Expression profile analysis identifies the long non-coding RNA landscape and the potential carcinogenic functions of LINC00668 in laryngeal squamous cell carcinoma

HDAC5-mediated PRAME regulates the proliferation, migration, invasion, and EMT of laryngeal squamous cell carcinoma via the PI3K/AKT/mTOR signaling pathway

Laryngeal squamous cell carcinoma (LSCC) is an aggressive and lethal malignant neoplasm with extremely poor prognoses. Accumulating evidence has indicated that preferentially expressed antigen in melanoma (PRAME) is correlated with several kinds of cancers. However, there is little direct evidence to substantiate the biological function of PRAME in LSCC. The purpose of the current study is to explore the oncogenic role of PRAME in LSCC. PRAME expression was analyzed in 57 pairs of LSCC tumor tissue samples through quantitative real-time PCR, and the correlation between PRAME and clinicopathological features was analyzed. The result indicated that PRAME was overexpressed in the LSCC patients and correlated with the TNM staging and lymphatic metastasis. The biological functions and molecular mechanism of PRAME in LSCC progression were investigated through in vitro and in vivo assays. Functional studies confirmed that PRAME facilitated the proliferation, invasion, migration, and epithelial-mesenchymal transition of LSCC cells, and PRAME also promoted tumor growth in vivo. HDAC5 was identified as an upstream regulator that can affect the expression of PRAME. Moreover, PRAME played the role at least partially by activating PI3K/AKT/mTOR pathways. The above findings elucidate that PRAME may be a valuable oncogene target, contributing to the diagnosis and therapy of LSCC.

[LINC00668 is Highly Expressed in Lung Squamous Cell Carcinoma and Promotes Tumor Cell Migration and Invasion]

BACKGROUND

A lack of effective treatment for lung squamous cell carcinoma (LUSC) makes it an important factor restricting the 5-year survival rate of non-small cell lung cancer (NSCLC). Long non-coding RNA 00668 (LINC00668) was reported to play crucial regulatory roles in the tumorigenesis and progression of various cancers; however, its role in LUSC is unclear. The aim of this study was to investigate the prognosis value and biological function of LINC00668 in NSCLC, especially in LUSC.

METHODS

The expression pattern of LINC00668 and its relationship with clinical characteristics and prognosis of patients were investigated in the NSCLC especially LUSC based on The Cancer Genome Altas (TCGA) database. Its function in LUSC cells was explored in vitro.

RESULTS

LINC00668 expression was significantly up-regulated in LUSC patients and high expression level of LINC00668 was associated with advanced tumor-node-metastasis (TMN) stage. Moreover, the expression of LINC00668 significantly increased in smoking patients, and was a prognostic indicator for overall survival (OS) of smoking patients with LUSC. In vitro experiments showed that LINC00668 has significantly higher expression level in LUSC cell lines and tissues compared to normal bronchial epithelial cell and para-tumor tissues; meanwhile, functional assay indicated knockdown of LINC00668 effectively inhibited the migration and invasion of LUSC cells.

CONCLUSIONS

LINC00668 might closely relate to the development of LUSC, and inhibition of LINC00668 may reduce the metastasis of LUSC.

The Role of lncRNAs in Rare Tumors with a Focus on HOX Transcript Antisense RNA (HOTAIR)

Rare cancers are identified as those with an annual incidence of fewer than 6 per 100,000 persons and includes both epithelial and stromal tumors from different anatomical areas. The advancement of analytical methods has produced an accurate molecular characterization of most human cancers, suggesting a “molecular classification” that has allowed the establishment of increasingly personalized therapeutic strategies. However, the limited availability of rare cancer samples has resulted in very few therapeutic options for these tumors, often leading to poor prognosis. Long non coding RNAs (lncRNAs) are a class of non-coding RNAs mostly involved in tumor progression and drug response. In particular, the lncRNA HOX transcript antisense RNA (HOTAIR) represents an emergent diagnostic, prognostic and predictive biomarker in many human cancers. The aim of this review is to highlight the role of HOTAIR in rare cancers, proposing it as a new biomarker usable in the management of these tumors.

