Amino acids and their roles in tumor immunotherapy of breast cancer.

Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.

Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discriminative feature genes, and existing methods fail to deal with this problem efficiently. This article proposes a novel metaheuristic approach for gene feature extraction, called variable neighborhood learning Harris Hawks optimizer (VNLHHO). First, the F-score is used for a primary selection of the genes in gene expression data to narrow down the selection range of the feature genes. Subsequently, a variable neighborhood learning strategy is constructed to balance the global exploration and local exploitation of the Harris Hawks optimization. Finally, mutation operations are employed to increase the diversity of the population, so as to prevent the algorithm from falling into a local optimum. In addition, a novel activation function is used to convert the continuous solution of the VNLHHO into binary values, and a naive Bayesian classifier is utilized as a fitness function to select feature genes that can help classify biological tissues of binary and multi-class cancers. An experiment is conducted on gene expression profile data of eight types of tumors. The results show that the classification accuracy of the VNLHHO is greater than 96.128% for tumors in the colon, nervous system and lungs and 100% for the rest. We compare seven other algorithms and demonstrate the superiority of the VNLHHO in terms of the classification accuracy, fitness value and AUC value in feature selection for gene expression data.

[Effects of chrysin on the apoptosis in oral squamous carcinoma KB cell line and the underlying mechanisms].

OBJECTIVE: To investigate the effect of chrysin on apoptosis of oral squamous carcinoma KB cell line and the possible mechanisms, and to provide new ideas for the treatment of oral cancer.
 Methods: Oral cancer KB cells were treated with different concentrations of chrysin (1, 2, 4, 8, 16, and 32 µmol/L) for 24 h. Cell proliferation was detected by MMT assay; apoptosis was detected by flow cytometry; the activity of caspase-3/7 was detected by chemiluminescent assay; mitochondrial membrane potential in KB cells was determined by JC-1 assay; and Western blotting was used to determine the activation of protein kinase B (AKT) and phosphoinositide-3-kinase (PI3K).
 Results: Chrysin inhibited the proliferation of KB cells in a concentration-dependent manner, accompanied by increase in apoptosis of KB cells, activation of caspase-3/7, decrease in mitochondrial membrane potential, and suppression of the phosphorylation of AKT and PI3K.
 Conclusion: The effect of chrysin on KB cell apoptosis may be related to mitochondrial dysfunction and inhibition of PI3K/AKT pathway.

Folate treatment of pregnant rat dams abolishes metabolic effects in female offspring induced by a paternal pre-conception unhealthy diet.

AIMS/HYPOTHESIS: Paternal high-fat diet prior to mating programmes impaired glucose tolerance in female offspring. We examined whether the metabolic consequences in offspring could be abolished by folate treatment of either the male rats before mating or the corresponding female rats during pregnancy. METHODS: Male F0 rats were fed either control diet or high-fat, high-sucrose and high-salt diet (HFSSD), with or without folate, before mating. Male rats were mated with control-diet-fed dams. After mating, the F0 dams were fed control diet with or without folate during pregnancy. RESULTS: Male, but not female offspring of HFSSD-fed founders were heavier than those of control-diet-fed counterparts (p < 0.05 and p = 0.066 in males and females, respectively). Both male and female offspring of HFSSD-fed founders were longer compared with control (p < 0.01 for both sexes). Folate treatment of the pregnant dams abolished the effect of the paternal diet on the offspring's body length (p Ë‚ 0.05). Female offspring of HFSSD-fed founders developed impaired glucose tolerance, which was restored by folate treatment of the dams during pregnancy. The beta cell density per pancreatic islet was decreased in offspring of HFSSD-fed rats (-20% in male and -15% in female F1 offspring, p Ë‚ 0.001 vs controls). Folate treatment significantly increased the beta cell density (4.3% and 3.3% after folate supplementation given to dams and founders, respectively, p Ë‚ 0.05 vs the offspring of HFSSD-fed male rats). Changes in liver connective tissue of female offspring of HFSSD-fed founders were ameliorated by treatment of dams with folate (p Ë‚ 0.01). Hepatic Ppara gene expression was upregulated in female offspring only (1.51-fold, p Ë‚ 0.05) and was restored in the female offspring by folate treatment (p Ë‚ 0.05). We observed an increase in hepatic Lcn2 and Tmcc2 expression in female offspring born to male rats exposed to an unhealthy diet during spermatogenesis before mating (p Ë‚ 0.05 vs controls). Folate treatment of the corresponding dams during pregnancy abolished this effect (p Ë‚ 0.05). Analysis of DNA methylation levels of CpG islands in the Ppara, Lcn2 and Tmcc2 promoter regions revealed that the paternal unhealthy diet induced alterations in the methylation pattern. These patterns were also affected by folate treatment. Total liver DNA methylation was increased by 1.52-fold in female offspring born to male rats on an unhealthy diet prior to mating (p Ë‚ 0.05). This effect was abolished by folate treatment during pregnancy (p Ë‚ 0.05 vs the offspring of HFSSD-fed male rats). CONCLUSIONS/INTERPRETATION: Folate treatment of pregnant dams restores effects on female offspring's glucose metabolism induced by pre-conception male founder HFSSD.

