Mutasi EGFR pada Non-Small Cell Lung Cancer di Rumah Sakit Kanker “Dharmais”

This descriptive study illustrated the proportion of EGFR mutation in non-small cell lung cancer (NSCLC) at “Dharmais” National Cancer Hospital. Examination of EGFR mutation started in 2015, 196 data was collected and 68 data being analyses. Fixed Formalin Paraffin Embedded (FFPE) processed by cobas® 4800 real time polymerase chain reaction. The results shown 34% patients NSCLC with EGFR mutation and all of them was single mutation. EGFR mutation happens in Exon 21 L858R 10 cases (44 %), Exon 19del 12 cases (52 %) and the type of Exon 20 S768I 1 case (4 %). This study found a high proportion of EGFR mutation

Lysine acetyltransferase 5 in EGFR mutated non-small cell lung cancer

Histone modifications are crucial in activities such as transcriptional activation, gene silencing, and epigenetic cellular memory. In particular, lysine acetylation via lysine (K) acetyltransferases (KATs) has been implicated in cancer development. Interestingly, KAT5, also known as Tip60 (tat-interactive protein-60kDa), has been reported to possess both tumor promoting and tumor suppressing properties depending on the context of malignancy. Herein we report that KAT5 contributes to tumorigenesis in epidermal growth factor receptor (EGFR) mutated lung cancer, and Kat5-knockout mice models demonstrate significantly reduced lung tumor burden. To probe the aberrant modification of KAT5, we demonstrated that KAT5 binds to and is phosphorylated by oncogenic EGFR in co-immunoprecipitation experiments. Next, to investigate whether KAT5 is involved in cell proliferation and survival, H1975 cells harboring L858R-T790M double-activating mutations were transfected with doxycycline inducible short helical RNA (shRNA) targeting KAT5 (shKAT5). Following treatment, shKAT5 cells were observed to have suppressed proliferation rates. Pharmacological inhibition using TH1834, a known KAT5 inhibitor, also suppressed proliferation rates in shKAT5 cells; in contrast BEAS2B cells, an immortalized normal human bronchial cell line, surprisingly exhibited increased viability compared to transformed human lung H1975 cells. This finding supports KAT5’s context-dependent role in in normal and abnormal cell homeostasis. To further investigate KAT5 in lung tumorigenesis in vivo, we generated EGFR-mutant conditional Kat5 knockout mice using a tetracycline-induced Cre/loxP system. Following doxycycline treatment for 10 weeks, isolated mice lungs for EGFRTL/CCSP-rtTA/Cre/Kat5F/F possessed significantly lower tumor volume compared to EGFRTL/CCSP-rtTA/Cre/Kat5wt/F and EGFRTL/CCSP-rtTA/Cre/Kat5wt/wt mice lungs. Hemotoxylin and eosin staining showed no evident hyperproliferation in lungs isolated from EGFRTL/CCSP-rtTA/Cre/Kat5F/F mice whereas lungs isolated from EGFRTL/CCSP-rtTA/Cre/Kat5wt/wt and EGFRTL/CCSP-rtTA/Cre/Kat5wt/F did, signifying that KAT5 has a potential regulatory role in cellular proliferation. RNA-Seq analysis of shKAT5 H1975 cells identified downstream targets involved in tumorigenic pathways. Subsequent quantitative polymerase chain reaction (PCR) of shKAT5 cells served to validate the reported targets. Taken together, these data offer insight into a KAT5 mediated oncogenic pathway that can provide novel therapeutic approaches in treating lung cancer

Deep segmentation networks predict survival of non-small cell lung cancer

Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography-computed tomography (PET/CT) images have predictive power on NSCLC outcomes. To this end, easily calculated functional features such as the maximum and the mean of standard uptake value (SUV) and total lesion glycolysis (TLG) are most commonly used for NSCLC prognostication, but their prognostic value remains controversial. Meanwhile, convolutional neural networks (CNN) are rapidly emerging as a new premise for cancer image analysis, with significantly enhanced predictive power compared to other hand-crafted radiomics features. Here we show that CNN trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value. In a retrospective study on 96 NSCLC patients before stereotactic-body radiotherapy (SBRT), we found that the CNN segmentation algorithm (U-Net) trained for tumor segmentation in PET/CT images, contained features having strong correlation with 2- and 5-year overall and disease-specific survivals. The U-net algorithm has not seen any other clinical information (e.g. survival, age, smoking history) than the images and the corresponding tumor contours provided by physicians. Furthermore, through visualization of the U-Net, we also found convincing evidence that the regions of progression appear to match with the regions where the U-Net features identified patterns that predicted higher likelihood of death. We anticipate our findings will be a starting point for more sophisticated non-intrusive patient specific cancer prognosis determination

Salivary cytokine panel indicative of non-small cell lung cancer.

