Exploring the oncoproteomic response of human prostate cancer to therapeutic radiation using data-independent acquisition (DIA) mass spectrometry

Proteomic changes of botulinum neurotoxin injection on muscle growth in children with spastic cerebral palsy

PURPOSE

The study aims to explore the proteomic profile and specific target proteins associated with muscle growth in response to botulinum neurotoxin A (BoNT-A) treatment, in order to improve spasticity management in children with cerebral palsy (CP).

EXPERIMENTAL DESIGN

A total of 54 participants provided 60 plasma samples for proteomic analysis. Among them, six children were sampled before and after receiving their first BoNT-A injection. In addition, 48 unrelated children were enrolled, among whom one group had never received BoNT-A injections and another group was sampled after their first BoNT-A injection. Differentially expressed proteins were identified using the data-independent acquisition (DIA) mass spectrometry approach. Gene Ontology (GO), protein-protein interaction network, and Kyoto Encyclopedia of Genes and Genome analysis were conducted to explore the function and relationship among differentially expressed proteins. The expression levels of target proteins were verified by quantitative real-time PCR and western blotting.

RESULTS

Analysis identified significant differential expression of 90 proteins across two time points, including 48 upregulated and 42 downregulated proteins. The upregulated thioredoxin, α-actinin-1, and aggrecan, and the downregulated integrin beta-1 may affect the growth of muscles affected by spasticity 3 months after BoNT-A injection. This effect is potentially mediated through the activation or inhibition of PI3K-Akt, focal adhesion, and regulation of actin cytoskeleton signaling pathways.

CONCLUSION AND CLINICAL RELEVANCE

BoNT-A injection could lead to a disruption of protein levels and signaling pathways, a condition subsequently associated with muscle growth. This finding might aid clinicians in optimizing the management of spasticity in children with CP.

Multiplexed quantitative proteomics in prostate cancer biomarker development

Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.

Identification of plasma proteomic signatures associated with the progression of cardia gastric cancer and precancerous lesions

Objective

Considering that there are no effective biomarkers for the screening of cardia gastric cancer (CGC), we developed a noninvasive diagnostic approach, employing data-independent acquisition (DIA) proteomics to identify candidate protein markers.

Methods

Plasma samples were obtained from 40 subjects, 10 each for CGC, cardia high-grade dysplasia (CHGD), cardia low-grade dysplasia (CLGD), and healthy controls. Proteomic profiles were obtained through liquid chromatography-mass spectrometry (LC-MS/MS-based DIA proteomics. Candidate plasma proteins were identified by weighted gene co-expression network analysis (WGCNA) combined with machine learning and further validated by the Human Protein Atlas (HPA) database. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the biomarker panel.

Results

There was a clear distinction in proteomic features among CGC, CHGD, CLGD, and the healthy controls. According to the WGCNA, we found 42 positively associated and 164 inversely associated proteins related to CGC progression and demonstrated several canonical cancer-associated pathways. Combined with the results from random forests, LASSO regression, and immunohistochemical results from the HPA database, we identified three candidate proteins (GSTP1, CSRP1, and LY6G6F) that could together distinguish CLGD (AUC = 0.91), CHGD (AUC = 0.99) and CGC (AUC = 0.98) from healthy controls with excellent accuracy.

Conclusions

The panel of protein biomarkers showed promising diagnostic potential for CGC and precancerous lesions. Further validation and a larger-scale study are warranted to assess its potential clinical applications, suggesting a potential avenue for CGC prevention in the future.

Clinical Proteomics for Solid Organ Tissues

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Clinical applications of mass spectrometry-based proteomics in cancer: where are we?

Tumor tissue processing methodologies in combination with data-independent acquisition mass spectrometry (DIA-MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS-based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA-MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi-omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic. This article is protected by copyright. All rights reserved.

Caffeic acid phenethyl ester protects against doxorubicin-induced cardiotoxicity and increases chemotherapeutic efficacy by regulating the unfolded protein response

Doxorubicin (Dox) is an efficient drug used in breast cancer chemotherapy. However, the clinical application of Dox in cancer treatment is limited due to its cardiotoxicity. Caffeic acid phenethyl ester (CAPE) is a critical bioactive ingredient of honeybee propolis that possesses various beneficial pharmacological properties, such as antioxidant and anticancer activities. Here, we aimed to investigate the protective effect of CAPE on Dox-induced cardiotoxicity and its anti-breast cancer effects. CAPE significantly ameliorated Dox-induced toxicity in H9c2 cells and in a mouse model. Mechanistically, Dox caused endoplasmic reticulum (ER) dysfunction characterized by the activation of the unfolded protein response (UPR) and upregulation of Bax proteins, and CAPE attenuated the Dox-induced UPR in H9c2 cells. In contrast, CAPE significantly enhanced Dox-induced cytotoxicity in human breast cancer cells by upregulating the Dox-induced UPR; it also markedly suppressed tumor growth in 4T1 cancer-bearing BALB/c mice. In conclusion, CAPE could be used as a promising therapy for patients with cancer receiving Dox treatment.

