Major Cancer Types Research Articles

RETRACTED ARTICLE: Cirsilineol inhibits cell growth and induces apoptosis in glioma C6 cells via inhibiting MAPK and PI3K/Akt/mTOR signaling pathways

BackgroundGlioma is a major type of brain cancer and responsible for high death rate worldwide due to the delayed diagnosis and chemo-resistance. It is responsible for nearly 16% of all brain cancer incidences with increased prevalence globally.ObjectiveThe present research study deals with discovering the in vitro anticancer potential of cirsilineol on the rat glioma C6 cells through the inhibition of PI3K/Akt/mTOR and MAPK signaling pathways.MethodologyThe in vitro antioxidant potential of cirsilineol was examined by different free radical scavenging analyses. The effects of cirsilineol on the cell viability of C6 and normal Vero cells were investigated by MTT assay. The intracellular ROS production and apoptotic cell death in the cirsilineol-administered C6 cells were scrutinized by fluorescent staining techniques. The contents of TBARS and GSH, SOD and caspase activity were examined using assay kits. The PI3K, mTOR, Akt, ERK1/2, JNK1/2, and p38 expressions in the cirsilineol-supplemented C6 cells were examined by RT-PCR study.ResultsThe cirsilineol treatment appreciably scavenged the DPPH, superoxide, and peroxyl radicals. The cell viability of C6 cells was markedly reduced by the cirsilineol; however, it does not affected the Vero cell viability. The cirsilineol treatment demonstrated the augmented ROS production and apoptosis in the C6 cells. The TBARS level and caspase activity were improved, and GSH level and SOD activity were depleted by the cirsilineol. Cirsilineol effectively inhibited PI3K, mTOR, Akt, ERK1/2, JNK1/2, and p38 expressions in the C6 cells.ConclusionOur findings confirmed that the cirsilineol inhibited cell growth and induced apoptosis in C6 cells by inhibiting the PI3K/Akt/mTOR and MAPK signaling cascades. Hence, it can be a potential candidate to treat the glioma in the future.

Geospatial Distribution of Age-Adjusted Incidence of the Three Major Types of Pediatric Cancers and Waterborne Agrichemicals in Nebraska.

This study was conducted to examine, at the county level, the relationship between pediatric cancer incidence rate and atrazine and nitrate mean concentrations in surface and groundwater. A negative binomial regression analysis was performed to investigate the association between central nervous system (CNS) tumors, leukemia, lymphoma, and atrazine and nitrate mean concentrations in groundwater. The age‐adjusted brain and other CNS cancer incidence was higher than the national average in 63% of the Nebraska counties. After controlling for the counties socio‐economic status and nitrate concentrations in groundwater, counties with groundwater atrazine concentrations above 0.0002 µg/L had a higher incidence rate for pediatric cancers (brain and other CNS, leukemia, and lymphoma) compared to counties with groundwater atrazine concentrations in the reference group (0.0000–0.0002 µg/L). Additionally, compared to counties with groundwater nitrate concentrations between 0 and 2 mg/L (reference group), counties with groundwater nitrate concentrations between 2.1 and 5 mg/L (group 2) had a higher incidence rate for pediatric brain and other CNS cancers (IRR = 8.39; 95% CI: 8.24–8.54), leukemia (IRR = 7.35; 95% CI: 7.22–7.48), and lymphoma (IRR = 5.59; CI: 5.48–5.69) after adjusting for atrazine groundwater concentration and the county socio‐economic status. While these findings do not indicate a causal relationship, because other contaminants or cancer risk factors have not been accounted for, they suggest that atrazine and nitrate may pose a risk relative to the genesis of pediatric brain and CNS cancers, leukemia, and lymphoma.

Methionine Restriction: Ready for Prime Time in the Cancer Clinic?

