Using Reverse Phase Protein Array (RPPA) to Identify and Target Adaptive Resistance

Labrie, Marilyne; Fang, Yong; Kendsersky, Nicholas D.; Li, Jun; Liang, Han; Westin, Shannon N.; Mitri, Zahi; Mills, Gordon B.

doi:10.1007/978-981-32-9755-5_14

Cited by 19 publications

(16 citation statements)

References 43 publications

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“…We also measured total and phosphoprotein levels in Bx1, Bx2, and Bx4 by RPPA (Figure 3E) and assessed pathway activity relative to the TCGA-BRCA cohort using proteomic pathway signatures. 12 We observed notable variations in pathways representing cell cycle regulation, hormone receptors, and PI3K-AKT signaling between biopsies (Figure 3D). For example, the “G0-G1”, “G2-M”, and “DNA Damage Checkpoint” pathways were increased in Bx1 relative to Bx2 and Bx4, as was phosphorylation of ATM, ATR, CDK1, and WEE1 (Figure 3E), suggesting that Bx1 had activated cell cycle checkpoints in response to DNA damage.…”

Section: Resultsmentioning

confidence: 93%

“…Figures S2E and S3A summarize the results of whole exome and Dual Index Degenerate Adaptor Sequencing (DIDA-Seq) of ctDNA from serial blood samples (Butler et al, 2019). Figure 3 also summarizes the results from RNA sequencing (RNAseq) to characterize the whole transcriptome ( Figure 3C), reverse phase protein arrays (RPPA) to profile the abundance of 450 proteins and phosphoproteins (Figures 3D, 3F;(Chen et al, 2019;Labrie et al, 2019a)), and a clinical multiplex protein analysis (Intracellular Signaling Protein Panel) of 22 cancer proteins and phosphoproteins ( Figure 3E; (Lee et al, 2018)). Computed pathway activity was estimated by assessing proteomic pathway signatures (Labrie et al, 2019a), total or phosphoprotein abundance levels, transcriptomic gene set variation analysis (GSVA; (Hanzelmann et al, 2013;Liberzon et al, 2015)), and transcriptional regulator networks (see Methods).…”

Section: An Integrated Clinical Omic and Multiscale Image Atlas Of mentioning

confidence: 99%

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An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

Johnson

Creason

Stommel

et al. 2020

Preprint

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SummaryMetastatic cancers often respond to treatment initially but almost universally escape therapeutic control through molecular mechanisms intrinsic to tumor cells, as well as extrinsic influences from immune cells, stroma, and structural microenvironments. We explore the extent to which we can learn these mechanisms and associated therapeutic vulnerabilities by linking comprehensive molecular and multiscale imaging analyses of tumor biopsies to detailed clinical information for a patient with metastatic breast cancer. Our analyses of three serial biopsies include DNA, RNA, and protein profiling, plus quantification of tumor microenvironment composition using multiplex immunostaining and electron microscopy. Features from these analyses are linked to treatments and treatment-response measurements, including CT and PET images, circulating tumor DNA and tumor protein levels in blood, and treatment-limiting readouts of blood counts and liver function. Importantly, the measurement modalities unique to this study complemented routine diagnostics to suggest actionable mechanisms of response and resistance for each treatment phase.

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Section: Resultsmentioning

confidence: 93%

Section: An Integrated Clinical Omic and Multiscale Image Atlas Of mentioning

confidence: 99%

An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

Johnson

Creason

Stommel

et al. 2020

Preprint

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“…Inherent resistance, characterized by a pre-existing resistance to therapy, is difficult to predict in static biopsies that are acquired prior to therapy. We and other groups have demonstrated in multiple studies that the acquisition of a second biopsy early during the course of treatment is a powerful tool for analyzing how the tumor responds to therapy and for helping to identify mechanisms of adaptive resistance (reviewed in (Labrie et al, 2019a)). We have shown that serial samples can be collected pre and on-therapy with minimum risk to the patient and that these samples can be analyzed in “real time” using CLIA assays.…”

Section: Discussionmentioning

confidence: 99%

Multi-omics analysis of serial samples from metastatic TNBC patients on PARP inhibitor monotherapy provide insight into rational PARP inhibitor therapy combinations

Labrie¹,

Li²,

Creason³

et al. 2020

Preprint

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Due to complexity of advanced epithelial cancers, it is necessary to implement patient specific combination therapies if we are to markedly improve patient outcomes. However, our ability to select and implement patient specific combination therapies based on dynamic molecular changes in the tumor and tumor ecosystem in response to therapy remains extremely limited. In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). Although PARP inhibition was consistently observed in all patients, deep molecular analysis of the tumor and its ecosystem revealed insights into potentially effective therapeutic PARPi combinations. In a BRCA-mutant basal breast cancer exceptional long-term survivor, we noted striking PARPi-induced tumor destruction accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor (LAR) rapid progressor in response to PARPi likely due to indifference to the effects of PARP inhibition. In this rapid progressor, there was minimal evidence of immune activation or protein network rewiring in response to PARPi, despite PARP being inhibited, and no clinical benefit was noted for this participant. Together, deep real-time analysis of longitudinal biopsies identified a suite of PARPi-induced emergent changes including immune activation, DNA damage checkpoint activation, apoptosis and signaling pathways including RTK, PI3K-AKT and RAS-MAPK, that could be used to select patient specific combination therapies, based on tumor and immune state changes that are likely to benefit specific patients.

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“…The RPPA were optimized to measure the levels of 300 proteins for downstream analysis. Normalized log2-transformed values of data were used throughout the reported analysis [14].…”

Section: Reverse-phase Protein Arraymentioning

confidence: 99%

ONC201 and an MEK Inhibitor Trametinib Synergistically Inhibit the Growth of Triple-Negative Breast Cancer Cells

et al. 2021

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Triple-negative breast cancer (TNBC) is a heterogeneous group of estrogen, progesterone, and HER2-negative breast cancers with poor clinical outcomes. The imipridone ONC201 is a G-protein-coupled dopamine receptor D2 modulator and an allosteric agonist of the mitochondrial protease caseinolytic protease P(ClpP), which induces apoptosis. Here, we aimed to develop a novel ONC201-based combination therapy targeting TNBC. We performed a reverse-phase protein array analysis of ONC201-treated/-untreated and -sensitive/-resistant cell lines to identify potential predictive biomarkers. A principal component analysis using measured protein expression levels, the apoptosis score (AS), and heatmaps of all the measured protein and AS-related protein expression levels did not show a clear correlation between the expression levels of a specific protein and ONC201 efficacy. Three-dimensional RNA interference kinome-wide library screening revealed the MAPK and PI3K/Akt pathways as potential synergistic therapeutic partners. The combination with the MEK inhibitor trametinib successfully inhibited the growth of both ONC201-sensitive/-resistant TNBC cell lines. The baseline ClpP level correlated with the efficacy of single-agent ONC201. Single and combination therapy increased caspase 3/7 activity. The predictive biomarkers and a detailed mechanism of synergy beyond an induction of caspase activation should be tested for translation into future studies.

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Using Reverse Phase Protein Array (RPPA) to Identify and Target Adaptive Resistance

Cited by 19 publications

References 43 publications

An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

An Omic and Multidimensional Spatial Atlas from Serial Biopsies of an Evolving Metastatic Breast Cancer

Multi-omics analysis of serial samples from metastatic TNBC patients on PARP inhibitor monotherapy provide insight into rational PARP inhibitor therapy combinations

ONC201 and an MEK Inhibitor Trametinib Synergistically Inhibit the Growth of Triple-Negative Breast Cancer Cells

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