Protein signatures for classification and prognosis of gastric cancer a signaling pathway-based approach

Novel Biomaterials Based Strategies for Neurodegeneration: Recent Advancements and Future Prospects

Neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and Huntington's disease, pose significant challenges for effective treatment due to the complex nature of the central nervous system and the limited delivery of therapeutic agents to the brain. Biomaterial-based drug delivery systems offer promising strategies to overcome these challenges and improve therapeutic outcomes. These systems utilize various biomaterials, such as nanoparticles, hydrogels, and implants, to deliver drugs, genes, or cells to the affected regions of the brain. They provide advantages such as targeted delivery, controlled release, and protection of therapeutic agents. This review examines the role of biomaterials in drug delivery for neurodegeneration, discussing different biomaterialbased approaches, including surface modification, encapsulation, and functionalization techniques. Furthermore, it explores the challenges, future perspectives, and potential impact of biomaterialbased drug delivery systems in the field of neurodegenerative diseases.

Alterations of Signaling Pathways in Essential Thrombocythemia with Calreticulin Mutation

Purpose

Though mutations of the calreticulin (CALR) gene have been identified in essential thrombocythemia patients, the detailed mechanisms for CALR mutations have not been completely clarified. Our study is aimed at characterizing alteration of protein expression in ET patients with mutated CALR^del52 and further recognizing possible involvement of signaling pathways associated with CALR mutations.

Patients and Methods

Protein pathway array was performed to analyze the expression levels of proteins involved in various signaling pathways in peripheral blood neutrophils from 18 ET patients with mutated CALR^del52, 20 ET patients with JAK2^V617F mutation and 20 controls.

Results

We found 20 proteins differentially expressed in ET patients with mutated CALR^del52 compared with healthy controls. These proteins were associated with molecular mechanisms of cancer in ingenuity pathways analysis (IPA) network. We identified top ten canonical pathways which including apoptotic pathways and cellular cytokine pathways might participate in pathogenesis of ET with mutated CALR^del52. Additionally, there were 8 proteins found to be dysregulated differently between ET patients with mutated CALR^del52 and those with JAK2^V617F mutation. These proteins might be related to the unique signaling pathways activated by CALR^del52 mutation which were different to JAK/STATs pathway by JAK2^V617F mutation.

Conclusion

Our study demonstrated that numerous alterations of signaling proteins and pathways in ET patients with mutated CALR^del52. These findings could help to gain insights into the pathological mechanisms of ET.

Lidocaine alleviates cisplatin resistance and inhibits migration of MGC-803/DDP cells through decreasing miR-10b

Although chemotherapy is one of the effective means of treating gastric cancer, the resistance of chemotherapeutic drugs has followed. And the mechanisms of resistance are not completely clear. The main aim of this article was to develop a kind of drug that could reduce the resistance of cisplatin on gastric cancer cells. The MGC-803 and MGC-803/DDP cells were treated by cisplatin for 48 h and Lidocaine (Lido) for 24 h. Cell viability, apoptosis, migration and invasion were tested by cell counting kit-8 (CCK-8) assay, apoptosis assay, western blot, migration and invasion assay. After MGC-803/DDP cells were transfected for 48 h, the expression of microRNA-10b (miR-10b) were detected by quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR). Activation of AKT/mTOR and β-catenin pathways was tested by western blot. Cisplatin caused MGC-803 and MGC-803/DDP cell apoptosis, and MGC-803/DDP cells possessed higher cisplatin resistance than MGC-803 cells. Lido reduced the cisplatin resistance of MGC-803/DDP cells. Besides, Lido inhibited MGC-803/DDP cell migration and invasion. In addition, Lido declined cisplatin resistance by down-regulating miR-10b. Lido also repressed AKT/mTOR and β-catenin pathway by down-regulating miR-10b. This article explained the role of Lido in cisplatin resistance in MGC-803/DDP cells. Furthermore, Lido weakened the cisplatin resistance in MGC-803/DDP cells at least in part through decreasing the expression of miR-10b.

