KIF20A silence inhibits the migration, invasion and proliferation of non-small cell lung cancer and regulates the JNK pathway

Berberine targets KIF20A and CCNE2 to inhibit the progression of nonsmall cell lung cancer via the PI3K/AKT pathway

BACKGROUND

Nonsmall cell lung cancer (NSCLC) is the main type of lung cancer, accounting for approximately 85%. Berberine (BBR), a commonly used traditional Chinese medicine, has been reported to exhibit a potential antitumor effect in various cancers. In this research, we explored the function of BBR and its underlying mechanisms in the development of NSCLC.

METHODS

Cell Counting Kit-8 (CCK-8), 5-ethynyl-20-deoxyuridine (EdU), colony formation assays, flow cytometry, and transwell invasion assay were employed to determine cell growth, the apoptotic rate, cell invasion of NSCLC cells, respectively. Western blot was applied for detecting the protein expression of c-Myc, matrix metalloprotease 9 (MMP9), kinesin family member 20A (KIF20A), cyclin E2 (CCNE2), and phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) pathway-related proteins. Glycolysis was evaluated by detecting glucose consumption, lactate production, and adenosine triphosphate/adenosine diphosphate (ATP/ADP) ratio with the matched kits. Real-time quantitative polymerase chain reaction (RT-qPCR) was conducted to analyze the level of KIF20A and CCNE2. Tumor model was established to evaluate the function of BBR on tumor growth in NSCLC in vivo. In addition, immunohistochemistry assay was employed to detect the level of KIF20A, CCNE2, c-Myc, and MMP9 in mice tissues.

RESULTS

BBR exhibited suppressive effects on the progression of NSCLC, as evidenced by inhibiting cell growth, invasion, glycolysis, and facilitating cell apoptosis in H1299 and A549 cells. KIF20A and CCNE2 were upregulated in NSCLC tissues and cells. Moreover, BBR treatment significantly decreased the expression of KIF20A and CCNE2. KIF20A or CCNE2 downregulation could repress cell proliferation, invasion, glycolysis, and induce cell apoptosis in both H1299 and A549 cells. The inhibition effects of BBR treatment on cell proliferation, invasion, glycolysis, and promotion effect on cell apoptosis were rescued by KIF20A or CCNE2 overexpression in NSCLC cells. The inactivation of PI3K/AKT pathway caused by BBR treatment in H1299 and A549 cells was restored by KIF20A or CCNE2 upregulation. In vivo experiments also demonstrated that BBR treatment could repress tumor growth by regulating KIF20A and CCNE2 and inactivating the PI3K/AKT pathway.

CONCLUSION

BBR treatment showed the suppressive impact on the progression of NSCLC by targeting KIF20A and CCNE2, thereby inhibiting the activation of the PI3K/AKT pathway.

Identification of the prognostic biomarkers and their correlations with immune infiltration in colorectal cancer through bioinformatics analysis and in vitro experiments

Colorectal cancer (CRC) is the third most diagnosed malignancy and the second leading cause of cancer death. The objective was to identify novel hub genes that were helpful for prognosis and targeted therapy in CRC. GSE23878, GSE24514, GSE41657, GSE81582 were filtered from the gene expression omnibus (GEO). Differentially expressed genes (DEGs) were identified through GEO2R, which were enriched in the GO term and KEGG pathway in DAVID. PPI network was constructed and analyzed using STRING and hub genes were screened out. The relationships between hub genes and prognoses in CRC were evaluated in GEPIA based on the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx). The transcription factors and miRNA-mRNA interaction networks for hub genes were performed using miRnet and miRTarBase. The relationship between hub genes and tumor-infiltrating lymphocytes were analyzed in TIMER. The protein levels of hub genes were identified in HPA. The expression levels of hub gene in CRC and its effect on the biological effect of CRC cells were identified in vitro. As hub genes, the mRNA levels of BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were highly expressed in CRC and had excellent prognostic value. The BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were closely associated with transcription factors, miRNAs, tumor-infiltrating lymphocytes, suggesting their involvement in the regulation of CRC. BIRC5 highly expressed in CRC tissues and cells, and promoted the proliferation, migration, and invasion of CRC cells. BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 are hub genes that serve as promising prognostic biomarkers in CRC. BIRC5 plays an important role in the development and progression of CRC.