Long Intergenic Non-Coding RNAs in HNSCC: From "Junk DNA" to Important Prognostic Factor

Head and neck squamous cell carcinoma is one of the most common and fatal cancers worldwide. Even a multimodal approach consisting of standard chemo- and radiotherapy along with surgical resection is only effective in approximately 50% of the cases. The rest of the patients develop a relapse of the disease and acquire resistance to treatment. Especially this group of individuals needs novel, personalized, targeted therapy. The first step to discovering such solutions is to investigate the tumor microenvironment, thus understanding the role and mechanism of the function of coding and non-coding sequences of the human genome. In recent years, RNA molecules gained great interest when the complex character of their impact on our biology allowed them to come out of the shadows of the "junk DNA" label. Furthermore, long non-coding RNAs (lncRNA), specifically the intergenic subgroup (lincRNA), are one of the most aberrantly expressed in several malignancies, which makes them particularly promising future diagnostic biomarkers and therapeutic targets. This review contains characteristics of known and validated lincRNAs in HNSCC, such as XIST, MALAT, HOTAIR, HOTTIP, lincRNA-p21, LINC02487, LINC02195, LINC00668, LINC00519, LINC00511, LINC00460, LINC00312, and LINC00052, with a description of their prognostic abilities. Even though much work remains to be done, lincRNAs are important factors in cancer biology that will become valuable biomarkers of tumor stage, outcome prognosis, and contribution to personalized medicine.

Long non-coding RNAs in head and neck squamous cell carcinoma: Diagnostic biomarkers, targeted therapies, and prognostic roles

At present, emerging evidence shows that non-coding RNAs (ncRNAs) play crucial roles for development of multiple tumors. Amongst these ncRNAs, long non-coding RNAs (lncRNAs) play prominent roles in physiological and pathological processes. LncRNAs are RNA transcripts larger than 200 nucleotides and have been shown to serve important regulatory roles in different types of cancer via interactions with DNA, RNA and proteins. Head and neck squamous cell carcinoma (HNSCC) is one of the most malignant tumors with low survival rates in advanced stages. Recently, lncRNAs have been demonstrated to be involved in a wide range of biological processes, including proliferation, metastasis, and prognosis of HNSCC. Therefore, this review describes molecular mechanisms of up- or down-regulation of lncRNAs and expounds their functions in pathology and clinical practices in HNSCC. It also highlights their potential clinical applications as biomarkers for the diagnosis, prognosis, and treatment of HNSCC. However, studies on lncRNAs are still not comprehensive, and more investigations are needed in the future.

Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma

Long non-coding RNAs (lncRNAs), as one common type of non-coding RNAs, play a critical role in the tumorigenesis and development of hepatocellular carcinoma (HCC). In the current study, we aimed to assess the correlation between lncRNAs expression levels and prognosis of HCC patients. A lncRNA-based signature was also developed to predict the prognosis of HCC in this work. The lncRNAs expression profiles in tissues of tumor and para-carcinoma were obtained from The Cancer Genome Atlas (TCGA) database. The lncRNA-based prognostic model was established by least absolute shrinkage and selection operator (LASSO). The multivariate Cox-regression analysis was applied to identify the independent risk factors and subsequently developed a prognostic nomogram. Based on the co-expression analyses, we identified the lncRNA-related mRNAs and performed the biological function analysis. Between HCC and para-carcinoma tissues, 220 differentially expressed lncRNAs were filtered. Among these lncRNAs, 19 lncRNAs were identified as prognostic factors and were used to build a prognostic signature of overall survival (OS). Furthermore, a nomogram with high performance for predicting the OS of HCC patients (C-index: 0.779) by combining the 19-lncRNA signature (P < 0.001) and clinicopathologic factors including HBV (P = 0.005) and stage (P =0.017) was established. Functional enrichment analysis revealed that 19 lncRNAs had potential effects on tumor cell proliferation in HCC. In summary, we established a 19-lncRNA signature to predict the prognosis of HCC patients, which may perform a crucial role in guiding the management of HCC.

Clinical significance and potential mechanisms of miR-223-3p and miR-204-5p in squamous cell carcinoma of head and neck: a study based on TCGA and GEO

Objective

To explore the clinical significance and mechanisms of altered miRNAs in squamous cell carcinoma of head and neck (SCCHN) and provide references for SCCHN diagnosis and prognosis.

