Identification of a 5-gene-risk score model for predicting luminal A-invasive lobular breast cancer survival.

Breast cancer is a devastating malignancy, among which the luminal A (LumA) breast cancer is the most common subtype. In the present study, we used a comprehensive bioinformatics approach in the hope of identifying novel prognostic biomarkers for LumA breast cancer patients. Transcriptomic profiling of 611 LumA breast cancer patients was downloaded from TCGA database. Differentially expressed genes (DEGs) between tumor samples and controls were first identified by differential expression analysis, before being used for the weighted gene co-expression network analysis. The subsequent univariate Cox regression and LASSO algorithm were used to uncover key prognostic genes for constructing multivariate Cox regression model. Patients were stratified into high-risk and low-risk groups according to the risk score, and subjected to multiple downstream analyses including survival analysis, gene set enrichment analysis (GSEA), inference on immune cell infiltration and analysis of mutation burden. Receiving operator curve analysis was also performed. A total of 7071 DEGs were first identified by edgeR package, pink module was found significantly associated with invasive lobular carcinoma (ILC). 105 prognostic genes and 9 predictors were identified, allowing the identification of a 5-key prognostic genes (LRRC77P, CA3, BAMBI, CABP1, ATP8A2) after intersection. These 5 genes, and the resulting Cox model, displayed good prognostic performance. Furthermore, distinct differences existed between two risk-score stratified groups at various levels. The identified 5-gene prognostic model will help deepen the understanding of the molecular and immunological mechanisms that affect the survival of LumA-ILC patients and guide and proper monitoring of these patients.

Fas -670 A/G polymorphism predicts prognosis of hepatocellular carcinoma after curative resection in Chinese Han population.

BACKGROUND: Apoptosis, also called programmed cell death, is a genetically controlled process against hyperproliferation and malignancy. The Fas-Fas ligand (FasL) system is considered a major pathway for apoptosis in cells and tissues. Thus, this study aimed to investigate whether single nucleotide polymorphisms (SNPs) in Fas and FasL gene may have effects on the recurrence and survival of patients with hepatocellular carcinoma (HCC) after curative hepatectomy. METHODS: We investigated the relationship between Fas rs1800682, rs2234767 and FasL rs763110 polymorphisms and recurrence-free survival (RFS) as well as overall survival (OS) in 117 Chinese Han patients with HCC who underwent hepatectomy. RESULTS: In Kaplan-Meier survival analysis, only Fas rs1800682 (-670 A/G) was associated with RFS and OS. Compared with AA genotype, the AG/GG genotype was significantly associated with better RFS (P = 0.008) and OS (P = 0.020). Moreover, multivariate Cox regression analysis showed that Fas rs1800682 remained as a significant independent predictor of RFS for HCC patients with hepatectomy [AG/GG vs. AA: adjusted hazard ratio = 0.464, 95% confidence interval: 0.275-0.782, P = 0.004], but was not an independent predictor of OS (P = 0.395). CONCLUSIONS: This study demonstrated that Fas -670 G allele may play a protective role in the recurrence and survival of HCC patients with hepatectomy. Furthermore, Fas rs1800682 polymorphism might be a promising biomarker for HCC patients after hepatectomy.

Cervical spinal functional magnetic resonance imaging of the spinal cord injured patient during electrical stimulation.

PURPOSE: To evaluate the spatial distribution and signal intensity changes following spinal cord activation in patients with spinal cord injury. METHODS: This study used spinal functional magnetic resonance imaging (fMRI) based on signal enhancement by extra-vascular water protons (SEEP) to assess elicited responses during subcutaneous electrical stimulation at the right elbow and right thumb in the cervical spinal cord. RESULTS: Seven healthy volunteers and seven patients with cervical spinal cord injury (SCI) were included in this study. Significant functional activation was observed mainly in the right side of the spinal cord at the level of the C5-C6 cervical vertebra in both the axial and sagittal planes. A higher percentage of signal changes (4.66 ± 2.08 % in injured subjects vs. 2.78 ± 1.66 % in normal) and more average activation voxels (4.69 ± 2.59 in injured subjects vs. 2.56 ± 1.13 in normal subject) in axial plane at the C5-C6 cervical vertebra with a statistically significant difference. The same trends were observed in the sagittal plane with higher percentage of signal changes and more average activation voxels, though no statistically significant difference compared with the control group. CONCLUSIONS: Spinal SEEP fMRI is a powerful noninvasive method for the study of local neuronal activation in the human spinal cord, which may be of clinical value for evaluating the effectiveness of interventions aimed at promoting recovery of function using electrical stimulation.

EGR3 Inhibits Tumor Progression by Inducing Schwann Cell-Like Differentiation.