Profiling of serum metabolites in advanced colon cancer using liquid chromatography-mass spectrometry

Lymph node metastasis remains a key factor that affects the prognosis of patients with colon cancer. The aim of the present study was to identify and evaluate serum metabolites as biomarkers for the detection of tumor lymph node metastasis and the prediction of patient survival. The present study analyzed the metabolites in the serum of patients with advanced colon cancer both with and without lymph node metastasis. Blood samples from 104 patients with stage T3 colon cancer were collected and analyzed using liquid chromatography-mass spectrometry. The metabolites were structurally confirmed with data from the Human Metabolome Database. The association between the serum metabolites and the clinicopathological characteristics and survival time of patients from the present study was analyzed. Overall, 227 different metabolites were identified in the serum of patients with stage T3 colon cancer with or without lymph node metastasis. Furthermore, 17 of these metabolites may potentially distinguish those patients with lymph node metastasis from those patients without. In addition, five factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum, age and sex, were identified as independent predictors for lymph node metastasis (P<0.05). Furthermore, three factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum were independent predictors for patient survival (P<0.05). In conclusion, the serum levels of abscisic acid, calcitroic-acid and glucosylsphingosine may be considered as potential biomarkers to predict the occurrence of lymph node metastasis and the survival time of patients with colon cancer.

Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival

BACKGROUND

Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses.

METHODS

Tissue microarrays were used to measure expression of nine GC-associated proteins in GC tissue and normal gastric tissue samples. Hierarchical cluster analysis of microarray data and feature selection for factors associated with survival were performed. Based on these data, prognostic scoring models were established to predict clinical outcomes. Finally, ingenuity pathway analysis (IPA) was used to identify a biological GC network.

RESULTS

Eight proteins were upregulated in GC tissues versus normal gastric tissues. Hierarchical cluster analysis and feature selection showed that overall survival was worse in cyclin dependent kinase (CDK)2, Akt1, X-linked inhibitor of apoptosis protein (XIAP), Notch4, and phosphorylated (p)-protein kinase C (PKC) α/β2 immunopositive patients than in patients that were immunonegative for these proteins. Risk score models based on these five proteins and clinicopathological characteristics were established to determine prognoses of GC patients. These proteins were found to be involved in cancer related-signaling pathways and upstream regulators were identified.

CONCLUSION

This study identified proteins that can be used as clinical biomarkers and established a risk score model based on these proteins and clinicopathological characteristics to assess GC prognosis.

Serum metabolomic profiling of human gastric cancer and its relationship with the prognosis

Objective

This study was aimed to investigate serum metabolites in gastric cancer (GC) patients and their relationships with the prognosis of GC in order to find potential specific serum biomarkers for GC.

Methods

Blood samples of 125 GC patients of unifocal GC at initial stage and 38 healthy people recruited in our hospital from September 2008 to August 2009 were analyzed by using high performance liquid chromatography coupled with electrospray ionization/quadrupole-time-of-flight mass spectrometry (HPLCESI/Q-TOFMS). Multiple statistical methods like principal component analysis (PCA), hierarchical clustering analysis, partial least squares discriminant analysis (PLS-DA), multivariate COX regression analysis, variance analysis and K-M survival curve were applied to analyze the raw obtained mass data in order to analyze the independent prognostic factors of GC. The structures of these metabolites were confirmed by comparing the m/z ratio and ion mode of with the data published from HMDB (www.hmdb.ca) databases.

Results

By PLS-DA test, 16 serum metabolites in ESI⁺ mode of VIP>1 in both test group and validation group could definitely distinguish GC patients from healthy peoples (p<0.05). Multivariate COX regression analysis showed TNM staging, 2,4-hexadienoic acid, 4-methylphenyl dodecanoate and glycerol tributanoate were independent prognostic factors of GC (p<0.05). In the K-M survival analysis, the survival rate in high level group of the 3 selected serum metabolites together or alone was significant lower than in those in low level group (p<0.05).

Conclusion

Low serum levels of 2,4-hexadienoic acid, 4-methylphenyl dodecanoate and glycerol tributanoate may be important independent prognostic factors of GC.

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

INTRODUCTION

Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification. Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references. Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.

