Proteomic analysis of effects by x-rays and heavy ion in HeLa cells

Enhanced Glycolysis Confers Resistance Against Photon but Not Carbon Ion Irradiation in Human Glioma Cell Lines

Purpose

Metabolic reprogramming is a key hallmark in various malignancies and poses a challenge in achieving success with various therapies. Enhanced glycolysis is known to confer resistance against photon irradiation while the tumor response to carbon ion irradiation (CII) has not been investigated. This study aimed to investigate the effects of enhanced glycolysis on the response of human glioma cell lines to CII compared to the response to X-rays.

Material and Methods

Glycolysis was stimulated using Dinitrophenol (DNP), a mild OXPHOS inhibitor, in three human glioma cell lines (U251, U87, and LN229) and assessed by monitoring glucose uptake and utilization as well as expression of regulators of glycolysis (glucose transporter protein type 1(Glut1), hexokinase-II (HKII), and Pyruvate Kinase-2 (PKM2). Radiation (X-rays and CII) induced loss of clonogenic survival growth inhibition and perturbations in cell cycle progression (G₂+M block), cytogenetic damage (micronuclei formation), apoptosis, necrosis (reflecting interphase death), and cell migration (Scratch assay) were investigated as parameters of radiation response.

Results

DNP (1 mM) enhanced the expression levels of GLUT1, HKII, and PKM2 by 30-60% and glucose uptake as well as usage by nearly 3 folds in U251 cells suggesting the stimulation of glycolysis. Enhanced glycolysis attenuated the loss of clonogenic survival with D₁₀ doses increasing by 20% to 65% in these cell lines, while no significant changes were noted following CII. Concomitantly, dose-dependent growth inhibition, and cytogenetic damage as well as apoptosis and necrosis induced by X-rays were also reduced by elevated glycolysis in U251 and LN229 cells by 20-50%. However, stimulation of glycolysis enhanced the X-ray-induced cell migration, while it had negligible effect on migration following CII.

Conclusion

Our results suggest that enhanced glycolysis confers resistance against X-ray-induced cell death and migration, while it may not significantly alter the cellular responses to carbon ion irradiation.

Identification of the key genes and pathways involved in the tumorigenesis and prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common renal cell carcinoma (RCC). However, patients with KIRC usually have poor prognosis due to limited biomarkers for early detection and prognosis prediction. In this study, we analysed key genes and pathways involved in KIRC from an array dataset including 26 tumour and 26 adjacent normal tissue samples. Weighted gene co-expression network analysis (WGCNA) was performed with the WGCNA package, and 20 modules were characterized as having the highest correlation with KIRC. The upregulated genes in the tumour samples are involved in the innate immune response, whereas the downregulated genes contribute to the cellular catabolism of glucose, amino acids and fatty acids. Furthermore, the key genes were evaluated through a protein-protein interaction (PPI) network combined with a co-expression network. The comparatively lower expression of AGXT, PTGER3 and SLC12A3 in tumours correlates with worse prognosis in KIRC patients, while higher expression of ALOX5 predicts reduced survival. Our integrated analysis illustrated the hub genes involved in KIRC tumorigenesis, shedding light on the development of prognostic markers. Further understanding of the function of the identified KIRC hub genes could provide deep insights into the molecular mechanisms of KIRC.

Quantitative proteomics reveals mitochondrial respiratory chain as a dominant target for carbon ion radiation: Delayed reactive oxygen species generation caused DNA damage

Heavy ion radiotherapy has shown great promise for cancer therapy. Understanding the cellular response mechanism to heavy ion radiation is required to explore measures of overcoming devastating side effects. Here, we performed a quantitative proteomic analysis to investigate the mechanism of carbon ion irradiation on human AHH-1 lymphoblastoid cells. We identified 4602 proteins and quantified 4569 proteins showing high coverage in the mitochondria. Data are available via ProteomeXchange with identifier PXD008351. After stringent filtering, 290 proteins were found to be significantly up-regulated and 16 proteins were down-regulated. Functional analysis revealed that these up-regulated proteins were enriched in the process of DNA damage repair, mitochondrial ribosome, and particularly mitochondrial respiratory chain, accounting for approximately 50% of the accumulated proteins. Bioinformatics and functional analysis demonstrated that these up-regulated mitochondrial respiratory chain proteins enhanced ATP production and simultaneously reactive oxygen species release. More importantly, increased reactive oxygen species led to secondary organelle injury and lagged DNA double-strand breaks. Consistently, the expression of antioxidant enzymes was up-regulated for free radical scavenging. The mechanism of lagged secondary injury originated from disturbances in the mitochondrial respiratory chain. Our results provided a novel target for cell self-repair against heavy ion radiation-induced cellular damage.

