 10) during chemotherapy and tested with an antibody array curated by the MD Anderson RPPA Core), we found that 19 proteins were increased, and 12 proteins decreased over 12 weeks of treatment. Among those downregulate were proteins known to be critical for neuronal viability and function including GRB2 (growth factor receptor-bound protein 2) and NCS1 (neuronal calcium sensor 1). Concurrently, proteins associated with apoptosis, including BAK1 (Bcl-1 homologous antagonist/killer), were upregulated. These results support the proposal that CIPN and CRCI increase with increasing taxane exposure, and identified several proteins that are altered with taxane exposure that could be implicated in their pathogenesis. In conclusion, our study provides evidence for progressive neurological changes and the rationale to investigate the molecular basis for these changes with the goal of target identification for mitigation of these neurological side effects.

High-throughput profiling of histone post-translational modifications and chromatin modifying proteins by reverse phase protein array

Epigenetic variation plays a significant role in normal development and human diseases including cancer, in part through post-translational modifications (PTMs) of histones. Identification and profiling of changes in histone PTMs, and in proteins regulating PTMs, are crucial to understanding diseases, and for discovery of epigenetic therapeutic agents. In this study, we have adapted and validated an antibody-based reverse phase protein array (RPPA) platform for profiling 20 histone PTMs and expression of 40 proteins that modify histones and other epigenomic regulators. The specificity of the RPPA assay for histone PTMs was validated with synthetic peptides corresponding to histone PTMs and by detection of histone PTM changes in response to inhibitors of histone modifier proteins in cell cultures. The useful application of the RPPA platform was demonstrated with two models: induction of pluripotent stem cells and a mouse mammary tumor progression model. Described here is a robust platform that includes a rapid microscale method for histone isolation and partially automated workflows for analysis of histone PTMs and histone modifiers that can be performed in a high-throughput manner with hundreds of samples. This RPPA platform has potential for translational applications through the discovery and validation of epigenetic states as therapeutic targets and biomarkers. SIGNIFICANCE: Our study has established an antibody-based reverse phase protein array platform for global profiling of a wide range of post-translational modifications of histones and histone modifier proteins. The high-throughput platform provides comprehensive analyses of epigenetics for biological research and disease studies and may serve as screening assay for diagnostic purpose or therapy development.

Reverse phase protein arrays in acute leukemia: investigative and methodological challenges

INTRODUCTION

Acute leukemia results from a series of mutational events that alter cell growth and proliferation. Mutations result in protein changes that orchestrate growth alterations characteristic of leukemia. Proteomics is a methodology appropriate for study of protein changes found in leukemia. The high-throughput reverse phase protein array (RPPA) technology is particularly well-suited for the assessment of protein changes in samples derived from clinical trials.

AREAS COVERED

This review discusses the technical, methodological, and analytical issues related to the successful development of acute leukemia RPPAs.

EXPERT COMMENTARY

To obtain representative protein sample lysates, samples should be prepared from freshly collected blood or bone marrow material. Variables such as sample shipment, transit time, and holding temperature only have minimal effects on protein expression. CellSave preservation tubes are preferred for cells collected after exposure to chemotherapy, and incorporation of standardized guidelines for antibody validation is recommended. A more systematic biological approach to analyze protein expression is desired, searching for recurrent patterns of protein expression that allow classification of patients into risk groups, or groups of patients that may be treated similarly. Comparing RPPA protein analysis between cell lines and primary samples shows that cell lines are not representative of patient proteomic patterns.