Attempts to selectively starve cancers in the clinic have been made at least since the time of Warburg beginning 100 years ago. Calorie-restriction or low-carbohydrate diets have had limited success with cancer patients. Methionine restriction is another strategy to selectively starve cancer cells, since cancers are addicted to methionine, unlike normal cells. Methionine addiction of cancer is termed the Hoffman effect. Numerous preclinical studies over the past half century have shown methionine restriction to be highly effective against all major cancer types and synergistic with chemotherapy. Low-methionine medical diets can be effective in lowering methionine and have shown some clinical promise, but they are not palatable and thereby not sustainable. However, selectively choosing among plant-based foods allows a variety of low-methionine diets that are sustainable. Our laboratory has developed a methioninase that can be administered orally as a supplement and has resulted in anecdotal positive results in patients with advanced cancer, including hormone-independent prostate cancer, and other recalcitrant cancers. The question is whether methionine restriction through a low-methionine diet, or even greater methionine restriction with methioninase in combination with a low-methionine diet, is ready for prime time in the clinic, especially in combination with other synergistic therapy. The question will hopefully be answered in the near future, especially for advanced cancer patients who have failed all standard therapy.

Immune-related gene expression signatures: a step forward in the stratification of patients with ovarian clear cell carcinoma†.

Clear cell carcinoma of the ovary (CCC) is one of the five major histological types of ovarian cancer and presents specific clinicopathological features, such as a higher prevalence in the Asian population and a poor response to conventional chemotherapy. In a recent publication in The Journal of Pathology, Heong, Tan, Miwa et al demonstrated the heterogeneity of the immune landscape of CCC. They reported the immune signatures observed in a large cohort of CCC, including tumours from both Asian and Caucasian women. The authors analysed three cohorts from Europe, Japan, and Singapore, with a total of 246 tumours, and evaluated 730 immune-related genes using NanoString technology. The study revealed four main transcriptional subtypes characterised by the expression of specific sets of genes: PD1-high (11%), CTLA4-high (29%), antigen-presentation (42%), and a pro-angiogenic subtype (18%). The two main conclusions of the study were: (1) that CCCs in women of Asian and Caucasian descent share significant molecular similarities, since all four molecular signatures are present in all the cohorts analysed, without any evident differences in frequency; and (2) that the PD1-high and CTLA4-high subtypes were associated with worse clinical outcomes and may be useful when stratifying treatment in early-stage tumours. The immune signature could represent a promising biomarker of immunotherapy response if future prospective studies confirm it. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Landscape of mortality during and within thirty days after non-palliative radiotherapy across eleven major cancer types

Background and PurposePeri-RT mortality (death during or within 30 days of non-palliative radiotherapy) has been historically overlooked, and rates and risk factors are unclear. Materials and MethodsPatients with non-metastatic cancer, treated with non-palliative external beam radiation (RT) 2004–2016, were identified in the National Cancer Database for 11 cancer types: breast, prostate, non-prostate genitourinary, bone/soft tissue, gynecological, head/neck, lymphoma, gastrointestinal (GI), small cell lung, non-small cell lung, and central nervous system (CNS). Multivariable logistic regression was used to identify predictors of peri-RT mortality controlled for 17 covariates, including patient, tumor, and treatment factors. ResultsApproximately 1.53 million patients were identified. Peri-RT mortality was 2.46% overall, spanning two orders of magnitude from 0.14% for breast to 8.52% for CNS. Peri-RT mortality steadily improved from 3.13% in 2004 to 1.78% in 2016 (P < .0001). Major predictors of peri-RT mortality included age, baseline comorbidity, male sex, and stage (P < .0001). Conversely, higher patient volume at the treating facility and use of more conformal RT planning techniques were moderately protective (P < .0001). Racial disparities varied based on disease site, as Black patients had increased peri-RT mortality for breast, lymphoma, and GI cancers, but not for other cancer types. Lack of private insurance was associated with substantially increased peri-RT mortality regardless of cancer type. ConclusionPeri-RT mortality varied considerably according to multiple factors. Sociodemographic differences highlight areas of health disparities and opportunities for quality improvement. Early recognition of patients at increased risk may facilitate implementation of closer monitoring or other preventive measures.

Risk-Adjusted Mortality Rates as a Quality Proxy Outperform Volume in Surgical Oncology-A New Perspective on Hospital Centralization Using National Population-Based Data.