Method

Differential expressed miRNAs (DEMs) in SCCHN were screened through gene expression omnibus (GEO) DataSets and verified by the cancer genome atlas (TCGA) database. Next, the overall survival analysis, receiver operating characteristics, and clinical correlation analysis were adopted to filter the miRNAs with diagnostic and prognostic values. Finally, functional enrichment analyses were conducted for inquiring into the mechanisms of miRNAs.

Results

Total 103 DEMs (p < 0.05, fold change ≥ 2) in SCCHN were screened out from GSE124566. Partly, the expression levels of the selected (12/17) miRNAs were verified by TCGA. Followed, of the 12 miRNAs, two miRNA expression levels were associated with the overall survival, and five miRNAs showed diagnostic values (AUC ≥ 0.85). Besides, miR-223-3p and miR-204-5p expression levels were correlated to certain clinical features. Epithelial–mesenchymal transition (EMT) related biological process and energy metabolism controlling related AMPK signaling pathway might mediate the roles of miR-223-3p and miR-204-5p, respectively.

Conclusion

With diagnostic and prognostic values, miR-223-3p and miR-204-5p may be involved in the progression of SCCHN through EMT-related biological process and energy balance related AMPK signaling pathway, respectively.

Genome-Wide Analysis of the Expression of Circular RNA Full-Length Transcripts and Construction of the circRNA-miRNA-mRNA Network in Cervical Cancer

Increasing evidence suggests that circular RNA (circRNA) plays an important role in tumorigenesis by regulating gene expression at the transcriptional and post-transcriptional levels. Alternative splicing events permit multiple transcript isoforms of circRNA to be produced; however, changes in the expression of circRNA full-length transcripts in cervical cancer remain unclear. Here, we systematically explored the dysregulation circRNA full-length transcripts and constructed an improved circRNA-miRNA-mRNA regulatory network to provide potential biomarkers and possible treatment targets in cervical cancer. We identified 9359 circular full-length transcripts from RNase R-treated RNA-seq data in cervical cancer, of which 353 circular full-length transcripts were significantly differentially expressed (DE) between the tumor and normal group. A total of 881 DE mRNA transcript isoforms were also identified from total RNA-seq data in cervical cancer, of which 421 (47.8%) transcript isoforms were up-regulated, and 460 (52.2%) transcript isoforms were down-regulated in tumor samples. Two circRNA-miRNA-mRNA competitively regulated networks, including 33 circRNA transcripts, 2 miRNAs, and 189 mRNA transcripts were constructed. Three genes (COPE, RAB3B, and TFPI) in the network were significantly associated with overall survival (P < 0.05), which indicated that these genes could act as prognostic biomarkers for patients with cervical cancer. Our study revealed genome-wide differential expression of full-length circRNA transcripts and constructed a more accurate circRNA-miRNA-mRNA network at the full-length transcript expression level in cervical cancer. CircRNA may thus be involved in the development of cervical cancer by regulating the expression of COPE, RAB3B, and TFPI. However, the specific regulatory mechanism in cervical cancer requires further study.

Long noncoding RNAs in head and neck squamous cell carcinoma: biological functions and mechanisms

Head and neck squamous cell carcinoma (HNSCC) is the primary malignant tumor of the oral cavity, larynx, nasopharynx, esophagus and tongue. Although several novel therapeutic methods for HNSCC have been developed, the final therapeutic effect on the patient is still not satisfactory. Thus, it is imperative that scientists identify novel distinguishable markers with specific molecular characteristics that can be used in therapeutic and prognostic evaluation. Previous reports have shown that long noncoding RNAs (lncRNAs) are important regulators of gene expression in many cancers, including head and neck squamous cell carcinomas. Translational studies of lncRNAs in HNSCC are urgently required before their application as a treatment can be realized. We aimed to address the most relevant findings on lncRNAs as biomarkers or treatment targets in head and neck squamous cell carcinoma and to summarize their discovered pathways and mechanisms of action to reveal the possible future applications of these novel biomarkers in clinical translational research.