Objective To develop a combinatorial panel of salivary cytokines that manifests the presence of non-small cell lung cancer (NSCLC) that will eventually improve prognosis by facilitating the early diagnosis and management of this common cancer. Methods We performed a case-control study comparing salivary cytokine profiles of 35 adult subjects with NSCLC with those of 35 matched, healthy nonsmokers. Multiplex bead array assays were used to quantify 27 cytokines in saliva, serum, and oral mucosal transudate samples. Logistic regression analysis was used to develop an informative cytokine panel. Receiver operating characteristic (ROC) curves were generated to evaluate the discriminant ability of the panel. Results A combinatorial 12-cytokine panel (interleukin receptor antagonist [IL1RN], IL1B, IL6, IL7, IL8, IL10, C-C motif chemokine ligand 11 [CCL11], tumor necrosis factor, C-X-C motif chemokine ligand 10 [CXCL10], C-C motif chemokine ligand 3, C-C motif chemokine ligand 4, and platelet-derived growth factor-BB) distinguished patients with NSCLC from healthy controls. Further, ROC analysis revealed that a cytokine panel comprising IL10 (odds ratio, 1.156) and CXCL10 (odds ratio, 1.000) discriminated NSCLC with a sensitivity of 60.6% and specificity of 80.8% (area under the ROC curve, 0.701). Conclusion A combinatorial panel of select salivary cytokines indicates the presence of NSCLC

Alterations of immune response of non-small lung cancer with azacytidine

Innovative therapies are needed for advanced Non-Small Cell Lung Cancer (NSCLC). We have undertaken a genomics based, hypothesis driving, approach to query an emerging potential that epigenetic therapy may sensitize to immune checkpoint therapy targeting PD-L1/PD-1 interaction. NSCLC cell lines were treated with the DNA hypomethylating agent azacytidine (AZA - Vidaza) and genes and pathways altered were mapped by genome-wide expression and DNA methylation analyses. AZA-induced pathways were analyzed in The Cancer Genome Atlas (TCGA) project by mapping the derived gene signatures in hundreds of lung adeno (LUAD) and squamous cell carcinoma (LUSC) samples. AZA up-regulates genes and pathways related to both innate and adaptive immunity and genes related to immune evasion in a several NSCLC lines. DNA hypermethylation and low expression of IRF7, an interferon transcription factor, tracks with this signature particularly in LUSC. In concert with these events, AZA up-regulates PD-L1 transcripts and protein, a key ligand-mediator of immune tolerance. Analysis of TCGA samples demonstrates that a significant proportion of primary NSCLC have low expression of AZA-induced immune genes, including PD-L1. We hypothesize that epigenetic therapy combined with blockade of immune checkpoints - in particular the PD-1/PD-L1 pathway - may augment response of NSCLC by shifting the balance between immune activation and immune inhibition, particularly in a subset of NSCLC with low expression of these pathways. Our studies define a biomarker strategy for response in a recently initiated trial to examine the potential of epigenetic therapy to sensitize patients with NSCLC to PD-1 immune checkpoint blockade

MYC is a metastasis gene for non-small-cell lung cancer.

Metastasis is a process by which cancer cells learn to form satellite tumors in distant organs and represents the principle cause of death of patients with solid tumors. NSCLC is the most lethal human cancer due to its high rate of metastasis. Lack of a suitable animal model has so far hampered analysis of metastatic progression. We have examined c-MYC for its ability to induce metastasis in a C-RAF-driven mouse model for non-small-cell lung cancer. c-MYC alone induced frank tumor growth only after long latency at which time secondary mutations in K-Ras or LKB1 were detected reminiscent of human NSCLC. Combination with C-RAF led to immediate acceleration of tumor growth, conversion to papillary epithelial cells and angiogenic switch induction. Moreover, addition of c-MYC was sufficient to induce macrometastasis in liver and lymph nodes with short latency associated with lineage switch events. Thus we have generated the first conditional model for metastasis of NSCLC and identified a gene, c-MYC that is able to orchestrate all steps of this process. Potential markers for detection of metastasis were identified and validated for diagnosis of human biopsies. These markers may represent targets for future therapeutic intervention as they include genes such as Gata4 that are exclusively expressed during lung development