Despite a long-known association between annual hospital volume and outcome, little progress has been made in shifting high-risk surgery to safer hospitals. This study investigates whether the risk-standardized mortality rate (RSMR) could serve as a stronger proxy for surgical quality than volume. We included all patients who underwent complex oncologic surgeries in Germany between 2010 and 2018 for any of five major cancer types, splitting the data into training (2010-2015) and validation sets (2016-2018). For each surgical group, we calculated annual volume and RSMR quintiles in the training set and applied these thresholds to the validation set. We studied the overlap between the two systems, modeled a market exit of low-performing hospitals, and compared effectiveness and efficiency of volume- and RSMR-based rankings. We compared travel distance or time that would be required to reallocate patients to the nearest hospital with low-mortality ranking for the specific procedure. Between 2016 and 2018, 158,079 patients were treated in 974 hospitals. At least 50% of high-volume hospitals were not ranked in the low-mortality group according to RSMR grouping. In an RSMR centralization model, an average of 32 patients undergoing complex oncologic surgery would need to relocate to a low-mortality hospital to save one life, whereas 47 would need to relocate to a high-volume hospital. Mean difference in travel times between the nearest hospital to the hospital that performed surgery ranged from 10 minutes for colorectal cancer to 24 minutes for pancreatic cancer. Centralization on the basis of RSMR compared with volume would ensure lower median travel times for all cancer types, and these times would be lower than those observed. RSMR is a promising proxy for measuring surgical quality. It outperforms volume in effectiveness, efficiency, and hospital availability for patients.

TAp73α is Upregulated in the Most Common Human Cancers

The transcription factor p73 is a member of the p53 tumor suppressor gene family and one of the key regulators of apoptosis. TP73 gene encodes two protein isoforms classes with diverse functions, TAp73 and DNp73, and TAp73 expression in tumor tissues is altered. Unlike the TP53 gene, TP73 is not mutated in cancers. Here, we sought to explore the expression of p73 isoforms across eight major cancer types using the publicly available data deposited at the GDC data portal and the TSVdb database. Our results showed that TAp73α is overexpressed in breast invasive carcinoma, stomach adenocarcinoma, lung squamous cell carcinoma, colon adenocarcinoma, and esophageal carcinoma tumors, whereas the expression of DNp73 isoforms is downregulated in breast invasive carcinoma (DNp73α,β,γ), Prostate Adenocarcinoma (DNp73β), Lung Adenocarcinoma (DNp73α), Lung Squamous Cell Carcinoma (DNp73α) tumors. In summary, this study revealed that TAp73α has higher expression than the DNp73 isoforms in several cancer types.

Can we infer tumor presence of single cell transcriptomes and their tumor of origin from bulk transcriptomes by machine learning?

There is a growing need to build a model that uses single cell RNA-seq (scRNA-seq) to separate malignant cells from nonmalignant cells and to identify tumor of origin of single cells and/or circulating tumor cells (CTCs). Currently, it is infeasible to build a tumor of origin model learnt from scRNA-seq by machine learning (ML). We then wondered if an ML model learnt from bulk transcriptomes is applicable to scRNA-seq to infer single cells’ tumor presence and further indicate their tumor of origin. We used k-nearest neighbors, one-versus-all support vector machine, one-versus-one support vector machine, random forest and introduced scTumorTrace to conduct a pioneering experiment containing leukocytes and seven major cancer types where bulk RNA-seq and scRNA-seq data were available. 13 ML models learnt from bulk RNA-seq were all reliable to use (F-score > 96%) shown by a validation set of bulk transcriptomes, but none of them was applicable to scRNA-seq except scTumorTrace. Making inferences from bulk RNA-seq to scRNA-seq was impaired by feature selection and improved by log2-transformed TPM units. scTumorTrace with transcriptome-wide 2-tuples showed F-score beyond 98.74 and 94.29% in inferring tumor presence and tumor of origin at single-cell resolution and correctly identified 45 single candidate prostate CTCs but lineage-confirmed non-CTCs as leukocytes. We concluded that modern ML techniques are quantitative and could hardly address the raised questions. scTumorTrace with transcriptome-wide 2-tuples is qualitative, standardization-free and not subject to log2-transformed quantities, enabling us to infer tumor presence of single cell transcriptomes and their tumor of origin from bulk transcriptomes.