Enrichment of Up-regulated and Down-regulated Gene Clusters Using Gene Ontology, miRNAs and lncRNAs in Colorectal Cancer

AIM AND OBJECTIVE

It is interesting to find the gene signatures of cancer stages based on the omics data. The aim of study was to evaluate and to enrich the array data using gene ontology and ncRNA databases in colorectal cancer.

METHODS

The human colorectal cancer data were obtained from the GEO databank. The downregulated and up-regulated genes were identified after scoring, weighing and merging of the gene data. The clusters with high-score edges were determined from gene networks. The miRNAs related to the gene clusters were identified and enriched. Furthermore, the long non-coding RNA (lncRNA) networks were predicted with a central core for miRNAs.

RESULTS

Based on cluster enrichment, genes related to peptide receptor activity (1.26E-08), LBD domain binding (3.71E-07), rRNA processing (2.61E-34), chemokine (4.58E-19), peptide receptor (1.16E-19) and ECM organization (3.82E-16) were found. Furthermore, the clusters related to the non-coding RNAs, including hsa-miR-27b-5p, hsa-miR-155-5p, hsa-miR-125b-5p, hsa-miR-21-5p, hsa-miR-30e-5p, hsa-miR-588, hsa-miR-29-3p, LINC01234, LINC01029, LINC00917, LINC00668 and CASC11 were found.

CONCLUSION

The comprehensive bioinformatics analyses provided the gene networks related to some non-coding RNAs that might help in understanding the molecular mechanisms in CRC.

Regulatory Mechanisms of lncRNAs and Their Target Gene Signaling Pathways in Laryngeal Squamous Cell Carcinoma

Laryngeal squamous cell carcinoma (LSCC) is a common malignant tumor that occurs in the head and neck. People living in areas with serious air pollution and those who smoke and drink for a long time belong to high-risk groups. Although great progress has been made in chemotherapy, radiotherapy, and molecular targeted therapy in recent years, the prognosis of patients is still not good. The proliferation, invasion, and apoptosis of LSCC are controlled by many factors, which are the key factors influencing the prognosis of patients. Previous researches have demonstrated that long noncoding RNAs (lncRNAs) can be used as oncogenes or tumor suppressor genes in the occurrence and development of cancer and regulate cancer through various ways including epigenetic regulation and post-transcriptional regulation. The characteristics and roles of lncRNAs in LSCC, however, are not clear. In this review, we will discuss the role and function of lncRNAs in the proliferation, invasion, and apoptosis of LSCC and analyze the relationship between lncRNAs and lncRNA-regulated signaling pathways in LSCC pathological process. The difficulties faced by the related research of LSCC are discussed. It provides reference ideas for the molecular mechanism research of LSCC targeting lncRNA and its signaling pathways, the development of clinical prevention and therapeutic drug and individualized treatment, thereby improving the quality of life of patients.

Linc00668 Promotes Invasion and Stem Cell-Like Properties of Breast Cancer Cells by Interaction With SND1

Long non-coding RNAs (lncRNAs) are reported to be involved in breast cancer progression. Herein, we observed that the expression of Linc00668 was increased in breast cancer compared to normal tissue. The patients with high Linc00668 expression exhibited an association with a higher metastatic risk. We demonstrated that forced expression of Linc00668 enhanced, whereas depletion of Linc00668 diminished invasion and self-renewal of breast cancer cells as well as resistance to doxorubicin (Dox). Further mechanistic studies revealed that Linc00668 associated with staphylococcal nuclease domain-containing 1 (SND1) and regulated the expression of downstream genes. Linc00668 depletion led to reduced expression of the downstream target of SND1 and further attenuated the self-renewal capacity of breast cancer cells. Our observations suggest that Linc00668 promotes metastasis, and chemotherapeutic resistance in breast cancer by interacting with SND1. Therefore, Linc00668 may serve as a potential therapeutic modulator in breast cancer treatment.