TNFAIP1 contributes to the neurotoxicity induced by Aß25-35 in Neuro2a cells.

BACKGROUND: Amyloid-beta (Aß) accumulation is a hallmark of Alzheimer's disease (AD) that can lead to neuronal dysfunction and apoptosis. Tumor necrosis factor, alpha-induced protein 1 (TNFAIP1) is an apoptotic protein that was robustly induced in the transgenic C. elegans AD brains. However, the roles of TNFAIP1 in AD have not been investigated. RESULTS: We found TNFAIP1 protein and mRNA levels were dramatically elevated in primary mouse cortical neurons and Neuro2a (N2a) cells exposed to Aß25-35. Knockdown and overexpression of TNFAIP1 significantly attenuated and exacerbated Aß25-35-induced neurotoxicity in N2a cells, respectively. Further studies showed that TNFAIP1 knockdown significantly blocked Aß25-35-induced cleaved caspase 3, whereas TNFAIP1 overexpression enhanced Aß25-35-induced cleaved caspase 3, suggesting that TNFAIP1 plays an important role in Aß25-35-induced neuronal apoptosis. Moreover, we observed that TNFAIP1 was capable of inhibiting the levels of phosphorylated Akt and CREB, and also anti-apoptotic protein Bcl-2. TNFAIP1 overexpression enhanced the inhibitory effect of Aß25-35 on the levels of p-CREB and Bcl-2, while TNFAIP1 knockdown reversed Aß25-35-induced attenuation in the levels of p-CREB and Bcl-2. CONCLUSION: These results suggested that TNFAIP1 contributes to Aß25-35-induced neurotoxicity by attenuating Akt/CREB signaling pathway, and Bcl-2 expression.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

OBJECTIVE: To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. METHODS: We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. RESULTS: A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. CONCLUSION: The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

Log-less metadata management on metadata server for parallel file systems.

This paper presents a novel metadata management mechanism on the metadata server (MDS) for parallel and distributed file systems. In this technique, the client file system backs up the sent metadata requests, which have been handled by the metadata server, so that the MDS does not need to log metadata changes to nonvolatile storage for achieving highly available metadata service, as well as better performance improvement in metadata processing. As the client file system backs up certain sent metadata requests in its memory, the overhead for handling these backup requests is much smaller than that brought by the metadata server, while it adopts logging or journaling to yield highly available metadata service. The experimental results show that this newly proposed mechanism can significantly improve the speed of metadata processing and render a better I/O data throughput, in contrast to conventional metadata management schemes, that is, logging or journaling on MDS. Besides, a complete metadata recovery can be achieved by replaying the backup logs cached by all involved clients, when the metadata server has crashed or gone into nonoperational state exceptionally.

A new hybrid algorithm for three-stage gene selection based on whale optimization.