Radiosensitivity-Specific Proteomic and Signaling Pathway Network of Non-Small Cell Lung Cancer (NSCLC)

PURPOSE

An unmet clinical need in non-small cell lung cancer (NSCLC) management is the accurate prediction of radiation response in patients receiving radical radiation therapy. We explored the intrinsic radiosensitivity of NSCLC from the proteomic profiles of NSCLC cell lines and paraffin-embedded human samples.

METHODS AND MATERIALS

To uncover radiosensitivity-specific proteomic and signaling pathways, we performed quantitative proteomics by data-independent acquisition mass spectrometry assay on 29 human NSCLC cell lines and 13 paraffin-embedded human NSCLC samples. We validated closely interacting radioresistant proteins by western blotting, immunofluorescence, real-time quantitative polymerase chain reaction in NSCLC cell lines, and immunohistochemistry in paraffin-embedded human samples. We validated the functions of 3 key hub proteins by lentivirus transfection, clonogenic survival assay, and flow cytometry.

RESULTS

The proteomic profiling of NSCLC showed that the intrinsic radiosensitivity of NSCLC is mainly modulated by signaling pathways of proteoglycans in cancer, focal adhesion, and regulation of the actin cytoskeleton. We identified 71 differentially expressed proteins and validated 8 closely interacting proteins as radioresistant proteins of NSCLC. Moreover, we also validated the functionality of integrin-linked protein kinase, p21-activated kinase 1, and Ras GTPase-activating-like protein IQGAP1 in the radiation response of NSCLC cell lines. Finally, with the NSCLC radiosensitivity-specific proteins, we delineated the atlas network of NSCLC radiosensitivity-related signaling pathways.

CONCLUSIONS

Radiosensitivity-specific proteins could guide individualized radiation therapy in clinical practice by predicting the radiation response of patients with NSCLC. Moreover, the NSCLC radiosensitivity-related signaling pathway atlas could guide further exploration of the underlying mechanism.

The influence of hypoxia on the prostate cancer proteome

Prostate cancer accounts for around 15% of male deaths in Western Europe and is the second leading cause of cancer death in men after lung cancer. Mounting evidence suggests that prostate cancer deposits exist within a hypoxic environment and this contributes to radio-resistance thus hampering one of the major therapies for this cancer. Recent reports have shown that nitric oxide (NO) donating non-steroidal anti-inflammatory drugs (NSAIDs) reduced tumour hypoxia as well as maintaining a radio-sensitising/therapeutic effect on prostate cancer cells. The aim of this study was to evaluate the impact of hypoxia on the proteome of the prostate and to establish whether NO-NSAID treatment reverted the protein profiles back to their normoxic status. To this end an established hormone insensitive prostate cancer cell line, PC-3, was cultured under hypoxic and normoxic conditions before and following exposure to NO-NSAID in combination with selected other common prostate cancer treatment types. The extracted proteins were analysed by ion mobility-assisted data independent acquisition mass spectrometry (MS), combined with multivariate statistical analyses, to measure hypoxia-induced alterations in the proteome of these cells. The analyses demonstrated that under hypoxic conditions there were well-defined, significantly regulated/differentially expressed proteins primarily involved with structural and binding processes including, for example, TUBB4A, CIRP and PLOD1. Additionally, the exposure of hypoxic cells to NSAID and NO-NSAID agents, resulted in some of these proteins being differentially expressed; for example, both PCNA and HNRNPA1L were down-regulated, corresponding with disruption in the nucleocytoplasmic shuttling process.

