Background: Numerous studies have shown that long non-coding RNAs (lncRNAs) play key roles during multiple cancer processes, such as cell proliferation, apoptosis, migration and invasion. The previous studies found that NKILA interacted with and suppressed the nuclear translocation of NF-KappaB, which influenced metastasis and prognosis in breast cancer. However the clinical significance and biological role of NKILA in non-small cell lung cancer (NSCLC) remains unknown. Methods: We examined expression levels of NKILA in 106 pairs of NSCLC tissues and cell lines. The expression level of NKILA after TGF-β1 stimulation also was examined by qRT-PCR and validated by Chromatin immunoprecipitation (ChIP). Gain-of-function and loss-of-function assays were performed to examine the effect of NKILA on proliferation, migration and invasion of NSCLC cells. RNA immunoprecipitation (RIP), western blot and rescue experiments were carried out to reveal the interrelation between NKILA, NF-κB and EMT signal pathway. Results: The expression of NKILA was down-regulated in NSCLC cancer tissues compared with matched adjacent noncancerous tissues, and lower NKILA expression in tumor tissues were significantly correlated with lymph node metastasis and advanced TNM stage. We found that the expression of NKILA was mainly regulated by classical TGF-β signal pathway in NSCLC cells rather than NF-κB pathway reported in breast cancer. Gain and loss of function assays found that NKILA inhibited migration, invasion and viability of NSCLC cells. Mechanistic study showed that NKILA attenuated Snail expression via inhibiting the phosphorylation of IκBα and NF-κB activation, subsequently suppressed the expression of markers of epithelial-mesenchymal transition process. Conclusions: The present study found that the expression of NKILA was downregulated in tumor tissues of NSCLC, which improved the metastasis of NSCLC patients. In vitro studies further clarified that the expression of NKILA was regulated through classical TGF-β signal pathway, which subsequently inhibited migration and invasion of NSCLC cells through interfering NF-κB/Snail signal pathway in NSCLC cells.

Special AT-rich sequence binding protein 1 (SATB1) is found acting as a “genome organizer” that functions as a landing platform to regulate tissue-specific gene ex-pression. In breast cancer cell lines it has been proven that SATB1 could upregulate the expression of the HER2. In this paper, the relevance of SATB1 and HER2 expression was assessed in human breast cancer tissues, and their influence on tumor histological grade and patients’ survival was explored. Using immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH), 169 patients with breast cancer were assessed for SATB1 expression, HER2 amplification and hormone-receptor (HR) expression. The effects of SATB1 expression on HER2 and HR expression as well as their association with clinicopathologic characteristics were further analyzed by statistical evaluation. SATB1 expression was correlated with HER2 expression in breast cancer(r = 0.191; p = 0.013). SATB1, HER2 and SATB1/HER2 co-expression was negatively correlated with HR expression (r = −0.228, p = 0.003; r = −0.338, p = 0.000; r = −0.527, p = 0.000, respectively). SATB1 and HER2 single positive and their co-expression were all significantly correlated with higher histological grade (r = 0.239, p = 0.002; r = 0.160, p = 0.038; r = 0.306, p = 0.003, respectively). Multivariate cox regression analyses showed that SATB1 and HER2 were independent risk factors for breast cancer patients, while HR was a protective factor for patients’ survival. Comparing to SATB1 or HER2 single positive expression, SATB1/HER2 co-expression tended to have even worse prognosis. SATB1 and HER2 performed a synergistic effect in breast cancer. Their expression correlated with poorly differentiated breast cancer and indicated an unfavorable prognosis. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1400555050159723 .

The emergence of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) revolutionized the treatment of advanced-stage non-small cell lung cancer (NSCLC). Detected in more than 50% of late-stage lung adenocarcinoma in Asian patients, the EGFR mutation was regarded as a golden mutation for Asians. However, resistance to TKIs seems inevitable and severely hinders patients from getting further benefits from treatment. Even though resistance caused by EGFR T790M could be effectively managed by third-generation EGFR-TKIs currently, resistance to third-generation EGFR-TKIs is still a troublesome issue faced by both clinicians and patients. Various efforts have been made to maximize the benefits of patients from EGFR-TKIs therapy. Thus, new requirements and challenges have been posed to clinicians of this era. In this review, we summarized the clinical evidence on the efficacy of third-generation EGFR-TKIs in patients with EGFR-mutated NSCLC. Then, we discussed advancements in sequential treatment aiming to delay the onset of resistance. Moreover, the resistance mechanisms and features were depicted to help us better understand our enemies. Lastly, we put forward future strategies, including recent approaches involving the utilization of antibody drug conjugates against resistance and research directions about shaping the evolution of NSCLC as a core idea in the management of NSCLC.

Purpose. This study was designed to clarify the prognostic value of tumor microenvironment score and abnormal genomic alterations in TME for breast cancer patients. Method. The TCGA‐BRCA data were downloaded from TCGA and analyzed with R software. The results from analyses were further validated using the dataset from GSE96058, GSE124647, and GSE25066. Results. After analyzing the TCGA data and verifying it with the GEO data, we developed a TMEscore model based on the TME infiltration pattern and validated it in 3273 breast cancer patients. The results suggested that our TMEscore model has high prognostic value. TME features with the TMEscore model can help to predict breast cancer patients’ response to immunotherapy and provide new strategies for breast cancer treatment. Signature 24 was first found in breast cancer. In focal SCNAs, a total of 95 amplified genes and 169 deletion genes in the TMEscore high group were found to be significantly related to the prognosis of breast cancer patients, while 61 amplified genes and 174 deletion genes in the TMEscore low group were identified. LRRC48, CFAP69, and cg25726128 were first discovered and reported to be related to the survival of breast cancer patients. We identified specific mutation signatures that correlate with TMEscore and prognosis. Conclusion. TMEscore model has high predictive value regarding prognosis and patients’ response to immunotherapy. Signature 24 was first found in breast cancer. Specific mutation signatures that correlate with TMEscore and prognosis might be used for providing additional indicators for disease evaluation.