Protein Profiling of Bladder Urothelial Cell Carcinoma

This study aimed to detect protein changes that can assist to understand the underlying biology of bladder cancer. The data showed forty five proteins were found to be differentially expressed comparing tumors vs non-tumor tissues, of which EGFR and cdc2p34 were correlated with muscle invasion and histological grade. Ten proteins (ß-catenin, HSP70, autotaxin, Notch4, PSTPIP1, DPYD, ODC, cyclinB1, calretinin and EPO) were able to classify muscle invasive BCa (MIBC) into 2 distinct groups, with group 2 associated with poorer survival. Finally, 3 proteins (P2X7, cdc25B and TFIIH p89) were independent factors for favorable overall survival.

Protein profiling of alpha-fetoprotein producing gastric adenocarcinoma

Alpha-fetoprotein (AFP) producing gastric adenocarcinoma is considered as a rare subtype of gastric adenocarcinoma. Compared with AFP non-producing gastric adenocarcinoma, our study and other previous studies showed that AFP producing gastric adenocarcinoma is more aggressive and prone to liver metastasis. Using the Protein Pathway Array, 11 of out of 286 proteins tested were found to be differentially expressed between AFP producing (n=32) and AFP non-producing (n=45) gastric adenocarcinoma tissues. In addition, the high level expression of XIAP and IGF-Irβ in gastric adenocarcinoma tissues was independent factors for poor prognosis in AFP producing gastric adenocarcinoma patients. A risk model based on the XIAP and IGF-Irβ expression levels can separate AFP producing gastric adenocarcinoma patients into 2 subgroups and each subgroup had a distinct set of signaling pathways involved. In conclusion, AFP producing gastric adenocarcinoma is a heterogeneous cancer with different clinical outcomes, biological behaviors and underlying molecular alterations.

Serum biomarker panels for diagnosis of gastric cancer

Purpose

Currently, serum biomarkers that are sufficiently sensitive and specific for early detection and risk classification of gastric adenocarcinomas are not known. In this study, ten serum markers were assessed using the Luminex system and enzyme-linked immunosorbent assay for the diagnosis of gastric cancer and analysis of the relation between prognosis and metastases.

Patients and methods

A training set consisting of 228 gastric adenocarcinoma and 190 control samples was examined. A Luminex multiplex panel with nine biomarkers, consisting of three proteins discovered through our previous studies and six proteins previously reported to be cancer-associated, was constructed. One additional biomarker was detected using a commercial kit containing EDTA. Logistic regression, random forest (RF), and support vector machine (SVM) were used to identify the panel of discriminatory biomarkers in the training set. After selecting five proteins as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations. These algorithms were independently validated using a set of 57 gastric adenocarcinoma and 48 control samples.

Results

Serum pepsinogen I, serum pepsinogen II, A Disintegrin And Metalloproteinase domain-containing protein 8 (ADAM8), vascular endothelial growth factor (VEGF), and serum IgG to Helicobacter pylori were selected as classifiers in the three algorithms. These algorithms differentiated between the majority of gastric adenocarcinoma and control serum samples in the training/test set with high accuracy (RF 79.0%, SVM 83.8%, logistic regression 76.2%). These algorithms also differentiated the samples in the validation set (accuracy: RF 82.5%, SVM 86.1%, logistic regression 78.7%).

Conclusion

A panel of combinatorial biomarkers comprising VEGF, ADAM8, IgG to H. pylori, serum pepsinogen I, and pepsinogen II were developed. The use of biomarkers is a less invasive method for the diagnosis of gastric adenocarcinoma. They may supplement clinical gastroscopic evaluation of symptomatic gastric cancer patients and enhance the diagnostic accuracy.

Progress in the development of protein biomarkers of oesophageal and gastric cancers

Upper gastrointestinal cancers originating in the oesophagus and stomach often present late and have a very poor prognosis. Treatment options include surgery for localised disease but, increasingly, neoadjuvant chemotherapy and radiotherapy are being employed to improve outcome. There is often a variable response to neoadjuvant treatment between individual patients and side effects are relatively common. There is an urgent need for novel biomarkers of upper gastrointestinal cancer, not only to improve screening and early diagnosis of the oesophageal and gastric cancers when treatment options are potentially more effective, but also to accurately guide therapy in more advanced disease. The development of predictive biomarkers will also help to more effectively identify those patients that will benefit from targeted therapies. Although many promising results have been derived from these studies there remains a lack of validated clinically applicable biomarkers available for translation into routine clinical use. This review will provide an overview of the recent proteomic research on upper gastrointestinal cancer protein biomarker identification and validation. The challenges faced in the development of validated, clinically acceptable and accurate protein biomarkers will also be discussed, along with possible areas of future progress.

