Temporal dynamics from phosphoproteomics using endoscopic biopsy specimens provides new therapeutic targets in stage IV gastric cancer

Inhalation of hydrogen gas mitigates sevoflurane-induced neuronal apoptosis in the neonatal cortex and is associated with changes in protein phosphorylation

Inhalation of hydrogen (H2) gas is therapeutically effective for cerebrovascular diseases, neurodegenerative disorders, and neonatal brain disorders including pathologies induced by anesthetic gases. To understand the mechanisms underlying the protective effects of H2 on the brain, we investigated the molecular signals affected by H2 in sevoflurane-induced neuronal cell death. We confirmed that neural progenitor cells are susceptible to sevoflurane and undergo apoptosis in the retrosplenial cortex of neonatal mice. Co-administration of 1-8% H2 gas for 3 h to sevoflurane-exposed pups suppressed elevated caspase-3-mediated apoptotic cell death and concomitantly decreased c-Jun phosphorylation and activation of the c-Jun pathway, all of which are induced by oxidative stress. Anesthesia-induced increases in lipid peroxidation and oxidative DNA damage were alleviated by H2 inhalation. Phosphoproteome analysis revealed enriched clusters of differentially phosphorylated proteins in the sevoflurane-exposed neonatal brain that included proteins involved in neuronal development and synaptic signaling. H2 inhalation modified cellular transport pathways that depend on hyperphosphorylated proteins including microtubule-associated protein family. These modifications may be involved in the protective mechanisms of H2 against sevoflurane-induced neuronal cell death.

Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited number of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a direct read-out of aberrant signaling and the resultant clinically relevant phenotype. Mass spectrometry (MS)-based proteomics and phosphoproteomics were applied to 42 PDAC tumors. Data encompassed over 19 936 phosphoserine or phosphothreonine (pS/T; in 5412 phosphoproteins) and 1208 phosphotyrosine (pY; in 501 phosphoproteins) sites and a total of 3756 proteins. Proteome data identified three distinct subtypes with tumor intrinsic and stromal features. Subsequently, three phospho-subtypes were apparent: two tumor intrinsic (Phos1/2) and one stromal (Phos3), resembling known PDAC molecular subtypes. Kinase activity was analyzed by the Integrative iNferred Kinase Activity (INKA) scoring. Phospho-subtypes displayed differential phosphorylation signals and kinase activity, such as FGR and GSK3 activation in Phos1, SRC kinase family and EPHA2 in Phos2, and EGFR, INSR, MET, ABL1, HIPK1, JAK, and PRKCD in Phos3. Kinase activity analysis of an external PDAC cohort supported our findings and underscored the importance of PI3K/AKT and ERK pathways, among others. Interestingly, unfavorable patient prognosis correlated with higher RTK, PAK2, STK10, and CDK7 activity and high proliferation, whereas long survival was associated with MYLK and PTK6 activity, which was previously unknown. Subtype-associated activity profiles can guide therapeutic combination approaches in tumor and stroma-enriched tissues, and emphasize the critical role of parallel signaling pathways. In addition, kinase activity profiling identifies potential disease markers with prognostic significance.

Principles of phosphoproteomics and applications in cancer research

Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.

Integration of pharmacoproteomic and computational approaches reveals the cellular signal transduction pathways affected by apatinib in gastric cancer cell lines

Apatinib is known to be a highly selective vascular endothelial growth factor receptor 2 (VEGFR2) inhibitor with anti-angiogenic and anti-tumor properties. In a phase III study, the objective response rate to apatinib was low. It remains unclear why the effectivity of apatinib varies among patients and what type of patients are candidates for the treatment. In this study, we investigated the anti-tumor efficacy of apatinib against 13 gastric cancer cell lines and found that it differed depending on the cell line. Using integrated wet and dry approaches, we showed that apatinib was a multi-kinase inhibitor of c-Kit, RAF1, VEGFR1, VEGFR2, and VEGFR3, predominantly inhibiting c-Kit. Notably, KATO-III, which was the most apatinib-sensitive among the gastric cancer cell lines investigated, was the only cell line expressing c-Kit, RAF1, VEGFR1, and VEGFR3 but not VEGFR2. Furthermore, we identified SNW1 as a molecule affected by apatinib that plays an important role in cell survival. Finally, we identified the molecular network related to SNW1 that was affected by treatment with apatinib. These results suggest that the mechanism of action of apatinib in KATO-III cells is independent of VEGFR2 and that the differential efficacy of apatinib was due to differences in expression patterns of receptor tyrosine kinases. Furthermore, our results suggest that the differential efficacy of apatinib in gastric cell lines may be attributed to SNW1 phosphorylation levels at a steady state. These findings contribute to a deeper understanding of the mechanism of action of apatinib in gastric cancer cells.

Biomarker Analysis of Formalin-Fixed Paraffin-Embedded Clinical Tissues Using Proteomics

The relatively recent developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. This review will discuss the history of these developments and provide examples of how they are currently being used to identify biomarkers and diagnose diseases such as cancer.

A multi-institutional study to evaluate the feasibility of next-generation sequencing and genomic analysis using formalin-fixed, paraffin-embedded biopsies of gastric cancer

BACKGROUND

Formalin-fixed, paraffin-embedded (FFPE) samples acquired and preserved adequately are expected to faithfully maintain tumor characteristics. Endoscopic biopsy tissues represent an attractive resource for identifying predictive biomarkers to evaluate pretreatment responses of patients with advanced gastric cancer (GC). However, whether genomic profiles obtained through next-generation sequencing (NGS) using biopsy samples match well with those gained from surgical FFPE samples remains a concern.

METHODS

We collected 50 FFPE samples (26 biopsies and 24 surgical samples) from patients with GC who participated in phase III clinical trial JCOG1509. The quality and quantity of FFPE samples were determined for deep sequencing using NGS. We queried a 435-gene panel CANCERPLEX-JP to generate comprehensive genomic profiling data including the tumor mutation burden (TMB).

RESULTS

The median DNA yields and NGS success rates of biopsy samples compared with surgical samples were 879 ng and 80.8% vs 8523 ng and 100%, respectively. Epstein-Barr virus and microsatellite instability-high were detected in 9.5% of biopsy samples. Comparing the genomic profiles of 18 paired samples for which NGS data were available, we detected identical somatic mutations in paired biopsy and surgical samples (kappa coefficient, 0.8692). TMB positively correlated between paired biopsy and surgical samples (correlation coefficient, 0.6911).

CONCLUSIONS

NGS is applicable to the analysis of FFPE samples of GC acquired by the endoscopic biopsy, and the data were highly concordant with those obtained from surgical specimens of the same patients.