The mechanism and function of the expression of Schwann characteristics by nevus cells in the mature zone of the dermis are unknown. Early growth response 3 (EGR3) induces Schwann cell-like differentiation of melanoma cells by simulating the process of nevus maturation, which leads to a strong phenotypic transformation of the cells, including the formation of long protrusions and a decrease in cell motility, proliferation, and melanin production. Meanwhile, EGR3 regulates the levels of myelin protein zero (MPZ) and collagen type I alpha 1 chain (COL1A1) through SRY-box transcription factor 10 (SOX10)-dependent and independent mechanisms, by binding to non-strictly conserved motifs, respectively. Schwann cell-like differentiation demonstrates significant benefits in both in vivo and clinical studies. Finally, a CD86-P2A-EGR3 recombinant mRNA vaccine is developed which leads to tumor control through forced cell differentiation and enhanced immune infiltration. Together, these data support further development of the recombinant mRNA as a treatment for cancer.

Follicular carcinoma of the thyroid with a single metastatic lesion in the lumbar spine: A case report.

BACKGROUND: The bone is the second most common site of thyroid cancer metastasis, after the lung. Treatment options for bone metastasis of thyroid cancer include surgery, radioiodine therapy (RAIT), external radiation therapy, thyroid-stimulating hormone (TSH) inhibition, bisphosphonates, and small-molecule targeted therapies. In most cases, thyroid carcinoma is found in the thyroid tissue; reports of follicular thyroid carcinoma with a single metastasis to the lumbar spine are rare. CASE SUMMARY: We report a case of bone metastasis as the only clinical manifestation of thyroid cancer. The patient was a 67-year-old woman with lumbar pain for 7 years and aggravation with intermittent claudication who had previously undergone partial thyroidectomy of a benign thyroid lesion. No abnormal nodules were found in the bilateral thyroid glands. However, imaging studies were consistent with a spinal tumor, and the lesion was diagnosed as a metastatic follicular carcinoma of thyroid origin. We adopted a multidisciplinary collaboration and comprehensive treatment approach. The patient underwent lumbar spine surgery, total resection of the thyroid, postoperative TSH suppression therapy, and RAIT. There were no complications associated with the operation, and the patient had good postoperative recovery. She has experienced no recurrence. CONCLUSION: Follicular thyroid carcinoma is associated with early hematogenous metastasis, and the bone is a typical site of metastasis. Single bone metastasis is not a contraindication to medical procedures, and providing the appropriate therapy can result in better outcomes and quality of life for these patients.

Nomogram for predicting overall survival in Chinese triple-negative breast cancer patients after surgery.

BACKGROUND: There are few nomograms for the prognosis of Chinese patients with triple-negative breast cancer (TNBC). AIM: To construct and validate a nomogram for overall survival (OS) of Chinese TNBC patients after surgery. METHODS: This study used the data of SEER*stat 8.3.5 and selected Chinese patients with TNBC operated on between 2010 and 2015. Univariate and multivariate Cox proportional hazard regression models were used. The identified variables were integrated to form a predictive nomogram and risk stratification model; it was assessed with C-indexes and calibration curves. RESULTS: The median and maximal OS of the 336 patients was 39 and 83 mo, respectively. The multivariate analysis showed that age (P = 0.043), marital status (P = 0.040), tumor localization (P = 0.030), grade (P = 0.035), T classification (P = 0.012), and N classification (P = 0.002) were independent prognostic factors. The six variables were combined to construct a 1-, 3- and 5-year OS nomogram. The C-indexes of the nomogram to predict OS were 0.766 and compared to the seventh edition staging system, which was higher (0.766 vs 0.707, P < 0.001). In order to categorize patients into different prognostic groups, a risk stratification model was created. There was a significant difference between the Kaplan-Meier curves of the entire cohort and each disease stage according to the nomogram. CONCLUSION: The nomogram provided prognostic superiority over the traditional tumor, node and metastasis system. It could help clinicians make individual OS or risk predictions for Chinese TNBC patients after surgery.

Individualized treatment of breast cancer with chronic renal failure: A case report and review of literature.

BACKGROUND: Studies have shown that patients with chronic renal failure (CRF) are more likely to suffer from breast cancer and other malignant tumors. To our knowledge, CRF can reduce drug excretion, thereby increase drug exposure and lead to increased toxicity, which will limit drug treatment and lead to tumor progression. Currently, there are few successful reports on the combination of docetaxel, trastuzumab, and pertuzumab (THP) as a neoadjuvant treatment regimen for breast cancer patients with CRF. CASE SUMMARY: We report a breast cancer (cT2N2M0, Her-2+/HR-) patient with CRF. It was a clinical stage IIIA tumor on the left breast. The patient had suffered from uremia for 2 years, and her heart function was normal. Based on the pathological type, molecular type, and clinical stage of breast cancer, and the patient's renal function, the clinician analyzed the pharmacological and pharmacokinetic characteristics of the antitumor drugs after consulting the relevant literature, and prescribed the neoadjuvant regimen of THP (docetaxel 80 mg/m², trastuzumab 8 mg/kg for the first dose, and 6 mg/kg for the maintenance dose with pertuzumab 840 mg for the first dose and 420 mg for the maintenance dose), once every 3 wk, for a total of 6 courses. The neoadjuvant treatment had a good effect, and the patient then underwent surgery which was uneventful. CONCLUSION: CRF is not a contraindication for systemic treatment and surgery of breast cancer. The THP regimen without dose adjustment may be a safe and effective neoadjuvant treatment for HER-2 positive breast cancer patients with CRF.