Proteomic analyses identify major vault protein as a prognostic biomarker for fatal prostate cancer

The demographic shift toward an older population will increase the number of prostate cancer cases. A challenge in the treatment of prostate cancer is to avoid undertreatment of patients at high risk of progression following curative treatment. These men can benefit from early salvage treatment. An explorative cohort consisting of tissue from 16 patients who underwent radical prostatectomy, and were either alive or had died from prostate cancer within 10 years postsurgery, was analyzed by mass spectrometry analysis. Following proteomic and bioinformatic analyses, major vault protein (MVP) was identified as a putative prognostic biomarker. A publicly available tissue proteomics dataset and a retrospective cohort of 368 prostate cancer patients were used for validation. The prognostic value of the MVP was verified by scoring immunohistochemical staining of a tissue microarray. High level of MVP was associated with more than 4-fold higher risk for death from prostate cancer (hazard ratio = 4.41, 95% confidence interval: 1.45–13.38; P = 0.009) in a Cox proportional hazard models, adjusted for Cancer of the Prostate Risk Assessments Post-surgical (CAPRA-S) score and perineural invasion. Decision curve analyses suggested an improved standardized net benefit, ranging from 0.06 to 0.18, of adding MVP onto CAPRA-S score. This observation was confirmed by receiver operator characteristics curve analyses for the CAPRA-S score versus CAPRA-S and MVP score (area under the curve: 0.58 versus 0.73). From these analyses, one can infer that MVP levels in combination with CAPRA-S score might add onto established risk parameters to identify patients with lethal prostate cancer.

ACOX2 is a prognostic marker and impedes the progression of hepatocellular carcinoma via PPARα pathway

Hepatocellular carcinoma (HCC) has been extensively studied as one of the most aggressive tumors worldwide. However, its mortality rate remains high due to ideal diagnosis and treatment strategies. Uncovering novel genes with prognostic significance would shed light on improving the HCC patient's outcome. In our study, we applied data-independent acquisition (DIA) quantitative proteomics to investigate the expression landscape of 24 paired HCC patients. A total of 1029 differentially expressed proteins (DEPs) were screened. Then, we compared DEPs in our cohort with the differentially expressed genes (DEGs) in The Cancer Genome Atlas, and investigated their prognostic significance, and found 183 prognosis-related genes (PRGs). By conducting protein-protein interaction topological analysis, we identified four subnetworks with prognostic significance. Acyl-CoA oxidase 2 (ACOX2) is a novel gene in subnetwork1, encodes a peroxisomal enzyme, and its function in HCC was investigated in vivo and in vitro. The lower expression of ACOX2 was validated by real-time quantitative PCR, immunohistochemistry, and Western blot. Cell Counting Kit-8 assay, wound healing, and transwell migration assay were applied to evaluate the impact of ACOX2 overexpression on the proliferation and migration abilities in two liver cancer cell lines. ACOX2 overexpression, using a subcutaneous xenograft tumor model, indicated a tumor suppressor role in HCC. To uncover the underlying mechanism, gene set enrichment analysis was conducted, and peroxisome proliferator-activated receptor-α (PPARα) was proposed to be a potential target. In conclusion, we demonstrated a PRG ACOX2, and its overexpression reduced the proliferation and metastasis of liver cancer in vitro and in vivo through PPARα pathway.

Proteome analysis of rainbow trout (Oncorhynchus mykiss) liver responses to chronic heat stress using DIA/SWATH

Aquaculture of rainbow trout (Oncorhynchus mykiss) is severely hampered by high temperatures in summer, and understanding the regulatory mechanisms controlling responses to chronic heat stress may assist the development of measures to relieve heat stress. In the present study, biochemical parameters revealed a strong stress response in rainbow trout at 24 °C, including activation of stress defence and immune systems. Liver proteome analysis under heat stress (24 °C) and control (18 °C) conditions using DIA/SWATH identified precursors (90,827), peptides (67,028), proteins (6770) and protein groups (5124), among which 460 differentially abundant proteins (DAPs; q-value < 0.05, fold change >1.5), 201 and 259 were up- and down-regulated, respectively. Many were related to heat shock proteins (HSPs), metabolism and immunity. Gene Ontology (GO) analysis showed that some DAPs induced at high temperature were involved in regulating cell homeostasis, metabolism, adaptive stress and stimulation. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified metabolic pathways, protein processing in endoplasmic reticulum, PPAR signalling, and complement and coagulation cascades. Protein-protein interaction (PPI) network analysis indicated that HSP90b1 and C3 may cooperative to affect cell membrane integrity under heat stress. Our findings assist the development of strategies to relieve heat stress in rainbow trout.