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice

Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim to identify a pseudogene-based prognosis signature for HNSCC by machine learning. RNA-seq data were downloaded from The Cancer Genome Atlas, and 700 differentially-expressed pseudogenes were identified. The survival-related pseudogenes were screened through COX-regression analysis, which includes univariate regression, least absolute shrinkage and selection operator regression, and multivariate regression, and a five-pseudogene signature was constructed. The value of prediction for the signature was validated in multiple subgroups in terms of survival. Gene set enrichment analysis (GSEA) and coexpression analysis were used to determine the underlying biological functions. Seven hundred dysregulated pseudogenes were identified, and the five-pseudogene signature can distinguish the low-risk and high-risk patients for both training and testing sets and predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different genders, ages, stages, and grades. Coexpression analysis revealed that the five-pseudogene is associated with immune system. GSEA showed cancer-related biological process and pathways the five-pseudogene involved in. The five-pseudogene signature is not only a novel marker for prognosis but also a promising signature for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

7-lncRNA Assessment Model for Monitoring and Prognosis of Breast Cancer Patients: Based on Cox Regression and Co-expression Analysis

Background: Breast cancer is one of the deadliest malignant tumors worldwide. Due to its complex molecular and cellular heterogeneity, the efficacy of existing breast cancer risk prediction models is unsatisfactory. In this study, we developed a new lncRNA model to predict the prognosis of patients with BRCA.

Methods: BRCA-related differentially-expressed long non-coding RNA were screened from the Cancer Genome Atlas database. A novel lncRNA model was developed by univariate and multivariate analyses to predict the prognosis of patients with BRCA. The efficacy of the model was verified by TCGA-based breast cancer samples. Identified lncRNA-related mRNA based on the co-expression method.

Results: We constructed a 7-lncRNA breast cancer prediction model including LINC00377, LINC00536, LINC01224, LINC00668, LINC01234, LINC02037, and LINC01456. The breast cancer samples were divided into high-risk and low-risk groups based on the model, which verified the specificity and sensitivity of the model. The Area Under Curve (AUC) of the 3- and 5-year Receiver Operating Characteristic curve were 0.711 and 0.734, respectively, indicating that the model has good performance.

Conclusion: We constructed a 7-lncRNA model to predict the prognosis of patients with BRCA, and suggest that these lncRNAs may play a specific role in the carcinogenesis of BRCA.

A Genomic-Clinicopathologic Nomogram Predicts Survival for Patients with Laryngeal Squamous Cell Carcinoma

Background

Long noncoding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. We aimed to establish a lncRNA signature and a nomogram incorporating the genomic and clinicopathologic factors to improve the accuracy of survival prediction for laryngeal squamous cell carcinoma (LSCC).

Methods

A LSCC RNA-sequencing (RNA-seq) dataset and the matched clinicopathologic information were downloaded from The Cancer Genome Atlas (TCGA). Using univariable Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a thirteen-lncRNA signature related to prognosis. On the basis of multivariable Cox regression analysis results, a nomogram integrating the genomic and clinicopathologic predictors was built. The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with the TNM staging system by C-index and receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was conducted to evaluate the clinical value of our nomogram.

Results

Thirteen overall survival- (OS-) related lncRNAs were identified, and the signature consisting of the selected thirteen lncRNAs could effectively divide patients into high-risk and low-risk subgroups, with area under curves (AUC) of 0.89 (3-year OS) and 0.885 (5-year OS). Independent factors derived from multivariable analysis to predict survival were margin status, tumor status, and lncRNA signature, which were all assembled into the nomogram. The calibration curve for the survival probability showed that the predictions based on the nomogram coincided well with actual observations. The C-index of the nomogram was 0.82 (0.77-0.87), and the area under curve (AUC) of the nomogram in predicting overall survival (OS) was 0.938, both of which were significantly higher than the traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had larger net benefit than TNM stage.

Conclusion

An inclusive nomogram for patients with LSCC, comprising genomic and clinicopathologic variables, generates more accurate estimations of the survival probability when compared with TNM stage alone, but more data are needed before the nomogram is used in clinical practice.