Protein profiling of preeclampsia placental tissues

Preeclampsia is a multi-system disorder involved in pregnancy without an effective treatment except delivery. The precise pathogenesis of this complicated disorder is still not completely understood. The objective of this study is to evaluate the alterations of protein expression and phosphorylations that are important in regulating placental cell function in preterm and term preeclampsia. Using the Protein Pathway Array, 38 proteins in placental tissues were found to be differentially expressed between preterm preeclampsia and gestational age matched control, while 25 proteins were found to be expressed differentially between term preeclampsia and matched controls. Among these proteins, 16 proteins and their associated signaling pathways overlapped between preterm and term preeclampsia, suggesting the common pathogenesis of two subsets of disease. On the other hand, many proteins are uniquely altered in either preterm or term preeclampsia and correlated with severity of clinical symptoms and outcomes, therefore, providing molecular basis for these two subsets of preeclampsia. Furthermore, the expression levels of some of these proteins correlated with neonatal small for gestational age (PAI-1 and PAPP-A) and adverse outcomes (Flt-1) in women with preterm preeclampsia. These proteins could potentially be used as candidate biomarkers for predicting outcomes of preeclampsia.

Protein signature for non-small cell lung cancer prognosis

BACKGROUND

Current histopathological classification and TNM staging have limited accuracy in predicting survival and stratifying patients for appropriate treatment. The goal of the study is to determine whether the expression pattern of functionally important regulatory proteins can add additional values for more accurate classification and prognostication of non-small lung cancer (NSCLC).

METHODS

The expression of 108 proteins and phosphoproteins in 30 paired NSCLC samples were assessed using Protein Pathway Array (PPA). The differentially expressed proteins were further confirmed using a tissue microarray (TMA) containing 94 NSCLC samples and were correlated with clinical data and survival.

RESULTS

Twelve of 108 proteins (p-CREB(Ser133), p-ERK1/2(Thr202/Tyr204), Cyclin B1, p-PDK1(Ser241), CDK4, CDK2, HSP90, CDC2p34, β-catenin, EGFR, XIAP and PCNA) were selected to build the predictor to classify normal and tumor samples with 97% accuracy. Five proteins (CDC2p34, HSP90, XIAP, CDK4 and CREB) were confirmed to be differentially expressed between NSCLC (n=94) and benign lung tumor (n=19). Over-expression of CDK4 and HSP90 in tumors correlated with a favorable overall survival in all NSCLC patients and the over-expression of p-CREB(Ser133) and CREB in NSCLC correlated with a favorable survival in smokers and those with squamous cell carcinoma, respectively. Finally, the four proteins (CDK4, HSP90, p-CREB and CREB) were used to calculate the risk score of each individual patient with NSCLC to predict survival.

CONCLUSION

In summary, our data demonstrated a broad disturbance of functionally important regulatory proteins in NSCLC and some of these can be selected as clinically useful biomarkers for diagnosis, classification and prognosis.

Pathway-based analysis of breast cancer

INTRODUCTION

Although HER2 and ER pathways are predominant pathways altered in breast cancer, it is now well accepted that many other signaling pathways are also involved in the pathogenesis of breast cancer. The understanding of these additional pathways may assist in identifying new therapeutic approaches for breast cancer.

METHODS

13 invasive ductal carcinoma tissues and 5 benign breast tissues were analyzed for the mRNA expression level of 1243 cancer pathway-related genes using SmartChip (WaferGen, CA), a real-time PCR-base method. In addition, the levels of 131 cancer pathway-related proteins and phosphoproteins in 33 paired breast cancers were measured using our innovative Protein Pathway Array.

RESULTS

Out of 1,243 mRNAs, 68.7% (854) were detected in breast cancer and 395 mRNAs were statistically significant (fold change >2) between benign and cancer tissues. Of these mRNAs, 105 only expressed in breast cancer tissues and 33 mRNAs only expressed in normal breast tissues. Out of 131 proteins and phosphoproteins, 68% (89) were detected in cancer tissues and 57 proteins were significantly differentiated between tumor and normal tissues. Interestingly, only 3 genes (CDK6, Vimentin and SLUG) showed decreases in both protein and mRNA. Six proteins (BCL6, CCNE1, PCNA, PDK1, SRC and XIAP) were differentially expressed between tumor and normal tissues but no differences were observed at mRNA levels. Analyses of mRNA and protein data using Ingenuity Pathway Analysis showed more than 15 pathways were altered in breast cancer and 6 of which were shared between mRNAs and proteins, including p53, IL17, HGF, NGF, PTEN and PI3K/AKT pathways.