In biomedical data mining, the gene dimension is often much larger than the sample size. To solve this problem, we need to use a feature selection algorithm to select feature gene subsets with a strong correlation with phenotype to ensure the accuracy of subsequent analysis. This paper presents a new three-stage hybrid feature gene selection method, that combines a variance filter, extremely randomized tree, and whale optimization algorithm. First, a variance filter is used to reduce the dimension of the feature gene space, and an extremely randomized tree is used to further reduce the feature gene set. Finally, the whale optimization algorithm is used to select the optimal feature gene subset. We evaluate the proposed method with three different classifiers in seven published gene expression profile datasets and compare it with other advanced feature selection algorithms. The results show that the proposed method has significant advantages in a variety of evaluation indicators.

A novel DNA damage repair-related gene signature predicting survival, immune infiltration and drug sensitivity in cervical cancer based on single cell sequencing.

Background: Aberrant DNA damage repair (DDR) is one of the hallmarks of tumors, and therapeutic approaches targeting this feature are gaining increasing attention. This study aims to develop a signature of DDR-related genes to evaluate the prognosis of cervical cancer (CC). Methods: Differentially expressed genes were identified between high and low DDR groups of cells from the single-cell RNA sequencing dataset GSE168652 based on DDR scores. Using the ssGSEA and WGCNA methods, DDR-related differentially expressed genes were identified from different patients within the TCGA-CESC cohort. Using Cox analysis and LASSO regression analysis, a DDR-related gene signature was constructed based on the intersection of two groups of differentially expressed genes and DDR-related genes from WGCNA, and validated in GSE52903. Immune cell infiltration analysis, mutation analysis, survival analysis, drug sensitivity analysis, etc., were performed in different groups which were established based on the DDR gene signature scoring. A key gene affecting prognosis was selected and validated through biological experiments such as wound healing, migration, invasion, and comet assays. Results: A novel DDR-related signature was constructed and the nomogram results showed this signature performed better in predicting prognosis than other clinical features for CC. The high DDR group exhibited poorer prognosis, weaker immune cell infiltration in the immune microenvironment, lower expression of immune checkpoint-related genes, lower gene mutation frequencies and more sensitivity to drugs such as BI.2536, Bleomycin and etc. ITGB1, ZC3H13, and TOMM20 were expressed at higher levels in CaSki and HeLa cells compared to ECT1 cells. Compared with the native CaSki and HeLa cells, the proliferation, migration, invasion and DDR capabilities of CaSki and HeLa cell lines with ITGB1 suppressed expression were significantly decreased. Conclusion: The 7 DDR-related gene signature was an independent and powerful prognostic biomarker that might effectively evaluate the prognosis of CC and provide supplementary information for a more personalized evaluation and precision therapy. ITGB1 was a potential candidate gene that may affect the DDR capacity of CC cells, and its mechanism of action was worth further in-depth study.

A novel hybrid algorithm based on Harris Hawks for tumor feature gene selection.

Background: Gene expression data are often used to classify cancer genes. In such high-dimensional datasets, however, only a few feature genes are closely related to tumors. Therefore, it is important to accurately select a subset of feature genes with high contributions to cancer classification. Methods: In this article, a new three-stage hybrid gene selection method is proposed that combines a variance filter, extremely randomized tree and Harris Hawks (VEH). In the first stage, we evaluated each gene in the dataset through the variance filter and selected the feature genes that meet the variance threshold. In the second stage, we use extremely randomized tree to further eliminate irrelevant genes. Finally, we used the Harris Hawks algorithm to select the gene subset from the previous two stages to obtain the optimal feature gene subset. Results: We evaluated the proposed method using three different classifiers on eight published microarray gene expression datasets. The results showed a 100% classification accuracy for VEH in gastric cancer, acute lymphoblastic leukemia and ovarian cancer, and an average classification accuracy of 95.33% across a variety of other cancers. Compared with other advanced feature selection algorithms, VEH has obvious advantages when measured by many evaluation criteria.

Association of RNA-modification "writer" genes with prognosis and response to immunotherapy in patients with low-grade glioma.