Electronic structures of LixV2O5 (x=0.5 and 1): a theoretical study.

The electronic properties of alpha-Li(x)V2O5 (x=0.5 and 1) are investigated using first principle calculations based on density functional theory with local density approximation. Different intercalation sites for Li in the V2O5 lattices are considered, showing different influences on the electronic structures of Li(x)V2O5. The lowest total energy is found when Li is only intercalated along the c axis between two bridging oxygen ions of sequential V2O5 layers. The intercalation of Li into V2O5 does not change the electron transition property of V2O5, which is an indirect band gap semiconductor, but leads to a reduction of vanadium ions and an increase of the Fermi level of Li(x)V2O5 arising from the electron transfer from the Li 2 s orbital to the initially empty conduction band of the V2O5 host.

Computer Simulation Elucidates Yeast Flocculation and Sedimentation for Efficient Industrial Fermentation.

Flocculation plays an important role in the immobilized fermentation of biofuels and biochemicals. It is essential to understand the flocculation phenomenon at physical and molecular scale; however, flocs cannot be studied directly due to fragile nature. Hence, the present study is focused on the morphological specificities of yeast flocs formation and sedimentation via the computer simulation by a single floc growth model, based on Diffusion-Limited Aggregation (DLA) model. The impact of shear force, adsorption, and cell propagation on porosity and floc size is systematically illustrated. Strong shear force and weak adsorption reduced floc size but have little impact on porosity. Besides, cell propagation concreted the compactness of flocs enabling them to gain a larger size. Later, a multiple flocs growth model is developed to explain sedimentation at various initial floc sizes. Both models exhibited qualitative agreements with available experimental data. By regulating the operation constraints during fermentation, the present study will lead to finding optimal conditions to control the floc size distribution for efficient fermentation and harvesting.

Preparation and characterization of anti-GP73 monoclonal antibodies and development of double-antibody sandwich ELISA.

BACKGROUND: Serum Golgi protein 73 (GP73) as a novel and potential marker for diagnosing hepatocellular carcinoma (HCC) have been found to be elevated in HCC patients and associated with clinical variables representing tumor growth and invasiveness. The aim of this study was to prepare a pair of monoclonal antibodys (mAbs) against GP73 and develop a newly designed double-antibody sandwich enzyme-linked immunosorbent assay (s-ELISA), which would be used in the detection of serum GP73 (sGP73) as well as in the diagnosis of HCC. MATERIALS AND METHODS: Produced by prokaryotic expression, the purified recombinant GP73 (rGP73), produced by prokaryotic expression, was used to immunize the Balb/c mice. Two hybridoma cell lines against GP73 were obtained by fusing mouse Sp2/0 myeloma cells with spleen cells from the immunized mice. The titers of anti-GP73 mAb reached 1:243,000. Western blotting analysis and Immunohistochemistry staining revealed that anti-GP73 mAb could recognize GP73 protein. The double-antibody s-ELISA was successfully established and validated by 119 HCC and 103 normal serum samples. RESULTS: showed that the detection limit of this method could reach 1.56 ng/ml, and sGP73 levels in HCC group (mean=190.6 ng/ml) were much higher than those of in healthy controls (mean=70.92 ng/ml). CONCLUSIONS: Results of our study not only showed that sGP73 levels of HCC patients were significantly higher than those of healthy controls, but also indicated that the laboratory homemade anti-GP73 mAbs could be the optimal tool used in evaluating sGP73 levels, which would provide a solid foundation for subsequent clinical applications.

Computational prediction of cleavage using proteasomal in vitro digestion and MHC I ligand data.

Proteasomes are responsible for the production of the majority of cytotoxic T lymphocyte (CTL) epitopes. Hence, it is important to identify correctly which peptides will be generated by proteasomes from an unknown protein. However, the pool of proteasome cleavage data used in the prediction algorithms, whether from major histocompatibility complex (MHC) I ligand or in vitro digestion data, is not identical to in vivo proteasomal digestion products. Therefore, the accuracy and reliability of these models still need to be improved. In this paper, three types of proteasomal cleavage data, constitutive proteasome (cCP), immunoproteasome (iCP) in vitro cleavage, and MHC I ligand data, were used for training cleave-site predictive methods based on the kernel-function stabilized matrix method (KSMM). The predictive accuracies of the KSMM+pair coefficients were 75.0%, 72.3%, and 83.1% for cCP, iCP, and MHC I ligand data, respectively, which were comparable to the results from support vector machine (SVM). The three proteasomal cleavage methods were combined in turn with MHC I-peptide binding predictions to model MHC I-peptide processing and the presentation pathway. These integrations markedly improved MHC I peptide identification, increasing area under the receiver operator characteristics (ROC) curve (AUC) values from 0.82 to 0.91. The results suggested that both MHC I ligand and proteasomal in vitro degradation data can give an exact simulation of in vivo processed digestion. The information extracted from cCP and iCP in vitro cleavage data demonstrated that both cCP and iCP are selective in their usage of peptide bonds for cleavage.