Transcriptomic convergence despite genomic divergence drive field cancerization in synchronous squamous tumors.

Introduction: Field cancerization is suggested to arise from imbalanced differentiation in individual basal progenitor cells leading to clonal expansion of mutant cells that eventually replace the epithelium, although without evidence. Methods: We performed deep sequencing analyses to characterize the genomic and transcriptomic landscapes of field change in two patients with synchronous aerodigestive tract tumors. Results: Our data support the emergence of numerous genetic alterations in cancer-associated genes but refutes the hypothesis that founder mutation(s) underpin this phenomenon. Mutational signature analysis identified defective homologous recombination as a common underlying mutational process unique to synchronous tumors. Discussion: Our analyses suggest a common etiologic factor defined by mutational signatures and/or transcriptomic convergence, which could provide a therapeutic opportunity.

Artificial intelligence defines protein-based classification of thyroid nodules.

Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.

Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis.

Peritoneal carcinomatosis (PC) present a ubiquitous clinical conundrum in all intra-abdominal malignancies. Via functional and transcriptomic experiments of ascites-treated PC cells, we identify STAT3 as a key signaling pathway. Integrative analysis of publicly available databases and correlation with clinical cohorts (n = 7,359) reveal putative clinically significant activating ligands of STAT3 signaling. We further validate a 3-biomarker prognostic panel in ascites independent of clinical covariates in a prospective study (n = 149). Via single-cell sequencing experiments, we uncover that PAI-1, a key component of the prognostic biomarker panel, is largely secreted by fibroblasts and mesothelial cells. Molecular stratification of ascites using PAI-1 levels and STAT3 activation in ascites-treated cells highlight a therapeutic opportunity based on a phenomenon of paracrine addiction. These results are recapitulated in patient-derived ascites-dependent xenografts. Here, we demonstrate therapeutic proof of concept of direct ligand inhibition of a prognostic target within an enclosed biological space.

Stratification of follicular thyroid tumours using data-independent acquisition proteomics and a comprehensive thyroid tissue spectral library.

Thyroid nodules occur in about 60% of the population. A major challenge in thyroid nodule diagnosis is to distinguish between follicular adenoma (FA) and carcinoma (FTC). Here, we present a comprehensive thyroid spectral library covering five types of thyroid tissues. This library includes 121 960 peptides and 9941 protein groups. This spectral library can be used to quantify up to 7863 proteins from thyroid tissues, and can also be used to develop parallel reaction monitoring (PRM) assays for targeted protein quantification. Next, to stratify follicular thyroid tumours, we compared the proteomes of 24 FA and 22 FTC samples, and identified 204 differentially expressed proteins (DEPs). Our data suggest altered ferroptosis pathways in malignant follicular carcinoma. In all, 31 selected proteins effectively distinguished follicular tumours. Of those DEPs, nine proteins were further verified by PRM in an independent cohort of 18 FA and 19 FTC. Together, we present a comprehensive spectral library for DIA and targeted proteomics analysis of thyroid tissue specimens, and identified nine proteins that could potentially distinguish FA and FTC.

High-throughput proteomics and AI for cancer biomarker discovery.

Biomarkers are assayed to assess biological and pathological status. Recent advances in high-throughput proteomic technology provide opportunities for developing next generation biomarkers for clinical practice aided by artificial intelligence (AI) based techniques. We summarize the advances and limitations of cancer biomarkers based on genomic and transcriptomic analysis, as well as classical antibody-based methodologies. Then we review recent progresses in mass spectrometry (MS)-based proteomics in terms of sample preparation, peptide fractionation by liquid chromatography (LC) and mass spectrometric data acquisition. We highlight applications of AI techniques in high-throughput clinical studies as compared with clinical decisions based on singular features. This review sets out our approach for discovering clinical biomarkers in studies using proteomic big data technology conjoined with computational and statistical methods.

Pairing a prognostic target with potential therapeutic strategy for head and neck cancer.

