Dana Pascovici

The clinical management of Barrett’s esophagus (BE) and the risk of esophageal adenocarcinoma (EAC) is dependent on the presence or absence of dysplasia. The histopathological diagnosis of dysplasia is unreliable however, and would benefit from additional diagnostic criteria. Here, we obtained EM-seq whole-genome methylation profiles from 86 samples across the BE/EAC disease spectrum, notably supplementing the scant existing methylation evidence for low-grade and high-grade dysplasia. While the bulk of methylation changes occur in the transition from normal squamous epithelium to intestinal metaplasia (non-dysplastic Barrett’s esophagus), we identified a smaller set of changes that mark the onset of dysplasia and progression to EAC. Methylation changes were broadly independent of copy number variation. They were tightly anticorrelated with RNA-seq expression for some genes. Deconvolution of the bulk methylation signatures into constituent cell types revealed four sample groupings enriched with a particular cell type (squamous, columnar, lymphoid and erythroid cells), somewhat reflecting existing clinical classifications. We outline potential markers that could improve the diagnosis of metaplasia and dysplasia in EAC.

New prognostic biomarkers for oesophageal adenocarcinoma (OAC) may help treatment planning as current staging does not accurately predict survival for many patients. We used a 451 cancer-associated gene panel to assess genomic alterations associated with survival for a cohort of 65 OAC patients who underwent surgical resection without perioperative treatment, reflecting institutional practice at the time. Median age at operation was 72 years, 88% were male, median 32 lymph nodes were removed per patient, and minimum follow-up exceeded 11 years. TNM stages (pTNM, 8 ^th ed.) were 14% stage 1, 14% stage 2, 45% stage 3, and 6% stage 4 (non-locoregional nodal metastases). Copy number changes were common, and somatic mutations were similar to those reported previously. Genetic associations with worse survival included amplification of CCND1 (HR=3.08, p=0.02), EGFR (HR=2.98, p=0.01), loss of ARID2 (HR=2.12, p=0.05), KMT2D (HR=1.99, p=0.07) and missense mutation within RYR1 (HR=2.68, p=0.01). This study identifies candidate genomic prognostic biomarkers in OAC using a cohort treated by surgery alone, enabling assessment of tumour biology independent of the confounding effects of peri-operative systemic therapy and radiotherapy. Several of the identified alterations are potentially targetable, supporting further investigation of genomic profiling to refine prognostication and guide treatment selection.

Esophageal adenocarcinoma (EAC) has a poor five-year survival rate and one of the fastest-rising incidences of any cancer. The presence of dysplasia in Barrett’s esophagus (BE) is the main risk factor for EAC development and guides clinical management. Unfortunately, the current histopathological diagnosis of dysplasia is unreliable, with poor inter-observer agreement, highlighting the need for novel biomarkers that can improve diagnostic accuracy. Here, we performed transcriptome profiling across the full spectrum of BE-related neoplasia in 85 samples to delineate gene expression alterations in progressively worse disease stages and identify biomarkers that could complement histopathology to improve the detection of dysplasia and EAC in endoscopic biopsy specimens. Differential gene expression and pathway analyses revealed that the most extensive transcriptional changes occurred during the transition from normal squamous (NSq) to non-dysplastic BE (NDBE), consistent with metaplastic transformation. Compared to NDBE, dysplasia was characterized by enhanced cellular growth and proliferation; upregulation of immune processes and oncogenic signaling pathways were present in EAC. Using machine learning approaches, we identified a novel five-gene panel suitable for a potential RNAseq-based diagnostic test (SLC11A1, IL36A, LUCAT1, MIR215, RNU6-954P) and performed an initial validation of this signature in an additional 51 samples. We also identified several potential novel immunohistochemical markers that may warrant further evaluation, including TREM1, CXCL5, OSM, and motilin. In summary, by delineating transcriptional changes across the full disease spectrum, this study identifies several candidate biomarkers for improving current diagnostic methods for Barrett’s dysplasia and EAC. Significance statement: Current histopathological assessment of Barrett’s dysplasia has limited diagnostic reproducibility. By defining transcriptional changes across the disease spectrum, this study identifies novel biomarker candidates for the detection of dysplasia and adenocarcinoma. These include a five-gene panel for a potential RNA sequencing- based diagnostic test to complement histopathology.

