Determinants of variability of five programmed death ligand-1 immunohistochemistry assays in non-small cell lung cancer samples.

Programmed death ligand-1 (PD-L1) expression as determined by immunohistochemistry (IHC) is potentially predictive of clinical outcome. The aim of this study was to assess the concordance of reported PD-L1 IHC assays and investigate factors influencing variability. Consecutive sections from 20 non-small cell lung cancers (NSCLCs) comprising resection, core biopsy, cytology and pleural fluid samples underwent IHC with 5 different antibody/autostainer combinations: 22C3/Link48, 28-8/BOND-MAX, E1L3N/BOND-MAX, SP142/BenchMark and SP263/BenchMark. PD-L1 RNA levels were assessed using RNAscope. The frequency of positive cases using scoring thresholds from clinical trials was 72%, 33%, 61%, 56%, and 33% for the 5 IHC protocols respectively, and 33% for RNAscope. Pairwise agreement on the classification of cases as positive or negative for PD-L1 expression ranged from 61%-94%. On a continuous scale, the lowest correlation was between 28-8/BOND-MAX and SP142/BenchMark (R2=0.25) and highest was between 22C3/Link48 and E1L3N/BOND-MAX (R2=0.71). When cases were ordered according to tumor cell (TC)%, a similar ranking of cases across IHC protocols could be observed, albeit with different quanta and limits of detection. Single-slide OPAL 7-color fluorescence IHC analysis revealed a high degree of co-localization of staining from the 5 PD-L1 antibodies. Using SP142 antibody in a BOND-MAX protocol led to increased TC% quanta, while retaining a similar ranking of samples according to TC%. The results of this study highlight tumor PD-L1 status can vary significantly according to IHC protocol. Protocol-dependent staining intensities and nominated thresholds for positivity contribute to this variability, while the antibody used appears to be less of a factor.

Acquired resistance to PI3K/mTOR inhibition is associated with mitochondrial DNA mutation and glycolysis.

Acquired resistance (AQR) to drug treatment occurs frequently in cancer patients and remains an impediment to successful therapy. The aim of this study was to gain insight into how AQR arises following the application of PI3K/mTOR inhibitors. H1975 lung cancer cells with EGFR T790M mutations that confer resistance to EGFR inhibitors underwent prolonged treatment with the PI3K/mTOR inhibitor, BEZ235. Monoclonal cells with stable and increased resistance to BEZ235 were obtained after 8 months treatment. These AQR clones showed class-specific resistance to PI3K/mTOR inhibitors, reduced G1 cell cycle arrest and impedance of migration following PI3K/mTOR inhibition, reduced PTEN expression and increased Akt and S6RP phosphorylation. Transcriptome analysis revealed the AQR clones had increased expression of the metabolite transporters SLC16A9 and SLC16A7, suggestive of altered cell metabolism. Subsequent experiments revealed that AQR clones possess features consistent with elevated glycolysis, including increased levels of glucose, lactate, glutamine, glucose dependence, GLUT1 expression, and rates of post-glucose extracellular acidification, and decreased levels of reactive oxygen species and rates of oxygen consumption. Combination treatment of BEZ235 with the glycolysis inhibitor 3-bromopyruvate was synergistic in AQR clones, but only additive in parental cells. DNA sequencing revealed the presence of a mitochondrial DNA (mtDNA) MT-C01 variant in AQR but not parental cells. Depletion of mitochondrial DNA in parental cells induced resistance to BEZ235 and other PI3K/mTOR inhibitors, and was accompanied by increased glycolysis. The results of this study provide the first evidence that a metabolic switch associated with mtDNA mutation can be an underlying mechanism for AQR.

The Warburg effect and drug resistance.

: The Warburg effect describes the increased utilization of glycolysis rather than oxidative phosphorylation by tumour cells for their energy requirements under physiological oxygen conditions. This effect has been the basis for much speculation on the survival advantage of tumour cells, tumourigenesis and the microenvironment of tumours. More recently, studies have begun to reveal how the Warburg effect could influence drug efficacy and how our understanding of tumour energetics could be exploited to improve drug development. In particular, evidence is emerging demonstrating how better modelling of the tumour metabolic microenvironment could lead to a better prediction of drug efficacy and the identification of new combination strategies. This review will provide details of the current understanding of the complex interplay between glucose metabolism and pharmacology and discuss opportunities for utilizing the Warburg effect in future drug development.

Methodological aspects of whole-genome bisulfite sequencing analysis.

The combination of DNA bisulfite treatment with high-throughput sequencing technologies has enabled investigation of genome-wide DNA methylation beyond CpG sites and CpG islands. These technologies have opened new avenues to understand the interplay between epigenetic events, chromatin plasticity and gene regulation. However, the processing, managing and mining of this huge volume of data require specialized computational tools and statistical methods that are yet to be standardized. Here, we describe a complete bisulfite sequencing analysis workflow, including recently developed programs, highlighting each of the crucial analysis steps required, i.e. sequencing quality control, reads alignment, methylation scoring, methylation heterogeneity assessment, genomic features annotation, data visualization and determination of differentially methylated cytosines. Moreover, we discuss the limitations of these technologies and considerations to perform suitable analyses.

Molecular-assisted immunohistochemical optimization.

Immunohistochemistry (IHC) is an essential tool in diagnostic surgical pathology, allowing analysis of protein subcellular localization. The use of IHC by different laboratories has lead to inconsistencies in published literature for several antibodies, due to either interpretative (inter-observer variation) or technical reasons. These disparities have major implications in both clinical and research settings. In this study, we report our experience conducting an IHC optimization of antibodies against five proteins previously identified by proteomic analysis to be breast cancer biomarkers, namely 6PGL (PGLS), CAZ2 (CAPZA2), PA2G4 (EBP1) PSD2 and TKT. Large variations in the immunolocalizations and intensities were observed when manipulating the antigen retrieval method and primary antibody incubation concentration. However, the use of an independent molecular analysis method provided a clear indication in choosing the appropriate biologically and functionally relevant "staining pattern". Without this latter step, each of these contradictory results would have been a priori "technically acceptable" and would have led to different biological and functional interpretations of these proteins and potentially different applications in a routine pathology setting. Thus, we conclude that full validation of immunohistochemical protocols for scientific and clinical use will require the incorporation of biological knowledge of the biomarker and the disease in question.

TRARESA: a tissue microarray-based hospital system for biomarker validation and discovery.

Formalin fixed and paraffin embedded tissue (FFPE) collections in pathology departments are the largest resource for retrospective biomedical research studies. Based on the literature analysis of FFPE related research, as well as our own technical validation, we present the Translational Research Arrays (TRARESA), a tissue microarray centred, hospital based, translational research conceptual framework for both validation and/or discovery of novel biomarkers. TRARESA incorporates the analysis of protein, DNA and RNA in the same samples, correlating with clinical and pathological parameters from each case, and allowing (a) the confirmation of new biomarkers, disease hypotheses and drug targets, and (b) the postulation of novel hypotheses on disease mechanisms and drug targets based on known biomarkers. While presenting TRARESA, we illustrate the use of such a comprehensive approach. The conceptualisation of the role of FFPE-based studies in translational research allows the utilisation of this commodity, and adds to the hypothesis-generating armamentarium of existing high-throughput technologies.