RNA modification is a key regulatory mechanism involved in tumorigenesis, tumor progression, and the immune response. However, the potential role of RNA modification "writer" genes in the immune microenvironment of gliomas and their effect on the response to immunotherapy remains unclear. The purpose of this study was to evaluate the role of RNA modification "writer" gene in the prognosis and immunotherapy response of low-grade glioma (LGG). The consensus non-negative matrix factorization (CNMF) method was used to identify different RNA modification subtypes. We used a novel eigengene screening method, the variable neighborhood learning Harris Hawks optimizer (VNLHHO), to screen for eigengenes among the RNA modification subtypes. We constructed a principal components analysis score(PCA_score)-based prognostic prediction model and validated it using an independent cohort. We also analyzed the association between PCA_score and the immune and molecular features of LGG. The results suggested that LGG can be divided into two different RNA modification-based subtypes with distinct prognostic and molecular features. High PCA_score was significantly associated with a poor prognosis in LGG and was an independent prognostic factor. A nomogram containing PCA_score and clinical features was constructed, and it showed a significant predictive value. PCA_score was negatively correlated with tumor purity and the abundance of CD4+ T cells in LGG patients. LGG patients with high PCA_score had lower Tumor Immune Dysfunction and Exclusion scores and showed an immunotherapy response. In conclusion, we report a novel RNA modification-based prognostic model for LGG that lays the foundation for evaluating LGG prognosis and developing more effective therapeutic strategies for these tumors.

The most likely but largely ignored triggering factor for breast (or all) cancer invasion.

Breast cancer development and progression are believed to be a sequential process, from normal to hyperplastic, to in situ, and to invasive and metastatic stages. Given that over 90% of cancer deaths are caused by invasive and metastatic lesions, countless factors and multiple theories have been proposed as the triggering factor for the cascade of actions of cancer invasion. However, those factors and theories are largely based on the studies of cell lines or animal models. In addition, corresponding interventions based on these factors and theories have failed to reduce the incidence rate of invasive and metastatic lesions, suggesting that previous efforts may have failed to arm at the right target. Considering these facts and observations, we are proposing "A focal aberrant degeneration in the myoepithelial cell layer (MECL) as the most likely triggering factor for breast cancer invasion". Our hypothesis is based on our recent studies of breast and multiple other cancers. Our commentary provides the rationale, morphologic, immunohistochemical, and molecular data to support our hypotheses. As all epithelium-derived cancers share a very similar architecture, our hypothesis is likely to be applicable to invasion of all cancer types. We believe that human tissue-derived data may provide a more realistic roadmap to guide the clinic practice.

Depression and Quality of Life in Patients with Gliomas: A Narrative Review.

In patients with gliomas, depression is a common complication that may cause severe psychological barriers and deteriorate the patient's quality of life (QoL). Currently, the Hospital Anxiety and Depression Scale (HADS) is the most commonly used tool to diagnose depression in patients with gliomas. Female sex, unmarried status, low education level, high tumor grade, and a history of mental illness may increase the risks of depression and depressive symptoms in patients with gliomas. The QoL of patients with gliomas can be directly reduced by depression. Therefore, the evaluation and intervention of mood disorders could improve the overall QoL of patients with gliomas. Antidepressant use has become a treatment strategy for patients with gliomas and comorbid depression. This narrative review summarizes the current issues related to depression in patients with gliomas, including the prevalence, risk factors, and diagnostic criteria of depression as well as changes in QoL caused by comorbid depression and antidepressant use. The purpose of this review is to guide clinicians to assess the psychological status of patients with gliomas and to provide clinicians and oncologists with a new treatment strategy to improve the prognosis of such patients.

A novel prognostic model for cutaneous melanoma based on an immune-related gene signature and clinical variables.