CONCLUSIONS

There is a broad dysregulation of various pathways in breast cancer both at protein levels and mRNA levels. It is important to note that mRNA expression does not correlate with protein level, suggesting different regulation mechanisms between proteins and mRNAs.

Protein marker profiling in different T classification in laryngeal squamous cell carcinoma

BACKGROUND

The identification of specific biomarkers related to laryngeal squamous cell carcinoma (SCC) will be helpful in early detection and determination of reasonable treatment options, which are crucial for the prognosis of patients with laryngeal SCC. The purpose of this study was to profile the protein markers that can be used for diagnosis and prognosis of laryngeal SCC and to observe laryngeal SCC progression with distinct stages of malignant transformation.

METHODS

Two hundred twenty-five proteins were tested in 84 pairs of tumors and adjacent nontumor mucosa samples using protein pathway arrays (PPAs). Ingenuity pathway analysis (IPA) enrichment analysis was performed and protein expression profiles in different T classification were mapped by grid analysis of time-series expression (GATE).

RESULTS

Among 16 proteins differently expressed between tumors and normal tissues, we selected 9 proteins (TTF-1, CDK2, Eg5, proliferating cell nuclear antigen [PCNA], Bcl-xL, 14-3-3β, p27, SRC-1, cytokeratin 18) as markers for classification. From the IPA analysis, we observed a more malignant transformation from T3 to T4 at the protein level and described the changing patterns of the proteins' expression in this progression. JAK2, keratin 10, and IL-3Rα were identified as markers for prognosis. The risk model based on histological grade, T classification, N classification, JAK2, and IL-3Rα can predict the prognosis with 85.5% accuracy.

CONCLUSION

This study indicated that dysregulated signaling proteins can be selected as useful biomarkers for tumor classification and predicting the outcome in patients with laryngeal SCC. The changing patterns of the proteins' expression in different stages were related to the more malignant transformation and further studies will focus on the role of these proteins in laryngeal SCC progression.

Helicobacter pylori and gastric cancer

Infection with Helicobacter pylori is established as the major risk factor for gastric cancer development. Damage of the mucosal barrier due to H. pylori-induced inflammation enhances the carcinogenic effect of other risk factors such as salt intake or tobacco smoking. The genetic disposition of both the bacterial strain and the host can increase the potential towards gastric cancer formation. Genetic variance of the bacterial proteins CagA and VacA is associated with a higher gastric cancer risk, as are polymorphisms and epigenetic changes in host gene coding for interleukins (IL1β, IL8), transcription factors (CDX2, RUNX3) and DNA repair enzymes. Application of high-throughput assays for genome-wide assessment of either genetic structural variance or gene expression patterns may lead to a better understanding of the pathobiological background of these processes, including the underlying signaling pathways. Understanding of the stepwise alterations that take place in the transition from chronic atrophic gastritis, via metaplastic changes, to invasive neoplasia is vital to define the 'point of no return' before which eradication of H. pylori has the potential to prevent gastric cancer. Currently, eradication as preventive strategy is only recommended for high-incidence regions in Asia; large population studies with an adequate follow-up are required to demonstrate the effectiveness of such an approach in Western populations.