OBJECTIVES: We have previously identified and validated a panel of molecular prognostic markers (ATP13A3, SSR3, and ANO1) for Head and Neck Squamous Cell Carcinoma (HNSCC). The aim of this study was to investigate the consequence of ATP13A3 dysregulation on signaling pathways, to aid in formulating a therapeutic strategy targeting ATP13A3-overexpressing HNSCC. MATERIALS AND METHODS: Gene Set Enrichment Analysis (GSEA) was performed on HNSCC microarray expression data (Internal local dataset [n = 92], TCGA [n = 232], EMBL [n = 81]) to identify pathways associated with high expression of ATP13A3. Validation was performed using immunohistochemistry (IHC) on tissue microarrays (TMAs) of head and neck cancers (n = 333), staining for ATP13A3 and phosphorylated Aurora kinase A (phospho-T288). Short interfering RNA was used to knockdown ATP13A3 expression in patient derived HNSCC cell lines. Protein expression of ATP13A3 and Aurora kinase A was then assessed by immunoblotting. RESULTS: GSEA identified Aurora kinase pathway to be associated with high expression of ATP13A3 (p = 0.026). The Aurora kinase pathway was also associated with a trend towards poor prognosis and tumor aggressiveness (p = 0.086, 0.094, respectively). Furthermore, the immunohistochemical staining results revealed a significant association between Aurora kinase activity and high ATP13A3 expression (p < 0.001). Knockdown of ATP13A3 in human head and neck cell lines showed decrease in Aurora kinase A levels. CONCLUSION: Tumors with high ATP13A3 are associated with high Aurora kinase activity. This suggests a potential therapeutic role of Aurora kinase inhibitors in a subset of poor prognosis HNSCC patients with overexpression of ATP13A3.

Phenotype Classification using Proteome Data in a Data-Independent Acquisition Tensor Format.

A novel approach for phenotype prediction is developed for data-independent acquisition (DIA) mass spectrometric (MS) data without the need for peptide precursor identification using existing DIA software tools. The first step converts the DIA-MS data file into a new file format called DIA tensor (DIAT), which can be used for the convenient visualization of all the ions from peptide precursors and fragments. DIAT files can be fed directly into a deep neural network to predict phenotypes such as appearances of cats, dogs, and microscopic images. As a proof of principle, we applied this approach to 102 hepatocellular carcinoma samples and achieved an accuracy of 96.8% in distinguishing malignant from benign samples. We further applied a refined model to classify thyroid nodules. Deep learning based on 492 training samples achieved an accuracy of 91.7% in an independent cohort of 216 test samples. This approach surpassed the deep-learning model based on peptide and protein matrices generated by OpenSWATH. In summary, we present a new strategy for DIA data analysis based on a novel data format called DIAT, which enables facile two-dimensional visualization of DIA proteomics data. DIAT files can be directly used for deep learning for biological and clinical phenotype classification. Future research will interpret the deep-learning models emerged from DIAT analysis.

An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours.

Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis. To facilitate such downstream analyses, laser capture microdissection (LCM) could be utilized to obtain pure cell populations. The aim of this protocol study was to develop a methodology to obtain high-quality expression data from matched primary tumours and metastases by utilizing LCM to isolate pure cellular populations. We demonstrate an optimized LCM protocol which reproducibly delivered intact RNA used for RNA sequencing and quantitative polymerase chain reaction (qPCR). After pathologic annotation of normal epithelial, tumour and stromal components, LCM coupled with cDNA library generation provided for successful RNA sequencing. To illustrate our framework's potential to identify targets that would otherwise be missed with conventional bulk tumour sequencing, we performed qPCR and immunohistochemical technical validation to show that the genes identified were truly expressed only in certain sub-components. This study suggests that the combination of matched tissue specimens with tissue microdissection and NGS provides a viable platform to unmask hidden biomarkers and provides insight into tumour biology at a higher resolution.