Abundant evidence has indicated that the prognosis of cutaneous melanoma (CM) patients is highly complicated by the tumour immune microenvironment. We retrieved the clinical data and gene expression data of CM patients in The Cancer Genome Atlas (TCGA) database for modelling and validation analysis. Based on single-sample gene set enrichment analysis (ssGSEA) and consensus clustering analysis, CM patients were classified into three immune level groups, and the differences in the tumour immune microenvironment and clinical characteristics were evaluated. Seven immune-related CM prognostic molecules, including three mRNAs (SUCO, BTN3A1 and TBC1D2), three lncRNAs (HLA-DQB1-AS1, C9orf139 and C22orf34) and one miRNA (hsa-miR-17-5p), were screened by differential expression analysis, ceRNA network analysis, LASSO Cox regression analysis and univariate Cox regression analysis. Their biological functions were mainly concentrated in the phospholipid metabolic process, transcription regulator complex, protein serine/threonine kinase activity and MAPK signalling pathway. We established a novel prognostic model for CM integrating clinical variables and immune molecules that showed promising predictive performance demonstrated by receiver operating characteristic curves (AUC ≥ 0.74), providing a scientific basis for predicting the prognosis and improving the clinical outcomes of CM patients.

The Ter mutation in the dead end gene causes germ cell loss and testicular germ cell tumours.

In mice, the Ter mutation causes primordial germ cell (PGC) loss in all genetic backgrounds. Ter is also a potent modifier of spontaneous testicular germ cell tumour (TGCT) susceptibility in the 129 family of inbred strains, and markedly increases TGCT incidence in 129-Ter/Ter males. In 129-Ter/Ter mice, some of the remaining PGCs transform into undifferentiated pluripotent embryonal carcinoma cells, and after birth differentiate into various cells and tissues that compose TGCTs. Here, we report the positional cloning of Ter, revealing a point mutation that introduces a termination codon in the mouse orthologue (Dnd1) of the zebrafish dead end (dnd) gene. PGC deficiency is corrected both with bacterial artificial chromosomes that contain Dnd1 and with a Dnd1-encoding transgene. Dnd1 is expressed in fetal gonads during the critical period when TGCTs originate. DND1 has an RNA recognition motif and is most similar to the apobec complementation factor, a component of the cytidine to uridine RNA-editing complex. These results suggest that Ter may adversely affect essential aspects of RNA biology during PGC development. DND1 is the first protein known to have an RNA recognition motif directly implicated as a heritable cause of spontaneous tumorigenesis. TGCT development in the 129-Ter mouse strain models paediatric TGCT in humans. This work will have important implications for our understanding of the genetic control of TGCT pathogenesis and PGC biology.

A Novel Prognostic Model of Endometrial Carcinoma Based on Clinical Variables and Oncogenomic Gene Signature.

Due to the difficulty in predicting the prognosis of endometrial carcinoma (EC) patients by clinical variables alone, this study aims to build a new EC prognosis model integrating clinical and molecular information, so as to improve the accuracy of predicting the prognosis of EC. The clinical and gene expression data of 496 EC patients in the TCGA database were used to establish and validate this model. General Cox regression was applied to analyze clinical variables and RNAs. Elastic net-penalized Cox proportional hazard regression was employed to select the best EC prognosis-related RNAs, and ridge regression was used to construct the EC prognostic model. The predictive ability of the prognostic model was evaluated by the Kaplan-Meier curve and the area under the receiver operating characteristic curve (AUC-ROC). A clinical-RNA prognostic model integrating two clinical variables and 28 RNAs was established. The 5-year AUC of the clinical-RNA prognostic model was 0.932, which is higher than that of the clinical-alone (0.897) or RNA-alone prognostic model (0.836). This clinical-RNA prognostic model can better classify the prognosis risk of EC patients. In the training group (396 patients), the overall survival of EC patients was lower in the high-risk group than in the low-risk group [HR = 32.263, (95% CI, 7.707-135.058), P = 8e-14]. The same comparison result was also observed for the validation group. A novel EC prognosis model integrating clinical variables and RNAs was established, which can better predict the prognosis and help to improve the clinical management of EC patients.

Prognostic value of miR-21 in gliomas: comprehensive study based on meta-analysis and TCGA dataset validation.