Reduced expression of AMPK-β1 during tumor progression enhances the oncogenic capacity of advanced ovarian cancer

AMP-activated protein kinase (AMPK) is a key energy sensor that is involved in regulating cell metabolism. Our previous study revealed that the subunits of the heterotimeric AMPK enzyme are diversely expressed during ovarian cancer progression. However, the impact of the variable expression of these AMPK subunits in ovarian cancer oncogenesis remains obscure. Here, we provide evidence to show that reduced expression of the AMPK-β1 subunit during tumor progression is associated with the increased oncogenic capacity of advanced ovarian cancer cells. Immunohistochemical analysis revealed that AMPK-β1 levels were reduced in advanced-stage (P = 0.008), high-grade (P = 0.013) and metastatic ovarian cancers (P = 0.008). Intriguingly, down-regulation of AMPK-β1 was progressively reduced from tumor stages 1 to 3 of ovarian cancer. Functionally, enforced expression of AMPK-β1 inhibited ovarian-cancer-cell proliferation, anchorage-independent cell growth, cell migration and invasion. Conversely, depletion of AMPK-β1 by siRNA enhanced the oncogenic capacities of ovarian cancer cells, suggesting that the loss of AMPK-β1 favors the aggressiveness of ovarian cancer. Mechanistically, enforced expression of AMPK-β1 increased AMPK activity, which, in turn, induced cell-cycle arrest via inhibition of AKT/ERK signaling activity as well as impaired cell migration/invasion through the suppression of JNK signaling in ovarian cancer cells. Taken together, these findings suggest that the reduced expression of AMPK-β1 confers lower AMPK activity, which enhances the oncogenic capacity of advanced-stage ovarian cancer.

Protein profiling of Helicobacter pylori-associated gastric cancer

Helicobacter pylori infection is an initiating factor in the development of gastric cancer. Gastric cancer can be divided into two groups on the basis of H. pylori serological status; seropositive H. pylori status predicts favorable prognosis in patients with gastric cancer. By using the protein pathway array, we identified 20 differentially expressed proteins in primary gastric cancer tissues between the H. pylori-seropositive and H. pylori-seronegative groups. Our results indicate that both brassinosteroid insensitive 1-associated kinase 1 and calpastatin are favorable prognostic factors in H. pylori-seropositive gastric cancer patients. In contrast, dachshund homolog 1 is a favorable prognostic factor in H. pylori-seronegative gastric cancer patients. Different signaling pathways were found to be altered between H. pylori-seropositive and H. pylori-seronegative gastric cancer, which may account for the different tumorigenesis and outcomes between these two subsets of patients.

Long chain fatty Acyl-CoA synthetase 4 is a biomarker for and mediator of hormone resistance in human breast cancer

The purpose of this study was to determine the role of long-chain fatty acyl-CoA synthetase 4 (ACSL4) in breast cancer. Public databases were utilized to analyze the relationship between ACSL4 mRNA expression and the presence of steroid hormone and human epidermal growth factor receptor 2 (HER2) in both breast cancer cell lines and tissue samples. In addition, cell lines were utilized to assess the consequences of either increased or decreased levels of ACSL4 expression. Proliferation, migration, anchorage-independent growth and apoptosis were used as biological end points. Effects on mRNA expression and signal transduction pathways were also monitored. A meta-analysis of public gene expression databases indicated that ACSL4 expression is positively correlated with a unique subtype of triple negative breast cancer (TNBC), characterized by the absence of androgen receptor (AR) and therefore referred to as quadruple negative breast cancer (QNBC). Results of experiments in breast cancer cell lines suggest that simultaneous expression of ACSL4 and a receptor is associated with hormone resistance. Forced expression of ACSL4 in ACSL4-negative, estrogen receptor α (ER)-positive MCF-7 cells resulted in increased growth, invasion and anchorage independent growth, as well as a loss of dependence on estrogen that was accompanied by a reduction in the levels of steroid hormone receptors. Sensitivity to tamoxifen, triacsin C and etoposide was also attenuated. Similarly, when HER2-positive, ACSL4-negative, SKBr3 breast cancer cells were induced to express ACSL4, the proliferation rate increased and the apoptotic effect of lapatinib was reduced. The growth stimulatory effect of ACSL4 expression was also observed in vivo in nude mice when MCF-7 control and ACSL4-expressing cells were utilized to induce tumors. Our data strongly suggest that ACSL4 can serve as both a biomarker for, and mediator of, an aggressive breast cancer phenotype.

Genetics/genomics/proteomics of gastric adenocarcinoma

Hereditary diffuse gastric cancer can be caused by epithelial cadherin mutations for which genetic testing is available. Inherited cancer predisposition syndromes including Lynch, Li-Fraumeni, and Peutz-Jeghers syndromes, can be associated with gastric cancer. Chromosomal and microsatellite instability occur in gastric cancers. Several consistent genetic and molecular alterations including chromosomal instability, microsatellite instability, and epigenetic alterations have been identified in gastric cancers. Biomarkers and molecular profiles are being discovered with potential for diagnostic, prognostic, and treatment guidance implications.