KIF20A as a potential biomarker of renal and bladder cancers based on bioinformatics and experimental verification

BACKGROUND

Bladder cancer (BC) is a malignant tumor that occurs in the bladder wall and often appears in elderly individuals. Renal cancer (RC) arises from the renal tubular epithelium, but its molecular mechanism remains unclear.

METHODS

We downloaded RC datasets (GSE14762 and GSE53757) and a BC dataset (GSE121711) to screen differentially expressed genes (DEGs). We also performed weighted gene coexpression network analysis (WGCNA). We created a protein-protein interaction (PPI) network and performed functional enrichment analysis, such as gene set enrichment analysis (GSEA). Heatmaps were made for gene expression. Survival analysis and immunoinfiltration analysis were performed. Comparative toxicogenomics database (CTD) analysis was performed to find the relationship between disease and hub genes. Western blotting was performed to verify the role of KIF20A in apoptosis.

RESULTS

A total of 764 DEGs were identified. The GSEA showed that the DEGs were mainly enriched in organic acid metabolism, drug metabolism, mitochondria, and metabolism of cysteine and methionine. The PPI network in GSE121711 showed that KIF20A was a hub gene of renal clear cell carcinoma. Where the expression level of KIF20A was higher, the prognosis of patients was worse. CTD analysis showed that KIF20A was associated with inflammation, proliferation, and apoptosis. KIF20A expression in the RC group was upregulated, as shown by western blotting. The core proteins (including pRB Ser 780, CyclinA, E2F1, CCNE1, and CCNE2) in the pRB Ser 780/CyclinA signaling pathway were also upregulated in the RC group.

CONCLUSIONS

KIF20A might be a novel biomarker for researching renal and bladder cancers.

Discovery of BAR502, as potent steroidal antagonist of leukemia inhibitory factor receptor for the treatment of pancreatic adenocarcinoma

Introduction

The leukemia inhibitory factor (LIF), is a cytokine belonging to IL-6 family, whose overexpression correlate with poor prognosis in cancer patients, including pancreatic ductal adenocarcinoma (PDAC). LIF signaling is mediate by its binding to the heterodimeric LIF receptor (LIFR) complex formed by the LIFR receptor and Gp130, leading to JAK1/STAT3 activation. Bile acids are steroid that modulates the expression/activity of membrane and nuclear receptors, including the Farnesoid-X-Receptor (FXR) and G Protein Bile Acid Activated Receptor (GPBAR1).

Methods

Herein we have investigated whether ligands to FXR and GPBAR1 modulate LIF/LIFR pathway in PDAC cells and whether these receptors are expressed in human neoplastic tissues.

Results

The transcriptome analysis of a cohort of PDCA patients revealed that expression of LIF and LIFR is increased in the neoplastic tissue in comparison to paired non-neoplastic tissues. By in vitro assay we found that both primary and secondary bile acids exert a weak antagonistic effect on LIF/LIFR signaling. In contrast, BAR502 a non-bile acid steroidal dual FXR and GPBAR1 ligand, potently inhibits binding of LIF to LIFR with an IC50 of 3.8 µM.

Discussion

BAR502 reverses the pattern LIF-induced in a FXR and GPBAR1 independent manner, suggesting a potential role for BAR502 in the treatment of LIFR overexpressing-PDAC.

Mir-153-3p Modulates the Breast Cancer Cells’ Chemosensitivity to Doxorubicin by Targeting KIF20A

Breast cancer is considered the solid tumor most sensitive to chemotherapy. However, it can become resistant to various chemotherapeutic drugs, including doxorubicin, which triggers cell death by intercalation between DNA bases, free radical formation, and topoisomerase II inhibition. When drug resistance develops, several miRNAs are dysregulated, suggesting that miRNAs may play a significant role in resistance formation. In the current study, we investigated how doxorubicin sensitivity of breast cancer cells is affected by miR-153-3p and its target gene. The MTT method was used to determine the chemo-sensitizing effect of miR-153-3p on doxorubicin in MCF-7 and MDA-MB-231 cell lines. Results of Western blot and dual luciferase confirmed that miR-153-3p targets KIF20A and decreases its expression. Transwell and flow cytometry experiments showed that miR-153-3p and doxorubicin together had higher effects on MCF-7 and MDA-MB-231 cell proliferation, migration, and invasion, as well as increasing apoptosis and arresting cells in the G1 phase. Proteins related to apoptosis and the cell cycle exhibited the same tendency. Intracellular vesicle formation was inhibited and RAB26 was also downregulated by treatment with miR-153-3p alone or in combination with doxorubicin. Doxorubicin’s ability to suppress tumors may be enhanced by miR-153-3p, according to in vivo studies. According to our findings, miR-153-3p has a direct effect on KIF20A and may regulate the formation of intracellular vesicles, which in turn makes breast cancer cells more susceptible to doxorubicin.