Recent studies have highlighted the value of microRNA-21 (miR-21) as a prognostic biomarker in gliomas. However, the role of miR-21 in predicting prognosis remains controversial. We performed a comprehensive study based upon a meta-analysis and The Cancer Genome Atlas (TCGA) glioma dataset validation to clarify the prognostic significance of miR-21 in glioma patients. In this study, we searched Embase, PubMed, Web of science, CNKI, SinoMed, and Wanfang databases for records up to May 2018. Relevant data were extracted to assess the correlation between miR-21 expression and survival in glioma patients. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to describe association strength. We further used multivariate Cox regression analysis to assess miR-21 expression in the TCGA glioma dataset to validate the relationship between miR-21 expression and survival. Nine studies were included in the meta-analysis. Among them, eight studies provided data on overall survival (OS) with a pooled HR of 1.91 (95% CI: 1.34, 2.73), indicating that higher expression of miR-21 was significantly associated with worse OS in glioma patients; for the other study, which provided data on progression-free survival (PFS), no statistically significant HR was reported for PFS in the glioma patients (HR = 1.23, 95% CI: 0.41, 3.72). A multivariate Cox regression analysis of the miR-21 expression in the TCGA glioma dataset revealed that overexpression of miR-21 was a potential independent prognostic biomarker of poorer OS (HR = 1.27, 95% CI: 1.01, 1.59) and poorer PFS (HR = 1.46, 95% CI: 1.17, 1.82). Our findings suggest that higher expression of miR-21 is correlated with poorer glioma prognosis.

The role of microRNA-148a and downstream DLGAP1 on the molecular regulation and tumor progression on human glioblastoma.

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. Currently, the prognosis of the patients with GBM is very poor and new molecular targets and treatment strategies are urgently needed to combat it. MicroRNA-148a (miR-148a) has been shown to be dysregulated in certain tumor types. However, the role of miR-148a in the pathogenesis of GBM is not fully understood. Here we comprehensively analyzed the roles of miR-148a, downstream DLGAP1, and their molecular pathways in GBM. We showed that miR-148a promote the proliferation and growth of GBM cells both in vitro and in vivo, and also induced the migration, invasion, and EMT (epithelial-mesenchymal transition) program of GBM cells by directly targeting DLGAP1. Furthermore, we identified 31 new miR-148a targets and found that miR-148a function was mainly involved in the cell adhesion signaling pathway and was associated with nervous system diseases. Our findings provide a new mechanism for miR-148a-mediated GBM cell invasion and reveal previously unreported targets of miR-148a as well as novel miR-148a-mediated regulatory networks in GBM. These results increase the understanding of the role of miR-148a in GBM and may lead to novel therapeutic strategies for GBM.

Effective Biodegradation of Mycotoxin Patulin by Porcine Pancreatic Lipase.

Patulin is a common contaminant in fruits and vegetables, which is difficult to remove. In this study, the biodegradation of patulin using porcine pancreatic lipase (PPL) was investigated. The method of HPLC was used to analyze the concentration of patulin. Batch degradation experiments were performed to illustrate the effect of PPL amount, pH, temperature, contact time, and initial concentration. Besides, the degradation product of patulin was characterized by full wavelength scanning and MS technologies. The results showed that the optimum degradation conditions of PPL for patulin was observed at pH 7.5, 40°C for 48 h. The percentage of degradation could reach above 90%. The structure of degradable product of patulin was inferred by the molecular weight 159.0594, named C7H11O4+. It indicated that PPL was effective for the degradation of patulin in fruits and vegetables juice.

The Role of Mir-148a in Cancer.

MicroRNAs (miRNAs) are highly conserved noncoding RNAs of about 19-25 nucleotides. Through specifically pairing with complementary sites in 3' untranslated regions (UTRs) of target mRNAs, they mediate post-transcriptional silencing. MicroRNAs have been implicated in many physiological processes including proliferation, differentiation, development, apoptosis, and metabolism. In recent years many studies have revealed that the aberrant expression of miRNA is closely related to oncogenesis and is now an intense field of study. Mir-148a is aberrantly expressed in various cancers and has been identified as an oncogenic or tumor suppressor with crucial roles in the molecular mechanisms of oncogenesis. In this review, we have summarized the role of mir-148a in the oncogenic pathways of gastric, liver, breast and urogenital cancers, and in neurogliocytoma oncogenesis. Studying the functional role of mir-148a is crucial in discovering novel tumor molecular markers and identifying potential therapeutic targets.