Genome‑wide investigation of the clinical implications and molecular mechanism of long noncoding RNA LINC00668 and protein‑coding genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of tumor‑related mortalities worldwide. Long noncoding RNAs have been reported to be associated with tumor initiation, progression and prognosis. The present study aimed to explore the association between long noncoding RNA LINC00668 and its co‑expression correlated protein‑coding genes (PCGs) in HCC. Data of 370 HCC patients from The Cancer Genome Atlas database were used for analysis. LINC00668 and its top 10 PCGs were selected to determine their diagnostic and prognostic value. Molecular mechanisms were explored to identify metabolic processes that LINC00668 and its PCGs are involved in. Prognosis‑related clinical factors and PCGs were used to construct a nomogram for predicting prognosis in HCC. A Connectivity Map was constructed to identify candidate target drugs for HCC. The top 10 PCGs identified were: Pyrimidineregic receptor P2Y4 (P2RY4), signal peptidase complex subunit 2 (SPCS2), family with sequence similarity 86 member C1 (FAM86C1), tudor domain containing 5 (TDRD5), ferritin light chain (FTL), stratifin (SFN), nucleolar complex associated 2 homolog (NOC2L), peroxiredoxin 1 (PRDX1), cancer/testis antigen 2 CTAG2 and leucine zipper and CTNNBIP1 domain containing (LZIC). FAM86C1, CTAG2 and SFN had significant diagnostic value for HCC (total area under the curve ≥0.7, P≤0.05); LINC00668, FAM86C1, TDRD5, FTL and SFN were of significant prognostic value for HCC (all P≤0.05). Investigation into the molecular mechanism indicated that LINC00668 affects cell division, cell cycle, mitotic nuclear division, and drug metabolism cytochrome P450 (all P≤0.05). The Connectivity Map identified seven candidate target drugs for the treatment of HCC, which were: Indolylheptylamine, mimosine, disopyramide, lidocaine, NU‑1025, bumetanide, and DQNLAOWBTJPFKL‑PKZXCIMASA‑N (all P≤0.05). Our findings indicated that LINC00668 may function as an oncogene and its overexpression indicates poor prognosis of HCC. FAM86C1, CTAG2 and SFN are of diagnostic significance, while FAM86C1, TDRD5, FTL and SFN are of prognostic significance for HCC.

Long Non-coding RNAs as Important Biomarkers in Laryngeal Cancer and Other Head and Neck Tumours

Head and neck carcinoma (HNC) is a heterogeneous disease encompassing a variety of tumors according to the origin. Laryngeal cancer (LC) represents one of the most frequent tumors in the head and neck region. Despite clinical studies and advance in treatment, satisfactory curative strategy has not yet been reached. Therefore, there is an urgent need for the identification of specific molecular signatures that better predict the clinical outcomes and markers that serve as suitable therapeutic targets. Long non-coding RNAs (lncRNA) are reported as important regulators of gene expression and represent an innovative pharmacological application as molecular biomarkers in cancer. The purpose of this review is to discuss the most relevant epigenetic and histological prognostic biomarkers in HNC, with particular focus on LC. We summarize the emerging roles of long non-coding RNAs in HNC and LC development and their possible use in early diagnosis.

STAT3-induced long noncoding RNA LINC00668 promotes migration and invasion of non-small cell lung cancer via the miR-193a/KLF7 axis

Long noncoding RNAs (lncRNAs) have been demonstrated to play significant roles in non-small cell lung cancer (NSCLC) progression. Recently, a newly identified lncRNA, LncRNA LINC00668 (LINC00668), was reported to be involved in the regulation of progression of several tumors. However, the expression pattern and biological function of LINC00668 in NSCLC remains largely unclear. In this study, we found that LINC00668 expression was significantly up-regulated in both NSCLC tissues and cell lines. we also showed that LINC00668 upregulation was induced by transcription factor STAT3. Clinical investigation demonstrated that high expression level of LINC00668 was associated with advanced TNM stage, histological grade and lymph node metastasis. Moreover, multivariate analysis confirmed LINC00668 expression level to be an independent prognostic indicator for overall survival of NSCLC patients. Functional assays indicated that knockdown of LINC00668 suppressed NSCLC cells proliferation, migration and invasion, and promoted apoptosis. Mechanistic studies indicated that LINC00668 is a direct target of miR-193a, leading to down-regulation in the expression of its target gene KLF7. Our findings suggested that STAT3-induced LINC00668 contributed to NSCLC progression through upregulating KLF7 expression by sponging miR-193a, and may serve as a prognostic biomarker and a potential target for NSCLC.