Lung Cancer Therapeutics Landscape, A Current Overview

Lung cancer is the leading cause of death across the world, both among men and women. According to the CDC, Center for Disease Control and Prevention, every year, about 200,000 people are diagnosed and about 150,000 people die because of lung cancer. Lung cancer begins in the lungs, a pair of respiratory organs in the thoracic cavity. Majority of the lung cancers are carcinogenic in nature, which means the uncontrolled tumor cell growth causes malignant tumor cells, eventually spread out from the lungs to the nearby lymph nodes and possibly to other organs, for example, the brain. Two major types of lung cancers are small cell and non-small cell lung cancers. Non-small cell lung cancer constitutes 80 to 90% of all lung cancers and can further be subdivided into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These different types of lung cancers develop differently, grow differently, and are treated differently. Cigarette smoking has been attributed to the number one cause of lung cancer across the world and links to almost 80 to 90% of all lung cancers. Historically, lung cancers have been treated, using conventional therapies which include resection surgery, radiotherapy, and chemotherapies. Recent advancement in science lead to targeted therapies for lung cancer, which includes ALK inhibitors, EGFR inhibitors, VEGF inhibitors, and immunotherapies. This review delves into the recent advancement in the lung cancer therapeutic landscape and discusses recent treatment strategies and options available to the patients. This review also discusses new therapies in the pipeline for lung cancers including allogeneic vaccines. Peptide or protein vaccines, autologous dendritic cell vaccines, DNA vaccines, vector-based vaccines, CAR-T therapies, and Heme-sequestering proteins, which are used to target cancer cells.

The Mitochondrial Protein C1QBP Promotes Hepatocellular Carcinoma Progression by Enhancing Cell Survival, Migration and Invasion.

Backgrounds: Hepatocellular carcinoma (HCC) is a major type of death-causing cancer whose pathological mechanisms are not fully understood. In addition, the identification of effective biomarkers for HCC prognosis is in emergency. Although a variety of studies have shown that Complement C11 binding protein (C1QBP) may play a tumor-promoting or tumor-suppressive role in cancer, the functions and mechanisms of C1QBP in HCC progression are under-investigating.Methods and results: Bioinformatic approaches were employed for checking the expression of C1QBP in HCC patient samples and the association between C1QBP mRNA expression and survival rates of patients with HCC or the promoter methylation of C1QBP. MTT analysis, PI/Annexin V staining, transwell and metabolic flux assays were performed to examine the effects of C1QBP on proliferation, apoptosis, migration, invasion, and oxidative phosphorylation of HCC cells. In the present study, we observed that C1QBP is lower expressed in HCC samples and cell lines. Moreover, high levels of C1QBP were associated with unfavorable outcomes of HCC patients. Loss-of-function assays showed that proliferation, migration and invasion of HCC cells were mitigated while cell apoptosis was augmented upon the loos of C1QBP. Moreover, the oxidative phosphorylation was moderately decreased when C1QBP was depleted. Furthermore, we also investigated the methylation status and copy number variation of C1QBP and analyzed their correlation with its mRNA expression in HCC patients. Finally, we suggested that C1QBP is correlated with genes encoding ribosome RPL-related proteins and mitochondrial MRPL-related proteins in HCC patients.Conclusions: C1QBP is correlated with a poor prognosis of HCC patients and promotes the survival, migration and invasion of HCC cells.

Comprehensive Analysis of Tumor Immune Microenvironment and Prognosis of m6A-Related IncRNAs in Lung Adenocarcinoma.

Lung cancer is a fatal disease with high morbidity and mortality. As a major type of non-small cell lung cancer (NSCLC), lung adenocarcinoma (LUAD) has come into the focus of the biological and clinical research. Nevertheless, potential functions of N6-methyladenosine (m6A) methylation-related long non-coding RNAs (lncRNAs) in the tumor immune microenvironment (TIME) remain unclear. Here, we analyzed RNA-seq data of 522 samples from the TCGA-LUAD project. Based on integrative analyses of lncRNA, immune, and clinical profiles, we developed a computational method to determine the characteristics of lncRNAs as an indicators of immune cell infiltration in LUAD patients. Subsequently, we investigated the influence of m6A-related lncRNAs on prognosis and immunotherapy in patients with LUAD. We identified 24 m6A-related lncRNAs that were related to LUAD prognosis and clustered in two molecular subtypes (clusters 1 and 2). Our results suggest that cluster 1 was significantly related to downregulation of PD-L1, enhancement of immune cell infiltration, and good prognosis. Furthermore, p53 and mTOR pathways were enriched in cluster 1, whereas in the cluster 2, PPAR was uncommonly enriched. Patients with LUAD who had lower risk scores exhibited higher immunoscores and lower expression levels of programmed cell death-ligand 1, compared with patients who had higher risk scores. Finally, m6A-related lncRNAs were implicated in the TIME; our findings indicate that these lncRNAs are critical within the TIME in LUAD. These signatures are promising as potential targets for improved LUAD immunotherapy.

Evaluation of deep learning techniques for identification of sarcoma-causing carcinogenic mutations.

The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is sarcoma, mostly found in human bones and soft tissue cells. It commonly occurs in children. According to a survey of the United States of America, there are more than 17,000 sarcoma patients registered each year which is 15% of all cancer cases. Recognition of cancer at its early stage saves many lives. The proposed study developed a framework for the early detection of human sarcoma cancer using deep learning Recurrent Neural Network (RNN) algorithms. The DNA of a human cell is made up of 25,000 to 30,000 genes. Each gene is represented by sequences of nucleotides. The nucleotides in a sequence of a driver gene can change which is termed as mutations. Some mutations can cause cancer. There are seven types of a gene whose mutation causes sarcoma cancer. The study uses the dataset which has been taken from more than 134 samples and includes 141 mutations in 8 driver genes. On these gene sequences RNN algorithms Long and Short-Term Memory (LSTM), Gated Recurrent Units and Bi-directional LSTM (Bi-LSTM) are used for training. Rigorous testing techniques such as Self-consistency testing, independent set testing, 10-fold cross-validation test are applied for the validation of results. These validation techniques yield several metrics such as Area Under the Curve (AUC), sensitivity, specificity, Mathew's correlation coefficient, loss, and accuracy. The proposed algorithm exhibits an accuracy of 99.6% with an AUC value of 1.00.

PAN-CANCER INTEGRATIVE HISTOLOGY-GENOMIC ANALYSIS VIA INTERPRETABLE MULTIMODAL DEEP LEARNING

The rapidly emerging field of deep learning-based computational pathology has demonstrated promise in developing objective prognostic models from histology whole slide images. However, most prognostic models are either based on histology or genomics alone and do not address how histology and genomics can be integrated to develop joint image-omic prognostic models. Additionally identifying explainable morphological and molecular descriptors from these models that govern such prognosis is of interest. We used multimodal deep learning to integrate gigapixel whole slide pathology images, RNA-seq abundance, copy number variation, and mutation data from 5,720 patients across 14 major cancer types. Our interpretable, weakly-supervised, multimodal deep learning algorithm is able to fuse these heterogeneous modalities for predicting outcomes and discover prognostic features from these modalities that corroborate with poor and favorable outcomes via multimodal interpretability. We compared our model with unimodal deep learning models trained on histology slides and molecular profiles alone, and demonstrate performance increase in risk stratification on 9 out of 14 cancers. In addition, we analyze morphologic and molecular markers responsible for prognostic predictions across all cancer types. All analyzed data, including morphological and molecular correlates of patient prognosis across the 14 cancer types at a disease and patient level are presented in an interactive open-access database (this http URL) to allow for further exploration and prognostic biomarker discovery. To validate that these model explanations are prognostic, we further analyzed high attention morphological regions in WSIs, which indicates that tumor-infiltrating lymphocyte presence corroborates with favorable cancer prognosis on 9 out of 14 cancer types studied.