Neural regeneration and neuroprotection represent strategies for future management of neurodegenerative disorders such as Alzheimer’s disease (AD) or glaucoma. However, the complex molecular mechanisms that are involved in neuroprotection are not clearly understood. A promising candidate that maintains neuroprotective signaling networks is neuroserpin (Serpini1), a serine protease inhibitor expressed in neurons which selectively inhibits extracellular tissue-type plasminogen activator (tPA)/plasmin and plays a neuroprotective role during ischemic brain injury. Abnormal function of this protein has been implicated in several conditions including stroke, glaucoma, AD, and familial encephalopathy with neuroserpin inclusion bodies (FENIB). Here, we explore the potential biochemical roles of Serpini1 by comparing proteome changes between neuroserpin-deficient (NS^−/−) and control mice, in the retina (RE), optic nerve (ON), frontal cortex (FC), visual cortex (VC), and cerebellum (CB). To achieve this, a multiple-plex quantitative proteomics approach using isobaric tandem mass tag (TMT) technology was employed followed by functional enrichment and protein–protein interaction analysis. We detected around 5000 proteins in each tissue and a pool of 6432 quantified proteins across all regions, resulting in a pool of 1235 differentially expressed proteins (DEPs). Principal component analysis and hierarchical clustering highlighted similarities and differences in the retina compared to various brain regions, as well as differentiating NS^−/− proteome signatures from control samples. The visual cortex revealed the highest number of DEPs, followed by cerebellar regions. Pathway analysis unveiled region-specific changes, including visual perception, focal adhesion, apoptosis, glutamate receptor activation, and supramolecular fiber organization in RE, ON, FC, VC, and CB, respectively. These novel findings provide comprehensive insights into the region-specific networking of Serpini1 in the central nervous system, further characterizing its potential role as a neuroprotective agent. Data are available via ProteomeXchange with identifier PXD046873.

Understanding the mechanisms that drive TDP-43 pathology is integral to combating amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD) and other neurodegenerative diseases. Here we generated a longitudinal quantitative proteomic map of the cortex from the cytoplasmic TDP-43 rNLS8 mouse model of ALS and FTLD, and developed a complementary open-access webtool, TDP-map (https://shiny.rcc.uq.edu.au/TDP-map/). We identified distinct protein subsets enriched for diverse biological pathways with temporal alterations in protein abundance, including increases in protein folding factors prior to disease onset. This included increased levels of DnaJ homolog subfamily B member 5, DNAJB5, which also co-localized with TDP-43 pathology in diseased human motor cortex. DNAJB5 over-expression decreased TDP-43 aggregation in cell and cortical neuron cultures, and knockout of Dnajb5 exacerbated motor impairments caused by AAV-mediated cytoplasmic TDP-43 expression in mice. Together, these findings reveal molecular mechanisms at distinct stages of ALS and FTLD progression and suggest that protein folding factors could be protective in neurodegenerative diseases.