Clair DK, Kyprianou N. Profiles of Radioresistance Mechanisms in Prostate Cancer

Radiation therapy (RT) is commonly used for the treatment of localized prostate cancer (PCa). However, cancer cells often develop resistance to radiation through unknown mechanisms and pose an intractable challenge. Radiation resistance is highly unpredictable, rendering the treatment less effective in many patients and frequently causing metastasis and cancer recurrence. Understanding the molecular events that cause radioresistance in PCa will enable us to develop adjuvant treatments for enhancing the efficacy of RT. Radioresistant PCa depends on the elevated DNA repair system and the intracellular levels of reactive oxygen species (ROS) to proliferate, self-renew, and scavenge anti-cancer regimens, whereas the elevated heat shock protein 90 (HSP90) and the epithelial-mesenchymal transition (EMT) enable radioresistant PCa cells to metastasize after exposure to radiation. The up-regulation of the DNA repairing system, ROS, HSP90, and EMT effectors has been studied extensively, but not targeted by adjuvant therapy of radioresistant PCa. Here, we emphasize the effects of ionizing radiation and the mechanisms driving the emergence of radioresistant PCa. We also address the markers of radioresistance, the gene signatures for the predictive response to radiotherapy, and novel therapeutic platforms for targeting radioresistant PCa. This review provides significant insights into enhancing the current knowledge and the understanding toward optimization of these markers for the treatment of radioresistant PCa.

Cancer stem cells and signaling pathways in radioresistance

Radiation therapy (RT) is one of the most important strategies in cancer treatment. Radioresistance (the failure to RT) results in locoregional recurrence and metastasis. Therefore, it is critically important to investigate the mechanisms leading to cancer radioresistance to overcome this problem and increase patients' survival. Currently, the majority of the radioresistance-associated researches have focused on preclinical studies. Although the exact mechanisms of cancer radioresistance have not been fully uncovered, accumulating evidence supports that cancer stem cells (CSCs) and different signaling pathways play important roles in regulating radiation response and radioresistance. Therefore, targeting CSCs or signaling pathway proteins may hold promise for developing novel combination modalities and overcoming radioresistance. The present review focuses on the key evidence of CSC markers and several important signaling pathways in cancer radioresistance and explores innovative approaches for future radiation treatment.

Identification of protein biomarkers and signaling pathways associated with prostate cancer radioresistance using label-free LC-MS/MS proteomic approach

Identifying biomarkers and signaling pathways are important for the management of prostate cancer (CaP) radioresistance. In this study, we identified differential proteins and signaling pathways from parental CaP cell lines and CaP radioresistant (RR) sublines using a label-free LC-MS/MS proteomics approach. A total of 309 signaling pathway proteins were identified to be significantly altered between CaP and CaP-RR cells (p ≤ 0.05, fold differences >1.5, ≥80% power). Among these proteins, nineteen are common among three paired CaP cell lines and associated with metastasis, progression and radioresistance. The PI3K/Akt, VEGF and glucose metabolism pathways were identified as the main pathways associated with CaP radioresistance. In addition, the identified potential protein markers were further validated in CaP-RR cell lines and subcutaneous (s.c) animal xenografts by western blotting and immunohistochemistry, respectively and protein aldolase A (ALDOA) was selected for a radiosensitivity study. We found the depletion of ALDOA combined with radiotherapy effectively reduced colony formation, induced more apoptosis and increased radiosensitivity in CaP-RR cells. Our findings indicate that CaP radioresistance is caused by multifactorial traits and downregulation of ALDOA increases radiosensitivity in CaP-RR cells, suggesting that controlling these identified proteins or signaling pathways in combination with radiotherapy may hold promise to overcome CaP radioresistance.

Weighted gene co-expression network analysis in identification of metastasis-related genes of lung squamous cell carcinoma based on the Cancer Genome Atlas database

BACKGROUND

Lung squamous cell carcinoma (lung SCC) is a common type of malignancy. Its pathogenesis mechanism of tumor development is unclear. The aim of this study was to identify key genes for diagnosis biomarkers in lung SCC metastasis.

METHODS

We searched and downloaded mRNA expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify differences in mRNA expression of primary tumor tissues from lung SCC with and without metastasis. Gene co-expression network analysis, protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and quantitative real-time polymerase chain reactions (qRT-PCR) were used to explore the biological functions of the identified dysregulated genes.