ERO1α promotes hypoxic tumor progression and is associated with poor prognosis in pancreatic cancer.

Pancreatic cancer is a leading cause of mortality worldwide due to the difficulty of detecting early-stage disease and our poor understanding of the mediators that drive progression of hypoxic solid tumors. We therefore used a heavy isotope 'pulse/trace' proteomic approach to determine how hypoxia (Hx) alters pancreatic tumor expression of proteins that confer treatment resistance, promote metastasis, and suppress host immunity. Using this method, we identified that hypoxia stress stimulates pancreatic cancer cells to rapidly translate proteins that enhance metastasis (NOTCH2, NCS1, CD151, NUSAP1), treatment resistance (ABCB6), immune suppression (NFIL3, WDR4), angiogenesis (ANGPT4, ERO1α, FOS), alter cell metabolic activity (HK2, ENO2), and mediate growth-promoting cytokine responses (CLK3, ANGPTL4). Database mining confirmed that elevated gene expression of these hypoxia-induced mediators is significantly associated with poor patient survival in various stages of pancreatic cancer. Among these proteins, the oxidoreductase enzyme ERO1α was highly sensitive to induction by hypoxia stress across a range of different pancreatic cancer cell lines and was associated with particularly poor prognosis in human patients. Consistent with these data, genetic deletion of ERO1α substantially reduced growth rates and colony formation by pancreatic cancer cells when assessed in a series of functional assays in vitro. Accordingly, when transferred into a mouse xenograft model, ERO1α-deficient tumor cells exhibited severe growth restriction and negligible disease progression in vivo. Together, these data indicate that ERO1α is potential prognostic biomarker and novel drug target for pancreatic cancer therapy.

Roles and Regulation of Long Noncoding RNAs in Hepatocellular Carcinoma.

Next-generation sequencing has uncovered thousands of long noncoding RNAs (lncRNA). Many are reported to be aberrantly expressed in various cancers, including hepatocellular carcinoma (HCC), and play key roles in tumorigenesis. This review provides an in-depth discussion of the oncogenic mechanisms reported to be associated with deregulated HCC-associated lncRNAs. Transcriptional expression of lncRNAs in HCC is modulated through transcription factors, or epigenetically by aberrant histone acetylation or DNA methylation, and posttranscriptionally by lncRNA transcript stability modulated by miRNAs and RNA-binding proteins. Seventy-four deregulated lncRNAs have been identified in HCC, of which, 52 are upregulated. This review maps the oncogenic roles of these deregulated lncRNAs by integrating diverse datasets including clinicopathologic features, affected cancer phenotypes, associated miRNA and/or protein-interacting partners as well as modulated gene/protein expression. Notably, 63 deregulated lncRNAs are significantly associated with clinicopathologic features of HCC. Twenty-three deregulated lncRNAs associated with both tumor and metastatic clinical features were also tumorigenic and prometastatic in experimental models of HCC, and eight of these mapped to known cancer pathways. Fifty-two upregulated lncRNAs exhibit oncogenic properties and are associated with prominent hallmarks of cancer, whereas 22 downregulated lncRNAs have tumor-suppressive properties. Aberrantly expressed lncRNAs in HCC exert pleiotropic effects on miRNAs, mRNAs, and proteins. They affect multiple cancer phenotypes by altering miRNA and mRNA expression and stability, as well as through effects on protein expression, degradation, structure, or interactions with transcriptional regulators. Hence, these insights reveal novel lncRNAs as potential biomarkers and may enable the design of precision therapy for HCC.

A set of molecular markers predicts chemosensitivity to Mitomycin-C following cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for colorectal peritoneal metastasis.

Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) is associated with significant perioperative morbidity and mortality. We aim to generate and validate a biomarker set predicting sensitivity to Mitomycin-C to refine selection of patients with colorectal peritoneal metastasis (CPM) for this treatment. A signature predicting Mitomycin-C sensitivity was generated using data from Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas. Validation was performed on CPM patients who underwent CRS-HIPEC (n = 62) using immunohistochemistry (IHC). We determined predictive significance of our set using overall survival as a surrogate endpoint via a logistic regression model. Three potential biomarkers were identified and optimized for IHC. Patients exhibiting lower expression of PAXIP1 and SSBP2 had poorer survival than those with higher expression (p = 0.045 and 0.140, respectively). No difference was observed in patients with differing DTYMK expression (p = 0.715). Combining PAXIP1 and SSBP2 in a set, patients with two dysregulated protein markers had significantly poorer survival than one or no dysregulated marker (p = 0.016). This set independently predicted survival in a Cox regression model (HR 5.097; 95% CI 1.731-15.007; p = 0.003). We generated and validated an IHC prognostic set which could potentially identify patients who are likely to benefit from HIPEC using Mitomycin-C.

Enabling Mitochondrial Uptake of Lipophilic Dications Using Methylated Triphenylphosphonium Moieties.

Triphenylphosphonium (TPP+) species comprising multiple charges, i.e., bis-TPP+, are predicted to be superior mitochondrial-targeting vectors and are expected to have mitochondrial accumulations 1000-fold greater than TPP+, the current "gold standard". However, bis-TPP+ vectors linked by short hydrocarbon chains ( n < 5) are unable to be taken up by the mitochondria, thus hindering their development as mitochondrial delivery vectors. Through the incorporation of methylated TPP+ moieties (T*PP+), we successfully enabled the accumulation of bis-TPP+ with a short linker chain in isolated mitochondria, as measured by high performance liquid chromatography. These experimental results are further supported by molecular dynamics and ab initio calculations, revealing the strong correlations between mitochondria uptake and molecular volume, surface area, and chemical hardness. Most notably, the molecular volume has been shown to be a strong predictor of accumulation for both mono- and bis-TPP+ salts. Our study underscores the potential of T*PP+ moieties as alternative mitochondrial vectors to overcome low permeation into the mitochondria.

Pulsed SILAC-based proteomic analysis unveils hypoxia- and serum starvation-induced de novo protein synthesis with PHD finger protein 14 (PHF14) as a hypoxia sensitive epigenetic regulator in cell cycle progression.

Hypoxia is an environmental cue that is associated with multiple tumorigenic processes such as immunosuppression, angiogenesis, cancer invasion, metastasis, drug resistance, and poor clinical outcomes. When facing hypoxic stress, cells initiate several adaptive responses such as cell cycle arrest to reduce excessive oxygen consumption and co-activation of oncogenic factors. In order to identify the critical novel proteins for hypoxia responses, we used pulsed-SILAC method to trace the active cellular translation events in A431 cells. Proteomic discovery data and biochemical assays showed that cancer cells selectively activate key glycolytic enzymes and novel ER-stress markers, while protein synthesis is severely suppressed. Interestingly, deprivation of oxygen affected the expression of various epigenetic regulators such as histone demethylases and NuRD (nucleosome remodeling and deacetylase) complex in A431 cells. In addition, we identified PHF14 (the plant homeodomain finger-14) as a novel hypoxia-sensitive epigenetic regulator that plays a key role in cell cycle progress and protein synthesis. Hypoxia-mediated inhibition of PHF14 was associated with increase of key cell cycle inhibitors, p14ARF, p15INK4b, and p16INK4a, which are responsible for G1-S phase transition and decrease of AKT-mTOR-4E-BP1/pS6K signaling pathway, a master regulator of protein synthesis, in response to environmental cues. Analysis of TCGA colon cancer (n=461) and skin cancer (n=470) datasets revealed a positive correlation between PHF14 expression and protein translation initiation factors, eIF4E, eIF4B, and RPS6. Significance of PHF14 gene was further demonstrated by in vivo mouse xenograft model using PHF14 KD cell lines.

Hypoxia-induced tumor exosomes promote M2-like macrophage polarization of infiltrating myeloid cells and microRNA-mediated metabolic shift.

Developing tumors rapidly outgrow their oxygen supply and are subject to hypoxia, which stimulates hypersecretion of tumor-derived exosomes that promote angiogenesis, metastasis, and immunosuppression, but the molecular mediators of these pathological effects remain poorly defined. Using quantitative proteomics, we identified that exosomes produced by hypoxic tumor cells are highly enriched in immunomodulatory proteins and chemokines including CSF-1, CCL2, FTH, FTL, and TGFß. Modeling exosome effects on tumor-infiltrating immune cells, we observed a potent ability of these hypoxia-induced vesicles to influence macrophage recruitment and promote M2-like polarization both in vitro and in vivo. In addition, hypoxic, but not normoxic, tumor exosomes enhanced oxidative phosphorylation in bone marrow-derived macrophages via transfer of let-7a miRNA, resulting in suppression of the insulin-Akt-mTOR signaling pathway. Together, these data demonstrate that hypoxia promotes tumor secretion of biomolecule-loaded exosomes that can modify the immunometabolic profile of infiltrating monocyte-macrophages to better evade host immunity and enhance tumor progression.

Development of a liver-specific Tet-off AAV8 vector for improved safety of insulin gene therapy for diabetes.

BACKGROUND: Diabetes mellitus is caused by a partial or complete lack of insulin production in the body. We have previously shown that a single injection of an adeno-associated virus serotype 8 (AAV8) vector carrying a modified and codon optimized human insulin gene induced hepatic production of insulin and corrected streptozotocin (STZ)-induced diabetes in mice for more than 1 year. Insulin production was constitutive, analogous to long-acting insulin therapy. METHODS: We have developed a single AAV8 vector with a Tet-Off regulatable system as a safety mechanism to turn off insulin secretion should hypoglycaemia develop in vector-treated diabetic mice. We first transfected HepG2 cells or freshly isolated rat hepatocytes in vitro with the Tet-Off system (pAAV-Tetoffbidir -Alb-luc) regulating a luciferase reporter gene. We subsequently incorporated a furin-cleavable codon-optimised human proinsulin cDNA into pAAV-Tetoffbidir backbone to form the doxycycline inducible pAAV-Tetoffbidir -Alb-hINSco. RESULTS: Using STZ-induced diabetic mice, we were able to switch off insulin secretion repeatedly with doxycycline administration, and showed full restoration of insulin secretion on withdrawing doxycycline. CONCLUSIONS: The present study provides proof of concept that, under circumstances when inappropriate basal insulin secretion is a safety concern, insulin secretion from AAV8 gene therapy can be turned off reversibly with doxycycline.

Integrated Multimodal Evaluation of Genotoxicity in ZFN-Modified Primary Human Cells.

Iatrogenic adverse events in clinical trials of retroviral vector-mediated gene-corrected cells have prioritized the urgent need for more comprehensive and stringent assessment of potentially genotoxic off-target alterations and the biosafety of cells intended for therapeutic applications. Genome editing tools such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced palindromic repeats (CRISPR)-Cas9 nuclease systems are being investigated as safer and efficient alternatives for site-directed genome modification. Using site-specific integration into the AAVS1 locus of primary human cells as an example, we present an integrated approach to multimodal investigation of off-target alterations and an evaluation of potential genotoxicity induced by ZFN-mediated integration of a therapeutic transgene.

Soy-Derived Phytochemical Genistein Modifies Chromatome Topology to Restrict Cancer Cell Proliferation.