Selective Labeling and Identification of the Tumor Cell Proteome of Pancreatic Cancer In Vivo

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers. Dissecting the tumor cell proteome from that of the non-tumor cells in the PDAC tumor bulk is critical for tumorigenesis studies, biomarker discovery, and development of therapeutics. However, investigating the tumor cell proteome has proven evasive due to the tumor's extremely complex cellular composition. To circumvent this technical barrier, we have combined bioorthogonal noncanonical amino acid tagging (BONCAT) and data-independent acquisition mass spectrometry (DIA-MS) in an orthotopic PDAC model to specifically identify the tumor cell proteome in vivo. Utilizing the tumor cell-specific expression of a mutant tRNA synthetase transgene, this approach provides tumor cells with the exclusive ability to incorporate an azide-bearing methionine analogue into newly synthesized proteins. The azide-tagged tumor cell proteome is subsequently enriched and purified via a bioorthogonal reaction and then identified and quantified using DIA-MS. Applying this workflow to the orthotopic PDAC model, we have identified thousands of proteins expressed by the tumor cells. Furthermore, by comparing the tumor cell and tumor bulk proteomes, we showed that the approach can distinctly differentiate proteins produced by tumor cells from those of non-tumor cells within the tumor microenvironment. Our study, for the first time, reveals the tumor cell proteome of PDAC under physiological conditions, providing broad applications for tumorigenesis, therapeutics, and biomarker studies in various human cancers.

Immune molecular profiling of a multiresistant primary prostate cancer with a neuroendocrine-like phenotype: a case report

Background

Understanding the drivers of recurrence in aggressive prostate cancer requires detailed molecular and genomic understanding in order to aid therapeutic interventions. We provide here a case report of histological, transcriptional, proteomic, immunological, and genomic features in a longitudinal study of multiple biopsies from diagnosis, through treatment, and subsequent recurrence.

Case presentation

Here we present a case study of a male in 70 s with high-grade clinically-localised acinar adenocarcinoma treated with definitive hormone therapy and radiotherapy. The patient progressed rapidly with rising PSA and succumbed without metastasis 52 months after diagnosis. We identified the expression of canonical histological markers of neuroendocrine PC (NEPC) including synaptophysin, neuron-specific enolase and thyroid transcription factor 1, as well as intact AR expression, in the recurrent disease only. The resistant disease was also marked by an extremely low immune infiltrate, extensive genomic chromosomal aberrations, and overactivity in molecular hallmarks of NEPC disease including Aurora kinase and E2F, as well as novel alterations in the cMYB pathway. We also observed that responses to both primary treatments (high dose-rate brachytherapy and androgen deprivation therapies) were consistent with known optimal responses—ruling out treatment inefficacy as a factor in relapse.

Conclusions

These data provide novel insights into a case of locally recurrent aggressive prostate cancer harbouring NEPC pathology, in the absence of detected metastasis.

Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology

Data-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic methodology that generates permanent digital proteome maps offering highly reproducible retrospective analysis of cellular and tissue specimens. The adoption of this technology has ushered a new wave of oncology studies across a wide range of applications including its use in molecular classification, oncogenic pathway analysis, drug and biomarker discovery and unravelling mechanisms of therapy response and resistance. In this review, we provide an overview of the experimental workflows commonly used in DIA-MS, including its current strengths and limitations versus conventional data-dependent acquisition mass spectrometry (DDA-MS). We further summarise a number of key studies to illustrate the power of this technology when applied to different facets of oncology. Finally we offer a perspective of the latest innovations in DIA-MS technology and machine learning-based algorithms necessary for driving the development of high-throughput, in-depth and reproducible proteomic assays that are compatible with clinical diagnostic workflows, which will ultimately enable the delivery of precision cancer medicine to achieve optimal patient outcomes.

High dose-rate brachytherapy of localized prostate cancer converts tumors from cold to hot

BACKGROUND

Prostate cancer (PCa) has a profoundly immunosuppressive microenvironment and is commonly immune excluded with few infiltrative lymphocytes and low levels of immune activation. High-dose radiation has been demonstrated to stimulate the immune system in various human solid tumors. We hypothesized that localized radiation therapy, in the form of high dose-rate brachytherapy (HDRBT), would overcome immune suppression in PCa.

METHODS

To investigate whether HDRBT altered prostate immune context, we analyzed preradiation versus postradiation human tissue from a cohort of 24 patients with localized PCa that received HDRBT as primary treatment (RadBank cohort). We performed Nanostring immune gene expression profiling, digital spatial profiling, and high-throughput immune cell multiplex immunohistochemistry analysis. We also resolved tumor and nontumor zones in spatial and bioinformatic analyses to explore the immunological response.

