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.

Endogenous Gastrin Collaborates With Mutant KRAS in Pancreatic Carcinogenesis.

OBJECTIVE: The KRAS gene is the most frequently mutated gene in pancreatic cancer, and no successful anti-Ras therapy has been developed. Gastrin has been shown to stimulate pancreatic cancer in an autocrine fashion. We hypothesized that reactivation of the peptide gastrin collaborates with KRAS during pancreatic carcinogenesis. METHODS: LSL-Kras; P48-Cre (KC) mutant KRAS transgenic mice were crossed with gastrin-KO (GKO) mice to develop GKO/KC mice. Pancreata were examined for 8 months for stage of pancreatic intraepithelial neoplasia lesions, inflammation, fibrosis, gastrin peptide, and microRNA expression. Pancreatic intraepithelial neoplasias from mice were collected by laser capture microdissection and subjected to reverse-phase protein microarray, for gastrin and protein kinases associated with signal transduction. Gastrin mRNA was measured by RNAseq in human pancreatic cancer tissues and compared to that in normal pancreas. RESULTS: In the absence of gastrin, PanIN progression, inflammation, and fibrosis were significantly decreased and signal transduction was reversed to the canonical pathway with decreased KRAS. Gastrin re-expression in the PanINs was mediated by miR-27a. Gastrin mRNA expression was significantly increased in human pancreatic cancer samples compared to normal human pancreas controls. CONCLUSIONS: This study supports the mitogenic role of gastrin in activation of KRAS during pancreatic carcinogenesis.

Reverse phase protein array (RPPA) combined with computational analysis to unravel relevant prognostic factors in non- small cell lung cancer (NSCLC): a pilot study.

In this work high throughput technology and computational analysis were used to study two stage IV lung adenocarcinoma patients treated with standard chemotherapy with markedly different survival (128 months vs 6 months, respectively) and whose tumor samples exhibit a dissimilar protein activation pattern of the signal transduction. Tumor samples of the two patients were subjected to Reverse Phase Protein Microarray (RPPA) analysis to explore the expression/activation levels of 51 signaling proteins. We selected the most divergent proteins based on the ratio of their RPPA values in the two patients with short (s-OS) and long (l-OS) overall survival (OS) and tested them against a EGFR-IGF1R mathematical model. The model with RPPA data showed that the activation levels of 19 proteins were different in the two patients. The four proteins that most distinguished the two patients were BADS155/136 and c-KITY703/719 having a higher activation level in the patient with short survival and p70S6S371/T389 and b-RAFS445 that had a lower activation level in the s-OS patient. The final model describes the interactions between the MAPK and PI3K-mTOR pathways, including 21 nodes. According to our model mTOR and ERK activation levels were predicted to be lower in the s-OS patient than the l-OS patient, while the AMPK activation level was higher in the s-OS patient. Moreover, KRAS activation was predicted to be higher in the l-OS KRAS-mutated patient. In accordance with their different biological properties, the Moment Independent Robustness Indicator in s-OS and l-OS predicted the interaction of MAPK and mTOR and the crosstalk AKT with p90RSK as candidates to be prognostic factors and drug targets.

Kinase-driven metabolic signalling as a predictor of response to carboplatin-paclitaxel adjuvant treatment in advanced ovarian cancers.

BACKGROUND: The biological mechanisms underlying early- and advanced-stage epithelial ovarian cancers (EOCs) are still poorly understood. This study explored kinase-driven metabolic signalling in early and advanced EOCs, and its role in tumour progression and response to carboplatin-paclitaxel treatment. METHODS: Tumour epithelia were isolated from two independent sets of primary EOC (n=72 and 30 for the discovery and the validation sets, respectively) via laser capture microdissection. Reverse phase protein microarrays were used to broadly profile the kinase-driven metabolic signalling of EOC with particular emphasis on the LBK1-AMPK and AKT-mTOR axes. Signalling activation was compared between early and advanced lesions, and carboplatin-paclitaxel-sensitive and -resistant tumours. RESULTS: Advanced EOCs were characterised by a heterogeneous kinase-driven metabolic signature and decreased phosphorylation of the AMPK-AKT-mTOR axis compared to early EOC (P<0.05 for AMPKα T172, AMPKα1 S485, AMPKß1 S108, AKT S473 and T308, mTOR S2448, p70S6 S371, 4EBP1 S65, GSK-3 α/ß S21/9, FOXO1 T24/FOXO3 T32, and FOXO1 S256). Advanced tumours with low relative activation of the metabolic signature and increased FOXO1 T24/FOXO3 T32 phosphorylation (P=0.041) were associated with carboplatin-paclitaxel resistance. CONCLUSIONS: If validated in a larger cohort of patients, the decreased AMPK-AKT-mTOR activation and phosphorylation of FOXO1 T24/FOXO3 T32 may help identify carboplatin-paclitaxel-resistant EOC patients.

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 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.