Epidemiological data indicate that human cancer risk is significantly reduced by the consumption of soy-based foods containing the "phytoestrogen" genistein, which can signal via host cell estrogen receptors. While additional chemoprotective effects of genistein induced by epigenetic factors have also been reported, the key molecules and mechanisms involved are poorly defined. We therefore investigated genistein effects on chromatin-bound proteins in the estrogen receptor-deficient cell line MDA-MB-231 which is insensitive to phytoestrogen signaling. After exposure to low-dose genistein for >1 month, MDA-MB-231 cells exhibited stable epigenetic alterations that are analyzed via partial MNase digestion and TMT-based quantitative proteomics. 3177 chromatin-bound proteins are identified with high confidence, including 882 molecules that displayed altered binding topology after cell conditioning with genistein. Prolonged phytochemical exposure conferred heritable changes in the binding topology of key epigenetic regulators including ATRX, SUV39H1/H2, and HP1BP3 that are preserved in untreated progeny, resulting in sustained downregulation of proliferation genes and reduced cell growth. These data indicate that soy derivative genistein exerts complex estrogen receptor-independent effects on the epigenome likely to influence tumorigenesis by restricting cell growth.

Durable engraftment of genetically modified FVIII-secreting autologous bone marrow stromal cells in the intramedullary microenvironment.

Genetically modified FVIII-expressing autologous bone marrow-derived mesenchymal stromal cells (BMSCs) could cure haemophilia A. However, culture-expanded BMSCs engraft poorly in extramedullary sites. Here, we compared the intramedullary cavity, skeletal muscle, subcutaneous tissue and systemic circulation as tissue microenvironments that could support durable engraftment of FVIII-secreting BMSC in vivo. A zinc finger nuclease integrated human FVIII transgene into PPP1R12C (intron 1) of culture-expanded primary canine BMSCs. FVIII-secretory capacity of implanted BMSCs in each dog was expressed as an individualized therapy index (number of viable BMSCs implanted × FVIII activity secreted/million BMSCs/24 hours). Plasma samples before and after implantation were assayed for transgenic FVIII protein using an anti-human FVIII antibody having negligible cross-reactivity with canine FVIII. Plasma transgenic FVIII persisted for at least 48 weeks after implantation in the intramedullary cavity. Transgenic FVIII protein levels were low after intramuscular implantation and undetectable after both intravenous infusion and subcutaneous implantation. All plasma samples were negative for anti-human FVIII antibodies. Plasma concentrations and durability of transgenic FVIII secretion showed no correlation with the therapy index. Thus, the implantation site microenvironment is crucial. The intramedullary microenvironment, but not extramedullary tissues, supported durable engraftment of genetically modified autologous FVIII-secreting BMSCs.

Unique Triphenylphosphonium Derivatives for Enhanced Mitochondrial Uptake and Photodynamic Therapy.

In this study, unique methyl-functionalized derivatives (T*PP+) of the drug carrier triphenylphosphonium (TPP+) that exhibit significant enhancement of the accumulation of both the cation and its conjugated cargo in cell mitochondria are designed. We show that the presence of methyl group(s) at key positions within the phenyl ring results in an increase in the hydrophobicity and solvent accessible surface area of T*PP+. In particular, when the para position of the phenyl ring in T*PP+ is functionalized with a methyl group, the cation is most exposed to the surrounding environment, leading to a large decrease in water entropy and an increase in the level of van der Waals interaction with and partition into a nonpolar solvent. Therefore, stronger binding between the hydrophobic T*PP+ and mitochondrial membrane occurs. This is exemplified in a (hexachloro-fluorescein)-TPP+ conjugate system, where an ∼12 times increase in the rate of mitochondrial uptake and a 2 times increase in photodynamic therapy (PDT) efficacy against HeLa and FU97 cancer cells are achieved when TPP+ is replaced with T*PP+. Importantly, nearly all the FU97 cells treated with the (hexachloro-fluorescein)-T*PP+ conjugate are killed as compared to only half the population of cells in the case of the (hexachloro-fluorescein)-TPP+ conjugate at a similar PDT light dosage. This study thus forms a platform for the healthcare community to explore alternative TPP+ derivatives that can act as optimal drug transporters for enhanced mitochondrially targeted therapies.