Protein predictive signatures for lymph node metastasis of gastric cancer

Lymph node status remains one of most crucial indicators of gastric cancer prognosis and treatment planning. Current imaging methods have limited accuracy in predicting lymph node metastasis. We sought to identify protein markers in primary gastric cancer and to define a risk model to predict lymph node metastasis. The Protein Pathway Array (PPA) (initial selection) and Western blot (confirmation) were used to assess the protein expression in a total of 190 freshly frozen gastric cancer samples. The protein expression levels were compared between samples with lymph node metastasis (n = 73) and those without lymph node metastasis (n = 57) using PPA. There were 27 proteins differentially expressed between lymph node positive samples and lymph node negative samples. Five proteins (Factor XIII B, TFIIH p89, ADAM8, COX-2 and CUL-1) were identified as independent predictors of lymph node metastasis. Together with vascular/lymphatic invasion status, a risk score model was established to determine the risk of lymph node metastasis for each individual gastric cancer patient. The ability of this model to predict lymph node metastasis was further confirmed in a second cohort of gastric cancer patients (33 with and 27 without lymph node metastasis) using Western blot. This study indicated that some proteins differentially expressed in gastric cancer can be selected as clinically useful biomarkers. The risk score model is useful for determining patients' risk of lymph node metastasis and prognosis.

Alterations of signaling pathways in muscle tissues of patients with amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS), a degenerative disorder of the central nervous system, manifests as progressive weakening of muscles. The diagnosis and prognosis of ALS are often unclear, so useful biomarkers are needed.

METHODS

Total proteins were extracted from muscle samples from 36 ALS, 17 spinal muscular atrophy (SMA), and 36 normal individuals. The expression levels of 134 proteins and phosphoproteins were assessed using protein pathway array analysis.

RESULTS

Seventeen proteins were differentially expressed between ALS and normal muscle, and 9 proteins were differentially expressed between ALS and SMA muscle. The low-level expression of Akt and Factor XIIIB correlates with unfavorable survival, and the risk score calculated based on these proteins predicts the survival of each individual patient.

CONCLUSIONS

Some proteins could be selected as clinically useful biomarkers. Specifically, Akt and Factor XIIIB were found to be promising biomarkers for estimating prognosis in ALS.

Regulation of a novel androgen receptor target gene, the cyclin B1 gene, through androgen-dependent E2F family member switching

The malignant transformation of human prostatic epithelium is associated with the loss of androgen receptor (AR) in the surrounding stroma. However, the function and mechanisms of AR signaling in prostate cancer (PCa) stroma remain elusive. Here we report, by using proteomics pathway array analysis (PPAA), that androgen and its receptor inhibit the proliferation of prostate stromal cells through transcriptional suppression of cyclin B1, and we confirmed our findings at mRNA and protein levels using AR-negative or -positive primary prostate stromal cells. Furthermore, AR showed a negative correlation with cyclin B1 expression in stroma of human PCa samples in vivo. Mechanistically, we identify cyclin B1 as a bona fide AR target gene in prostate stromal cells. The negative regulation of cyclin B1 by AR is mediated through switching between E2F1 and E2F4 on the promoter of cyclin B1. E2F1 binds to the cyclin B1 promoter and maintains its expression and subsequent cell cycle progression in AR-negative stromal cells or AR-positive stromal cells when androgens are depleted. Upon stimulation with androgen in AR-positive stromal cells, E2F1 is displaced from the binding site by AR and replaced with E2F4, leading to the recruitment of the silencing mediator for retinoid and thyroid hormone receptor (SMRT)/histone deacetylase 3 (HDAC3) corepressor complex and repression of cyclin B1 at the chromatin level. The switch between E2F1 and E2F4 at the E2F binding site of the cyclin B1 promoter coincides with an androgen-dependent interaction between AR and E2F1 as well as the cytoplasmic-to-nuclear translocation of E2F4. Thus, we identified a novel mechanism for E2F factors in the regulation of cell cycle gene expression and cell cycle progression under the control of AR signaling.