RESULTS

Nanostring immune profiling revealed numerous immune checkpoint molecules (eg, B7-H3, CTLA4, PDL1, and PDL2) and TGFβ levels were increased in response to HDRBT. We used a published 16-gene tumor inflammation signature (TIS) to divide tumors into distinct immune activation states (high:hot, intermediate and low:cold) and showed that most localized PCa are cold tumors pre-HDRBT. Crucially, HDRBT converted 80% of these 'cold'-phenotype tumors into an 'intermediate' or 'hot' class. We used digital spatial profiling to show these HDRBT-induced changes in prostate TIS scores were derived from the nontumor regions. Furthermore, these changes in TIS were also associated with pervasive changes in immune cell density and spatial relationships-in particular, between T cell subsets and antigen presenting cells. We identified an increased density of CD4+ FOXP3+ T cells, CD68+ macrophages and CD68+ CD11c+ dendritic cells in response to HDRBT. The only subset change specific to tumor zones was PDL1- macrophages. While these immune responses were heterogeneous, HDRBT induced significant changes in immune cell associations, including a gained T cell and HMWCK+ PDL1+ interaction in tumor zones.

CONCLUSION

In conclusion, we showed HDRBT converted "cold" prostate tumors into more immunologically activated "hot" tissues, with accompanying spatially organized immune infiltrates and signaling changes. Understanding and potentially harnessing these changes will have widespread implications for the future treatment of localized PCa, including rational use of combination radio-immunotherapy.

Mining cancer biology through bioinformatic analysis of proteomic data

Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research. Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes. Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Biodosimetric transcriptional and proteomic changes are conserved in irradiated human tissue

Transcriptional dosimetry is an emergent field of radiobiology aimed at developing robust methods for detecting and quantifying absorbed doses using radiation-induced fluctuations in gene expression. A combination of RNA sequencing, array-based and quantitative PCR transcriptomics in cellular, murine and various ex vivo human models has led to a comprehensive description of a fundamental set of genes with demonstrable dosimetric qualities. However, these are yet to be validated in human tissue due to the scarcity of in situ-irradiated source material. This represents a major hurdle to the continued development of transcriptional dosimetry. In this study, we present a novel evaluation of a previously reported set of dosimetric genes in human tissue exposed to a large therapeutic dose of radiation. To do this, we evaluated the quantitative changes of a set of dosimetric transcripts consisting of FDXR, BAX, BCL2, CDKN1A, DDB2, BBC3, GADD45A, GDF15, MDM2, SERPINE1, TNFRSF10B, PLK3, SESN2 and VWCE in guided pre- and post-radiation (2 weeks) prostate cancer biopsies from seven patients. We confirmed the prolonged dose-responsivity of most of these transcripts in in situ-irradiated tissue. BCL2, GDF15, and to some extent TNFRSF10B, were markedly unreliable single markers of radiation exposure. Nevertheless, as a full set, these genes reliably segregated non-irradiated and irradiated tissues and predicted radiation absorption on a patient-specific basis. We also confirmed changes in the translated protein product for a small subset of these dosimeters. This study provides the first confirmatory evidence of an existing dosimetric gene set in less-accessible tissues-ensuring peripheral responses reflect tissue-specific effects. Further work will be required to determine if these changes are conserved in different tissue types, post-radiation times and doses.

Biophysical, Biochemical, and Cell Based Approaches Used to Decipher the Role of Carbonic Anhydrases in Cancer and to Evaluate the Potency of Targeted Inhibitors

Carbonic anhydrases (CAs) are thought to be important for regulating pH in the tumor microenvironment. A few of the CA isoforms are upregulated in cancer cells, with only limited expression in normal cells. For these reasons, there is interest in developing inhibitors that target these tumor-associated CA isoforms, with increased efficacy but limited nonspecific cytotoxicity. Here we present some of the biophysical, biochemical, and cell based techniques and approaches that can be used to evaluate the potency of CA targeted inhibitors and decipher the role of CAs in tumorigenesis, cancer progression, and metastatic processes. These techniques include esterase activity assays, stop flow kinetics, and mass inlet mass spectroscopy (MIMS), all of which measure enzymatic activity of purified protein, in the presence or absence of inhibitors. Also discussed is the application of X-ray crystallography and Cryo-EM as well as other structure-based techniques and thermal shift assays to the studies of CA structure and function. Further, large-scale genomic and proteomic analytical methods, as well as cell based techniques like those that measure cell growth, apoptosis, clonogenicity, and cell migration and invasion, are discussed. We conclude by reviewing approaches that test the metastatic potential of CAs and how the aforementioned techniques have contributed to the field of CA cancer research.