Simulating non-small cell lung cancer with a multiscale agent-based model

Background The epidermal growth factor receptor (EGFR) is frequently overexpressed in many cancers, including non-small cell lung cancer (NSCLC). In silcio modeling is considered to be an increasingly promising tool to add useful insights into the dynamics of the EGFR signal transduction pathway. However, most of the previous modeling work focused on the molecular or the cellular level only, neglecting the crucial feedback between these scales as well as the interaction with the heterogeneous biochemical microenvironment. Results We developed a multiscale model for investigating expansion dynamics of NSCLC within a two-dimensional in silico microenvironment. At the molecular level, a specific EGFR-ERK intracellular signal transduction pathway was implemented. Dynamical alterations of these molecules were used to trigger phenotypic changes at the cellular level. Examining the relationship between extrinsic ligand concentrations, intrinsic molecular profiles and microscopic patterns, the results confirmed that increasing the amount of available growth factor leads to a spatially more aggressive cancer system. Moreover, for the cell closest to nutrient abundance, a phase-transition emerges where a minimal increase in extrinsic ligand abolishes the proliferative phenotype altogether. Conclusions Our in silico results indicate that, in NSCLC, in the presence of a strong extrinsic chemotactic stimulus, and depending on the cell's location, downstream EGFR-ERK signaling may be processed more efficiently, thereby yielding a migration-dominant cell phenotype and overall, an accelerated spatio-temporal expansion rate.Comment: 37 pages, 7 figure

Significance of KRAS/PAK1/Crk pathway in non-small cell lung cancer oncogenesis.

BackgroundKey effector(s) of mutated KRAS in lung cancer progression and metastasis are unknown. Here we investigated the role of PAK1/Crk axis in transduction of the oncogenic KRAS signal in non-small cell lung cancer (NSCLC).MethodsWe used NSCLC clinical specimens to examine the correlation among KRAS mutations (codon 12, 13 and 61); PAK1/Crk axis activation [p-PAK1(Thr423), p-Crk(Ser41)]; and adhesion molecules expression by immunohistochemistry. For assessing the role of proto-oncogene c-Crk as a KRAS effector, we inhibited KRAS in NSCLC cells by a combination of farnesyltransferase inhibitor (FTI) and geranylgeranyltransferase inhibitor (GGTI) and measured p-Crk-II(Ser41) by western blotting. Finally, we disrupted the signaling network downstream of KRAS by blocking KRAS/PAK1/Crk axis with PAK1 inhibitors (i.e., IPA-3, FRAX597 or FRAX1036) along with partial inhibition of all other KRAS effectors by prenylation inhibitors (FTI + GGTI) and examined the motility, morphology and proliferation of the NSCLC cells.ResultsImmunohistochemical analysis demonstrated an inverse correlation between PAK1/Crk phosphorylation and E-cadherin/p120-catenin expression. Furthermore, KRAS mutant tumors expressed higher p-PAK1(Thr423) compared to KRAS wild type. KRAS prenylation inhibition by (FTI + GGTI) completely dephosphorylated proto-oncogene c-Crk on Serine 41 while Crk phosphorylation did not change by individual prenylation inhibitors or diluent. Combination of PAK1 inhibition and partial inhibition of all other KRAS effectors by (FTI + GGTI) dramatically altered morphology, motility and proliferation of H157 and A549 cells.ConclusionsOur data provide evidence that proto-oncogene c-Crk is operative downstream of KRAS in NSCLC. Previously we demonstrated that Crk receives oncogenic signals from PAK1. These data in conjunction with the work of others that have specified the role of PAK1 in transduction of KRAS signal bring forward the importance of KRAS/PAK1/Crk axis as a prominent pathway in the oncogenesis of KRAS mutant lung cancer

The Diagnostic Accuracy of Chest CT in the Detection of Tumor and Nodal Status in Non Small Cell Lung Carcinoma

At this time there is an increasing demand for an accurate pre operative staging in non small cell lung cancer. Chest Computed Tomography (CT) is one of the imaging modality of choice used for this purpose. This study evaluated the accuracy of the chest CT to determine the status of the tumor and nodules in non small cell lung cancer. During the years 1998 and 1999, a descriptive prospective study of 32 patients undergoing a contrast enhanced chest CT examination for non small cell lung cancer, stage I-IIIA, was conducted. Lobectomy, lymph nodes dissection and postoperative histo-pathological examination were done. CT findings were as follows: a sensitivity of 100%, a specificity of 25% and an accuracy of 60% in the detection of the nodule stage were found. In 17 patients with adenocarcinoma, the sensitivity, the specificity and the accuracy were 86.6%, 100% and 88.2% respectively. The diagnosis of all patients was confirmed histo-pathologically. Six patients with T2 and 26 patients with T3 were detected by chest CT; the accuracy of the tumor status was 93.7%, confirmed by surgical and histo-pathological examinations. It was concluded that the CT played an important role in determining the clinical stage of non small cell lung cancer. The specificity and accuracy were higher in adeno-carcinoma as compared with squamous cell carcinoma in detecting the nodal status