Background: Alzheimer’s disease (AD) is a neurodegenerative age‐dependent disorder which disrupts cognition and eventually leads to death. Neural regeneration and neuroprotection represent promising therapeutic approaches for AD. The predominantly neurally expressed serine protease inhibitor, neuroserpin, selectively inhibits plasminogen activators/plasmin and plays a neuroprotective role in AD and glaucoma. Abnormal function of this protein has been implicated in stroke, glaucoma, AD and FENIB. Here we report the neuroprotective mechanisms of neuroserpin in different regions of brain, retina, and optic nerve in mouse.Method: Brains, retinas and optic nerves from 12‐month C57BL6/J neuroserpin knockout (NeuS^−/−) mice (n = 5) and their wildtypes were harvested. Brains were further dissected into frontal cortex, visual cortex and cerebellum. Sample were labelled using 10‐plex TMT, fractionated by high pH reversed phase chromatography and analysed by LC‐ESI‐MS/MS on QExactive HFX mass spectrometer. Bioinformatic analyses were performed using TMTPrepPro package, OmicsPlayGround pipeline and WGCNA package. The Candidate pathways were further validated using western blotting, immunofluorescence and in‐house meta‐analysis package for human AD brain tissues.Result: The effects of neuroserpin vary depending on the brain region. We detected the highest number of differentially expressed genes (DEG) in the visual cortex of KO/WT mice (∼ 700). Several pathways like synaptic plasticity, neurotransmitter transport and mitochondrial electron chain showed dysregulation in most of the regions. Most importantly, neuroserpin increases BCL2/BAX ratio through BDNF/TrkB axis in all regions. This is followed by downstream activation of ERK and Akt/ PI3K signalling which results in anti‐apoptotic and survival effects, without disrupting autophagy.Conclusion: Our results suggest that neuroserpin plays a neuroprotective role in murine brain and retina, reducing neuronal apoptosis by inhibiting apoptotic pathways. however, its precise mechanism of action is region dependent. These findings provide insights into neural regeneration and novel targets that can be disease modifying for AD.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Measuring host-bacteriophage dynamics is an important approach to understanding bacterial survival functions and responses to infection. The model Microviridae bacteriophage φX174 is endemic to the human gut and has been studied for over seventy years but the host response to infection has never been investigated in detail. To address this gap in our understanding of this important interaction within our microbiome we have measured host Escherichia coli C proteomic and transcriptomic response to φX174 infection. We used mass spectrometry and RNA-seq to identify and quantify all 11 φX174 proteins and over 1,700 E. coli proteins, enabling us to comprehensively map host pathways involved in φX174 infection. Most notably, we see significant host responses centered on membrane damage and remodeling, cellular chaperone and translocon activity, and lipoprotein processing, which we speculate is due to the peptidoglycan-disruptive effects of the φX174 lysis protein E on MraY activity. We also observe the massive upregulation of small heat-shock proteins IbpA/B, along with other heat shock pathway chaperones, and speculate on how the specific characteristics of holdase protein activity may be beneficial for viral infections. Together, this study enables us to begin to understand the proteomic and transcriptomic host responses of E. coli to Microviridae infections and contributes insights to the activities of this important model phage. IMPORTANCE: A major part of the healthy human gut microbiome are the Microviridae bacteriophage, exemplified by the model φX174 phage. Although much has been learned from studying φX174 over the last half century, until this work, the E. coli host response to infection has never been investigated in detail. We reveal the proteomic and transcriptomic pathways differentially regulated during the φX174 infection cycle, and uncover the details of a coordinated cellular response to membrane damage that results in increased lipoprotein processing and membrane trafficking, likely due to the phage antibiotic-like lysis protein. We also reveal that small heat shock proteins IbpA/B are massively upregulated during infection and that these holdase chaperones are highly conserved across the domains of life, indicating that reliance on them is likely widespread across viruses.

We describe a useful workflow for characterizing proteomics experiments incorporating many conditions and abundance data, incorporating the popular approach weighted gene correlation network analysis (WGCNA) and functional annotation with the PloGO2 R package, the latter of which we have extended and made available to Bioconductor. The approach can use quantitative data from labelled or label-free experiments, and was developed to handle multiple files stemming from data partition or multiple pairwise comparisons. The WGCNA approach can similarly produce a potentially large number of clusters of interest, which can also be characterised functionally using PloGO2. Enrichment analysis will identify clusters or subsets of proteins of interest, and the WGCNA network topology scores will produce a ranking of proteins within these clusters or subsets. This can naturally lead to prioritized proteins to be considered for further analysis or as candidates of interest for validation in the context of complex experiments. We demonstrate the use of the package on two published datasets using 2 different biological systems (plant and human plasma) and proteomics platforms (SWATH and TMT); an analysis of the effect of drought on rice over time generated using TMT, and a paediatric plasma sample dataset generated using SWATH. In both, the automated workflow recapitulates key insights or observations of the published papers, and provides additional suggestions for further investigation. These findings indicate that dataset analysis using WGCNA combined with the updated PloGO2 package is a powerful method to gain biological insights from complex multi-faceted proteomics experiments.

Background: Progesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms. Results: We demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/AKT activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/AKT activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells. Conclusions: Altogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology.