Lung cancer is the leading cause of cancer death in men and women worldwide. lung cancers. Furthermore microRNAs circulate in body fluids and therefore may serve as promising biomarkers for early diagnosis of lung cancer as well as for predicting prognosis of patients. In the present review we briefly summarize microRNAs in the development and progression of lung cancer focusing on possible applications of microRNAs as novel biomarkers and tools for treatment. Family The family was the first identified microRNA in humans . In lung cancer has been shown to inhibit the expression of oncogenes involved in cellular proliferation such as [18 19 also inhibits the expression of directly down-regulates expression suggesting that may regulate the global production of microRNAs . 3.1 Family members The family members (family members is down-regulated in lung tumor resulting in the up-regulation of focus on genes such as for example ((and by decreased expression qualified prospects to cell proliferation. reliant PDGFR-α/β downregulation inhibits tumorigenesis and enhances Path (TNF-related apoptosis-inducing ligand)-induced apoptosis in lung tumor . 3.1 Family members The family members (and UV-DDB2 ((family members encourages EMT in the development of A 922500 lung tumor [25 26 3.2 Oncogenic microRNAs 3.2 is among the most consultant oncogenic microRNAs getting overexpressed in a variety of types of good tumors aswell as A 922500 leukemia. drives tumorigenesis through inhibition of bad regulators of RAS/MEK/ERK suppression and pathway of apoptosis. Overexpressed downregulates the expressions of  [28 29 30 and  advertising cell migration and proliferation and inhibiting apoptosis. 3.2 Cluster The polycistronic cluster comprises seven different microRNAs (gene at 13q31.3 . The cluster was reported to become overexpressed in lung tumor specifically SCLC . Overexpression of cluster down-regulates and so are mixed up in development and development of lung tumor by focusing on and tumor suppressor genes [34 35 Overexpressed inhibits apoptosis and promotes cell migration by down-regulating PTEN and TIMP3. 4 Diagnostic microRNAs 4.1 Diagnostic microRNAs in Tissues Early detection of lung cancer is prerequisite to reduce lung A 922500 cancer mortality because lung cancers are often diagnosed at advanced stages where clinical treatments are less (or least) effective. MicroRNA expression signatures of lung cancer have been reported by numerous studies however the reported microRNA profiles were not so consistent. Vosa performed a comprehensive meta-analysis of 20 published microRNA expression studies in lung cancer including a total A 922500 of 598 tumor and 528 normal lung tissues . Using a recently published robust rank aggregation method they identified a statistically significant microRNA meta-signature of seven up-regulated (in sputum was higher in NSCLC patients and the detection of expression produced 70% sensitivity and 100% specificity in the distinction between 23 NSCLC patients and 17 cancer-free individuals. In another study using an independent set they demonstrated that the expression profile of four sputum microRNAs (as a biomarker to distinguish lung cancer patients from healthy individuals. Because is overexpressed in various types of cancer further studies are warranted to examine expression for the distinction between lung cancer patients and patients of the other cancers. 5 MicroRNAs as Biomarkers for Histological Classification Recent advances in the treatment of NSCLC with new drugs require an appropriate histological subtyping at diagnosis to avoid hazardous side effects. For instance bevacizumab (brand name: Avastin) a monoclonal antibody which blocks angiogenesis by inhibiting vascular endothelial growth factor A (VEGFA) cannot be used for SqCC patients due to serious hemorrhagic complications. Similarly pemetrexed (brand name: Alimta) a chemotherapy drug belonging to a class of chemotherapeutic drugs known as folate antimetabolites cannot be used for SqCC patients due to adverse responses. Several studies have been conducted to distinguish between SqCC and non-SqCC NSCLC utilizing microRNAs profiles [41 42 43 Lebanony found that higher expression of was specific to SqCC in a test set. In an independent validation set expression in FFPE samples yielded 96% sensitivity and 90% specificity in.