ATM and RAD51 Repair Pathways in Human Lymphocytes Irradiated with 70 MeV Therapeutic Proton Beam.

The repair of radiation-induced DNA damage is a key factor differentiating patients in terms of the therapeutic efficacy and toxicity to surrounding normal tissue. Proton energy substantially determines the types of cancers that can be treated. The present work investigated the DNA double-strand break repair systems, represented by phosphorylated ATM and Rad51. The status of proton therapy energy used to treat major types of cancer is summarized. Here, human lymphocytes from eight healthy donors (male and female) were irradiated with a spread-out Bragg peak using a therapeutic 70 MeV proton beam or with reference X rays. For both types of radiation, the kinetics of pATM and Rad51 repair protein activation (0-24 h) were estimated as determinants of homologous and non-homologous double-strand break repair. Additionally, γ-H2AX was used as the gold standard marker of double-strand breaks. Our results showed that at 30 min postirradiation there was significantly greater accumulation of γ-H2AX (0.6-fold), pATM (2.0-fold), and Rad51 (0.6-fold) in the proton-irradiated cells compared with the X-ray-treated cells. At 24 h post irradiation, for both types of radiation and all investigated proteins, the foci number was still significantly higher when compared with control. Furthermore, the mean value of pATM and Rad51 repair effectiveness was higher in cells exposed to protons than in cells exposed to X rays; however, the difference was significant only for pATM. The largest inter-individual differences in the repair capabilities were noted for Rad51. The association between the frequency of repair protein foci and the frequency of lymphocyte viability at 1 h post irradiation showed a positive correlation for protons but a negative correlation for X rays. These findings indicate that the accumulation of radiation-induced repair protein foci after proton versus X-ray irradiation differs between patients, consequently affecting the cellular responses to particle therapy and conventional radiation therapy.

Prediction of Cancer-Related piRNAs Based on Network-Based Stratification Analysis

PIWI-interacting RNA (PiRNA) was discovered in 2006 and is expected to become a new biomarker for diagnosis and prognosis of various diseases. The purpose of this study is to explore functions of piRNAs and identify cancer subtypes on the basis of the pattern of transcriptome and somatic mutation data. A total of 285 510 SNPs in piRNAs and genes, which might affect piRNA biogenesis or piRNA targets binding were identified. Significant co-expression networks of piRNAs were then constructed separately for 12 major types of cancer. Finally, mutational matrices were mapped to piRNA network, propagated, and clustered for identification of cancer-related piRNAs and cancer subtypes. Findings showed that subtypes of three types of cancer (COAD, STAD and UCEC), which are significantly associated with survival were identified. Analysis of differentially expressed piRNAs in UCEC subtypes showed that piRNA function is closely related to cancer hallmarks “Enabling Replicative Immortality” and contributes to initiation of cancer.

The Epithelial-Mesenchymal Transition Influences the Resistance of Oral Squamous Cell Carcinoma to Monoclonal Antibodies via Its Effect on Energy Homeostasis and the Tumor Microenvironment.

Simple SummaryDeveloping therapeutic resistance to monoclonal antibodies (mAbs) causes increasing failure in oral squamous cell carcinoma (OSCC) treatment. A clear understanding of the molecular basis for drug resistance will pave the way for OSCC management and a new effective therapeutic modality. This review elucidates the role played by EMT during the emergence of mAbs resistance and the configuration of the tumor microenvironment. The cancer cells that undergo the EMT process also cause significant energy substrate consumption which leads to a limited number and function of effective T-cells, eventually leading to immune evasion. This review firstly reveals the implicit crosstalk between the EMT, energy metabolism, and therapeutic resistance of mAbs. A focus on the rebalanced energy homeostasis in cancer cells and T-cells may provide a new perspective on the treatment of OSCC.Oral squamous cell carcinoma (OSCC) is a major type of cancer that accounts for over 90% of all oral cancer cases. Recently developed evidence-based therapeutic regimens for OSCC based on monoclonal antibodies (mAbs), such as cetuximab, pembrolizumab, and nivolumab, have attracted considerable attention worldwide due to their high specificity, low toxicity, and low rates of intolerance. However, the efficacy of those three mAbs remains poor because of the low rate of responders and acquired resistance within a short period of time. The epithelial–mesenchymal transition (EMT) process is fundamental for OSCC growth and metastasis and is also responsible for the poor response to mAbs. During EMT, cancer cells consume abundant energy substrates and create an immunosuppressive tumor microenvironment to support their growth and evade T cells. In this review, we provide an overview of the complex roles of major substrates and signaling pathways involved in the development of therapeutic resistance in OSCC. In addition, we summarize potential therapeutic strategies that may help overcome this resistance. This review aims to help oral oncologists and researchers aiming to manage OSCC and establish new treatment modalities.