RESULTS

Four hundred and eighty-two differentially expressed genes (DEGs) were identified between lung SCC with and without metastasis. Nineteen modules were identified in lung SCC through weighted gene co-expression network analysis (WGCNA). Twenty-three DEGs and 26 DEGs were significantly enriched in the respective pink and black module. KEGG pathway analysis displayed that 26 DEGs in the black module were significantly enriched in bile secretion pathway. Forty-nine DEGs in the two gene co-expression module were used to construct PPI network. CFTR in the black module was the hub protein, had the connectivity with 182 genes. The results of qRT-PCR displayed that FIGF, SFTPD, DYNLRB2 were significantly down-regulated in the tumor samples of lung SCC with metastasis and CFTR, SCGB3A2, SSTR1, SCTR, ROPN1L had the down-regulation tendency in lung SCC with metastasis compared to lung SCC without metastasis.

CONCLUSIONS

The dysregulated genes including CFTR, SCTR and FIGF might be involved in the pathology of lung SCC metastasis and could be used as potential diagnosis biomarkers or therapeutic targets for lung SCC.

Proteomic Analysis Implicates Dominant Alterations of RNA Metabolism and the Proteasome Pathway in the Cellular Response to Carbon-Ion Irradiation

Radiotherapy with heavy ions is considered advantageous compared to irradiation with photons due to the characteristics of the Braggs peak and the high linear energy transfer (LET) value. To understand the mechanisms of cellular responses to different LET values and dosages of heavy ion radiation, we analyzed the proteomic profiles of mouse embryo fibroblast MEF cells exposed to two doses from different LET values of heavy ion ¹²C. Total proteins were extracted from these cells and examined by Q Exactive with Liquid Chromatography (LC)—Electrospray Ionization (ESI) Tandem MS (MS/MS). Using bioinformatics approaches, differentially expressed proteins with 1.5 or 2.0-fold changes between different dosages of exposure were compared. With the higher the dosage and/or LET of ion irradiation, the worse response the cells were in terms of protein expression. For instance, compared to the control (0 Gy), 771 (20.2%) proteins in cells irradiated at 0.2 Gy of carbon-ion radiation with 12.6 keV/μm, 313 proteins (8.2%) in cells irradiated at 2 Gy of carbon-ion radiation with 12.6 keV/μm, and 243 proteins (6.4%) in cells irradiated at 2 Gy of carbon-ion radiation with 31.5 keV/μm exhibited changes of 1.5-fold or greater. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Munich Information Center for Protein Sequences (MIPS) analysis, and BioCarta analysis all indicated that RNA metabolic processes (RNA splicing, destabilization and deadenylation) and proteasome pathways may play key roles in the cellular response to heavy-ion irradiation. Proteasome pathways ranked highest among all biological processes associated with heavy carbon-ion irradiation. In addition, network analysis revealed that cellular pathways involving proteins such as Col1a1 and Fn1 continued to respond to high dosages of heavy-ion irradiation, suggesting that these pathways still protect cells against damage. However, pathways such as those involving Ikbkg1 responded better at lower dosages than at higher dosages, implying that cell damage would occur when the networks involving these proteins stop responding. Our investigation provides valuable proteomic information for elucidating the mechanism of biological effects induced by carbon ions in general.

Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis

AIM

To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.

METHODS

Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus (GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes. The function of the genes were annotated by gene ontology (GO).

RESULTS

In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location (sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter (LTD). Additionally, we identified the hug gene (top connectivity with other genes) in each module. The hub gene RPS15A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.

CONCLUSION

From WGCNA analysis and hub gene calculation, we identified RPS15A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.

Broader implications of SILAC-based proteomics for dissecting signaling dynamics in cancer

Large-scale transcriptome and epigenome analyses have been widely utilized to discover gene alterations implicated in cancer development at the genetic level. However, mapping of signaling dynamics at the protein level is likely to be more insightful and needed to complement massive genomic data. Stable isotope labeling with amino acids in cell culture (SILAC)-based proteomic analysis represents one of the most promising comparative quantitative methods that has been extensively employed in proteomic research. This technology allows for global, robust and confident identification and quantification of signal perturbations important for the progress of human diseases, particularly malignancies. The present review summarizes the latest applications of in vitro and in vivo SILAC-based proteomics in identifying global proteome/phosphoproteome and genome-wide protein-protein interactions that contribute to oncogenesis, highlighting the recent advances in dissecting signaling dynamics in cancer.