High expression of KIF20A in bladder cancer as a potential prognostic target for poor survival of renal cell carcinoma

Urinary system tumors are malignant tumors, including renal cancer and bladder cancer. however, molecular target of them remains unclear. GSE14762 and GSE53757 were downloaded from GEO database to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes were used for enrichment analysis. Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed on whole genome, as formulated by gene set enrichment analysis. Survival analysis was also performed. Comparative toxicogenomics database was used to identify diseases most associated with hub genes. A total of 1517 DEGs were identified. DEGs were mainly enriched in cancer pathway, HIF-1 signaling pathway, organic acid metabolism, glyoxylate and dicarboxylate metabolism, and protein homodimerization activity. Ten hub genes (TPX2, ASPM, NUSAP1, RAD51AP1, CCNA2, TTK, PBK, MELK, DTL, kinesin family member 20A [KIF20A]) were obtained, which were up-regulated in tumor tissue. The expression of KIF20A was related with the overall survival of renal and bladder cancer. KIF20A was up-regulated in the tumor tissue, and might worsen the overall survival of bladder and kidney cancer. KIF20A could be a novel biomarker of bladder and kidney cancer.

An evaluation of KIF20A as a prognostic factor and therapeutic target for lung adenocarcinoma using integrated bioinformatics analysis

The identification of prognostic and therapeutic biomarkers is essential to reduce morbidity and mortality from lung adenocarcinoma (LUAD). This study aimed to identify a reliable prognostic and therapeutic biomarker for LUAD using integrated bioinformatics. Based on the cancer genome atlas (TCGA) and genome-tissue expression (GTEx) analyses, KIF20A has been identified as the hub gene. Following validation using a series of cohorts, survival analysis, meta-analysis, and univariate Cox analysis was conducted. ESTIMATE and CIBERSORT algorithms were then used to study the association of KIF20A with the tumor microenvironment (TME) and the percentage of tumor-infiltrating immune cells (TICs). In vitro experiments were conducted to determine the function of KIF20A. Finally, there was a negative association between the expression of the KIF20A and overall survival, progression-free survival, and disease-free survival, which was confirmed by meta-analysis and COX analysis. Furthermore, KIF20A also had a potential role of altering the TME and TICs proportions in LUAD. Validations in vitro were performed on A549 and PC-9 cell lines, and we found that the knockdown of KIF20A exhibited inhibitory effects on cell proliferation, resulted in cell cycle arrest during the G2/M phase, and induced cellular apoptosis. Our study demonstrated that KIF20A could be utilized as a reliable prognostic marker and treatment target for LUAD. However, further studies are required to validate these findings.

KIF20A is associated with clinical prognosis and synergistic effect of gemcitabine combined with ferroptosis inducer in lung adenocarcinoma

Gemcitabine (GEM), an antimetabolite that terminates DNA synthesis, is commonly used in the treatment of cancers including lung adenocarcinoma (LUAD). However, downregulation of sensitivity limits the therapeutic effect. Ferroptosis as the new form of regulated cell death has been shown to have great potential for cancer treatment with chemoresistance. Here, three genes with both ferroptosis and GEM-response-associated features were screened from RNA sequencing and public data for constructing an independent risk model. LUAD patients with different risk scores had differences in mutational landscape, gene enrichment pathways, and drug sensitivity. By Cell Counting Kit-8 assay, flow cytometry, and colony forming assay, we demonstrate that GEM and ferroptosis inducer (FIN) imidazole Ketone Erastin had a synergistic combined anti-proliferative effect on LUAD cells and knockdown of KIF20A (the core gene of our model) further enhanced cell death in vitro by inducing ferroptosis. In conclusion, we identified a link between ferroptosis and GEM response in LUAD cells and developed a robust signature that can effectively classify LUAD patients into subgroups with different overall survival. For LUAD, the combined treatment modality of GEM and FIN is potentially effective and KIF20A may be a new therapeutic target.

Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma Progression

Medulloblastoma is the neuroepithelial tumor with the highest degree of malignancy in the central nervous system, accounting for about 8% to 10% of children’s brain tumors. It has a high degree of malignancy and is easily transmitted through cerebrospinal fluid, with a relatively poor prognosis. Although medulloblastoma has been widely studied and treated, its molecular mechanism remains unclear. To determine which gene plays a crucial role in medulloblastoma development and progression, we analyzed three microarray datasets from Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to detect and evaluate differentially expressed genes. Protein interaction network was established, and the hub genes were determined in cytoHubba through various assessment methods, while the target genes were screened out using survival analysis. Ultimately, human medulloblastoma samples were utilized to confirm target gene expression. In conclusion, This study found that aurora kinase A (AURKA) and kinesin family member 20A (KIF20A) may be involved in the initiation and development of medulloblastoma, have a close association with prognosis, and may become a potential therapeutic target and prognostic marker of MED.

Identifying Mitotic Kinesins as Potential Prognostic Biomarkers in Ovarian Cancer Using Bioinformatic Analyses

Ovarian cancer (OC) is characterized by late-stage presentation, chemoresistance, and poor survival. Evaluating the prognosis of OC patients via effective biomarkers is essential to manage OC progression and to improve survival; however, it has been barely established. Here, we intend to identify differentially expressed genes (DEGs) as potential prognostic biomarkers of OC via bioinformatic analyses. Initially, a total of thirteen DEGs were extracted from different public databases as candidates. The expression of KIF20A, one of the DEGs, was correlated with a worse outcome of OC patients. The functional correlation of the DEGs with mitosis and the prognostic value of KIF20A imply a high correlation between mitotic kinesins (KIFs) and OC development. Finally, we found that KIF20A, together with the other nine mitotic KIFs (4A, 11, 14, 15, 18A, 18B, 23, C1, and2C) were upregulated and activated in OC tissues. Among the ten, seven overexpressed mitotic KIFs (11, 14, 18B, 20A, 23, and C1) were correlated with unfavorable clinical prognosis. Moreover, KIF20A and KIF23 overexpression was associated with worse prognosis in OC patients treated with platinum/taxol chemotherapy, while OCs overexpressing mitotic KIFs (11, 15, 18B, and C1) were resistant to MAPK pathway inhibitors. In conclusion, worse outcomes of OC patients were correlated with overexpression of several mitotic KIFs, which may serve both as prognostic biomarkers and therapeutic targets for OC.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

Low expression of KIF20A suppresses cell proliferation, promotes chemosensitivity and is associated with better prognosis in HCC

This study analysed the microarray datasets from Gene Expression Omnibus (GEO) database, and aimed to identify novel potential hub genes associated with the progression of HCC via bioinformatics analysis and experimental validation. The common differentially expressed genes (DEGs) from five GEO datasets were screened using GEO2R tool. The expression and survival analysis of hub genes in HCC were performed using Gene Expression Profiling Interactive Analysis, UALCAN and Kaplan-Meier plotter tools. In vitro functional assays were used to determine the caspase-3, -9, cell proliferation and chemo-sensitivity of HCC cells. A total of 177 common DEGs were identified between normal liver and HCC tissues among these datasets. Functional enrichment and PPI network analysis identified 22 hub genes from the common DEGs. The mRNA expression of 22 hub genes was all significantly up-regulated in HCC tissues compared to that in normal liver tissues. Further survival analysis showed that 10 hub genes predicted poor prognosis of patients with HCC. More importantly, the in vitro functional studies demonstrated that KIF20A knockdown suppressed the HCC cell proliferation and promoted the chemosensitivity of HCC cells to cisplatin and sorafenib. In conclusion, the present study identified a total of 177 common DEGs among 5 GEO microarray datasets and found that 10 hub genes could predict the poor prognosis of patients with HCC using the comprehensive bioinformatics analysis. Furthermore, KIF20A silence suppressed cell proliferation and enhanced chemosensitivity in HCC cells. Further studies may be required to determine the mechanistic role of these hub genes in HCC progression.

Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.

Methods

A comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan–Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.

Results

We identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.

Conclusion

This study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.

Integrative analysis of transcriptional profile reveals LINC00052 as a suppressor of breast cancer cell migration

BACKGROUND

Long-non-coding RNAs, a class of transcripts with lengths > 200 nt, play key roles in tumour progression. Previous reports revealed that LINC00052 (long intergenic non-coding RNA 00052) was strongly downregulated during breast cancer multicellular spheroids formation and suggested a role in cell migration and oxidative metabolism.