MicroRNA-4317 suppresses the progression of hepatocellular carcinoma by targeting ZNF436-mediated PI3K/AKT signaling pathway

Hepatocellular carcinoma (HCC) is a major type of liver cancer with high mortality, which is a prevalent common cancer in the world. Aberrant miRNAs contribute to the progression and development of HCC. Currently, our study demonstrated that miR-4317 was decreased in HCC patient samples tissues and HCC cell lines, which was related to poor clinical features, including tumor size, advanced TNM stage and vascular invasion. Furthermore, we confirmed that miR-4317 suppressed cell viability, proliferation, invasion and migration through loss- and gain-of-function experiment in vitro. In addition, miR-4317 inhibited tumor growth in vivo experiment. Luciferase reporter assays confirmed that ZNF436 was a direct target of miR-4317. Restoration of ZNF436 reversed the role of miR-4317 on HCC. ZNF436 expression was increased in HCC tissues and cell lines, which was negatively correlated with miR-4317 expression. ZNF436 overexpression obviously promoted the cell proliferation, viability, invasion and migration of HCC cells. ZNF436 mediated the regulatory function of miR-4317 on PI3K/AKT pathway. Overall, our data suggest that miR-4317 is a novel tumor suppressor to suppress HCC progression through PI3K/AKT pathway by targeting ZNF436, and may serve as a prognostic biomarker and therapeutic target for HCC.

Cell Behavior of Non-Small Cell Lung Cancer Is at EGFR and MicroRNAs Hands.

Lung cancer is a complex disease associated with gene mutations, particularly mutations of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) and epidermal growth factor receptor (EGFR). Non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) are the two major types of lung cancer. The former includes most lung cancers (85%) and are commonly associated with EGFR mutations. Several EGFR-tyrosine kinase inhibitors (EGFR-TKIs), including erlotinib, gefitinib, and osimertinib, are effective therapeutic agents in EGFR-mutated NSCLC. However, their effectiveness is limited by the development (acquired) or presence of intrinsic drug resistance. MicroRNAs (miRNAs) are key gene regulators that play a profound role in the development and outcomes for NSCLC via their role as oncogenes or oncosuppressors. The regulatory role of miRNA-dependent EGFR crosstalk depends on EGFR signaling pathway, including Rat Sarcoma/Rapidly Accelerated Fibrosarcoma/Mitogen-Activated Protein Kinase/Extracellular Signal-Regulated Kinase 1/2 (Ras/Raf/MEK/ERK1/2), Signal Transducer and Activator of Transcription (STAT), Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells (NF-kB), phosphoinositide 3-kinase/protein kinase B (PI3K/AKT), Janus kinase 1 (JAK1), and growth factor receptor-bound protein 2 (GRB2). Dysregulated expression of miRNAs affects sensitivity to treatment with EGFR-TKIs. Thus, abnormalities in miRNA-dependent EGFR crosstalk can be used as diagnostic and prognostic markers, as well as therapeutic targets in NSCLC. In this review, we present an overview of miRNA-dependent EGFR expression regulation, which modulates the behavior and progression of NSCLC.

Dual role of allele-specific DNA hypermethylation within the TERT promoter in cancer.

Aberrant activation of telomerase in human cancer is achieved by various alterations within the TERT promoter, including cancer-specific DNA hypermethylation of the TERT hypermethylated oncological region (THOR). However, the impact of allele-specific DNA methylation within the TERT promoter on gene transcription remains incompletely understood. Using allele-specific next-generation sequencing, we screened a large cohort of normal and tumor tissues (n = 652) from 10 cancer types and identified that differential allelic methylation (DAM) of THOR is restricted to cancerous tissue and commonly observed in major cancer types. THOR-DAM was more common in adult cancers, which develop through multiple stages over time, than in childhood brain tumors. Furthermore, THOR-DAM was especially enriched in tumors harboring the activating TERT promoter mutations (TPMs). Functional studies revealed that allele-specific gene expression of TERT requires hypomethylation of the core promoter, both in TPM and TERT WT cancers. However, the expressing allele with hypomethylated core TERT promoter universally exhibits hypermethylation of THOR, while the nonexpressing alleles are either hypermethylated or hypomethylated throughout the promoter. Together, our findings suggest a dual role for allele-specific DNA methylation within the TERT promoter in the regulation of TERT expression in cancer.

Evaluation Expression of miR-146a and miR-155 in Non-Small-Cell Lung Cancer Patients.

BackgroundNon−small-cell lung cancer (NSCLC) is the major type of lung cancer. MicroRNAs (miRNAs) are novel markers and targets in cancer therapy and can act as both tumor suppressors and oncogenes and affect immune function. The aim of this study was to investigate the expression of miR146a and miR155 in linked to blood immune cell phenotypes and serum cytokines in NSCLC patients.MethodsThirty-three NSCLC patients and 30 healthy subjects were enrolled in this study. The allele frequencies of potential DNA polymorphisms were studied using polymerase chain reaction (PCR)–restriction fragment length polymorphism (PCR-RFLP) analysis in peripheral blood samples. Quantitative reverse transcription PCR (qRT-PCR) was used to measure the expression of miR-146a and miR-155 in peripheral blood mononuclear cells (PBMCs). Serum cytokine (IL-1β, IL-6, TNF-α, TGF-β, IL-4, IFN-γ) levels were determined by ELISA. The frequency of circulating CD3+CTLA-4+ and CD4+CD25+FOXP3+ (T regulatory cells/Treg) expression was measured by flow cytometry.ResultsmiR-146a was significantly downregulated in PBMC of NSCLC patients (P ≤ 0.001). Moreover, IL-6 and TGF-β levels were elevated in NSCLC patients (P ≤ 0.001, P ≤ 0.018, respectively). CD3+ CTLA-4+ and Treg cells frequencies were higher in patients than in control subjects (P ≤ 0.0001, P ≤ 0.0001, respectively). There was a positive correlation between miR-155 and IL-1β levels (r=0.567, p ≤ 0.001) and a negative correlation between miR-146a and TGF-β levels (r=-0.376, P ≤ 0.031) in NSCLC patients. No significant differences were found in the relative expression of miR-146a and miR-155, cytokine levels or immune cell numbers according to miR-146a and miR-155 (GG/GC/CC, TT/AT/AA) genotypes. However, there was a positive correlation between miR-146a and IL-1β levels (r=0.74, P ≤ 0.009) in GG subjects and a positive correlation between miR-146a expression and CD3+CTLA4+ cell frequency (r=0.79, P ≤ 0.01) in CC genotyped subjects. Conversely, a negative correlation between miR-146a expression and Treg cell frequency (r=−0.87, P ≤ 0.05) was observed with the GG genotype. A positive correlation between miR-155 and IL-1β expression (r=0.58, p ≤ 0.009) in the TT genotype and between miR-155 expression and CD3+CTLA-4 cell frequency (r=0.75, P ≤ 0.01) was observed in the AT genotype.ConclusionsThe current data suggest that the miR-146a expression in PBMC and serum TGF-β and IL-1β levels may act as blood markers in NSCLC patients. Further study is needed to elucidate the link between immune cells and serum miR146 at early disease stages.