OBJECTIVE

To examine the function of LINC00052 in MCF-7 breast cancer cells.

METHODS

Loss-of-function studies were performed to evaluate LINC00052 role on MCF-7 breast cancer cells. Microarray expression assays were performed to determine genes and cellular functions modified after LINC00052 knockdown. Next, the impact of LINC00052 depletion on MCF-7 cell respiration and migration was evaluated.

RESULTS

1,081 genes were differentially expressed upon LINC00052 inhibition. Gene set enrichment analysis, Gene Ontology and Key Pathway Advisor analysis showed that signalling networks related to cell migration and oxidative phosphorylation were enriched. However, whereas LINC00052 knockdown in MCF-7 cells revealed marginal difference in oxygen consumption rates when compared with control cells, LINC00052 inhibition enhanced cell migration in vitro and in vivo, as observed using a Zebrafish embryo xenotransplant model.

CONCLUSION

Our data show that LINC00052 modulates MCF-7 cell migration. Genome-wide microarray experiments suggest that cancer cell migration is affected by LINC00052 through cytoskeleton modulation and Notch/β-catenin/NF-κB signalling pathways.

Suppressing the KIF20A/NUAK1/Nrf2/GPX4 signaling pathway induces ferroptosis and enhances the sensitivity of colorectal cancer to oxaliplatin

Oxaliplatin resistance can develop in colorectal cancer (CRC), which may involve inhibition of ferroptosis, although further research is needed to understand this potential mechanism. We evaluated CRC cells with acquired oxaliplatin resistance (HCT116-Or) or congenital resistance (H716) to determine whether a ferroptosis inducer (RSL3) or inhibitor (liproxstatin-1) could modulate the effects of oxaliplatin. The results suggested that induction of ferroptosis could significantly reverse the oxaliplatin resistance of the CRC cells. Bioinformatic and cytobiological searches also revealed that KIF20A was highly expressed in the oxaliplatin-resistant cell lines and was strongly correlated with survival among CRC patients. Silencing KIF20A enhanced cellular sensitivity to oxaliplatin both in vivo and in vitro, and silencing KIF20A also suppressed NUAK1 activation, while a NUAK1 agonist (ETC-1002) could reverse the oxaliplatin sensitivity of KIF20A-silenced cells. Moreover, silencing NUAK1 up-regulated the expression of PP1β, down-regulated the phosphorylation of downstream GSK3βSer9, suppressed the nuclear import of Nrf2, inhibited the expression of a ferroptosis key negative regulatory protein (GPX4), and blocked cellular resistance. Applying a Nrf2 agonist (oltipraz) also reversed the oxaliplatin sensitivity of NUAK1-silenced cells. Therefore, cellular ferroptosis may be inhibited via the KIF20A/NUAK1/PP1β/GPX4 pathway in CRC cells, which may underly the resistance of CRC to oxaliplatin.

Unravelling the Role of miR-20b-5p, CCNB1, HMGA2 and E2F7 in Development and Progression of Non-Small Cell Lung Cancer (NSCLC)

Lung cancer is a prime cause of worldwide cancer deaths, with non-small cell lung cancer (NSCLC) as a frequent subtype. Surgical resection, chemotherapy are the currently used treatment methods. Delayed detection, poor prognosis, tumor heterogeneity, and chemoresistance make them relatively ineffective. Genomic medicine is a budding aspect of cancer therapeutics, where miRNAs are impressively involved. miRNAs are short ncRNAs that bind to 3′UTR of target mRNA, causing its degradation or translational repression to regulate gene expression. This study aims to identify important miRNA-mRNA-TF interactions in NSCLC using bioinformatics analysis. GEO datasets containing mRNA expression data of NSCLC were used to determine differentially expressed genes (DEGs), and identification of hub genes-BIRC5, CCNB1, KIF11, KIF20A, and KIF4A (all functionally enriched in cell cycle). The FFL network involved, comprised of miR-20b-5p, CCNB1, HMGA2, and E2F7. KM survival analysis determines that these components may be effective prognostic biomarkers and would be a new contemplation in NSCLC therapeutics as they target cell cycle and immunosurveillance mechanisms via HMGA2 and E2F7. They provide survival advantage and evasion of host immune response (via downregulation of cytokines-IL6, IL1R1 and upregulation of chemokines-CXCL13, CXCL14) to NSCLC. The study has provided innovative targets, but further validation is needed to confirm the proposed mechanism.