CKAP2L Promotes Non-Small Cell Lung Cancer Progression through Regulation of Transcription Elongation

Human CKAP2L shows a cell cycle-dependent expression pattern and exhibits microtubule-stabilizing properties

Cytoskeleton-associated protein 2-like (CKAP2L) is a paralogue of cytoskeleton-associated protein 2 (CKAP2). We characterized the expression pattern, subcellular localization, and microtubule-stabilizing properties of human CKAP2L. The levels of both CKAP2L transcript and protein were cell cycle phase-dependent, peaking during the G2/M phase and relatively high in certain human tissues, including testis, intestine, and spleen. CKAP2L protein was detectable in all human cancer cell lines we tested. CKAP2L localized to the mitotic spindle apparatus during mitosis, as reported previously. During interphase, however, CKAP2L localized mainly to the nucleus. Ectopic overexpression of CKAP2L resulted in 'microtubule bundling', and, consequently, an elevated CKAP2L level led to prolonged mitosis. These findings support the mitotic role of CKAP2L during the human cell cycle.

BUB1/KIF14 complex promotes anaplastic thyroid carcinoma progression by inducing chromosome instability

Chromosome instability (CIN) is a common contributor driving the formation and progression of anaplastic thyroid cancer (ATC), but its mechanism remains unclear. The BUB1 mitotic checkpoint serine/threonine kinase (BUB1) is responsible for the alignment of mitotic chromosomes, which has not been thoroughly studied in ATC. Our research demonstrated that BUB1 was remarkably upregulated and closely related to worse progression-free survival. Knockdown of BUB1 attenuated cell viability, invasion, migration and induced cell cycle arrests, whereas overexpression of BUB1 promoted the cell cycle progression of papillary thyroid cancer cells. BUB1 knockdown remarkably repressed tumour growth and tumour formation of nude mice with ATC xenografts and suppressed tumour metastasis in a zebrafish xenograft model. Inhibition of BUB1 by its inhibitor BAY-1816032 also exhibited considerable anti-tumour activity. Further studies showed that enforced expression of BUB1 evoked CIN in ATC cells. BUB1 induced CIN through phosphorylation of KIF14 at serine1292 (Ser1292 ). Overexpression of the KIF14ΔSer1292 mutant was unable to facilitate the aggressiveness of ATC cells when compared with that of the wild type. Collectively, these findings demonstrate that the BUB1/KIF14 complex drives the aggressiveness of ATC by inducing CIN.

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning

BACKGROUND AND OBJECTIVE

The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers responsible for the heterogeneity aid in distinguishing NSCLC into its prominent subtypes-adenocarcinoma and squamous cell carcinoma. Moreover, if identified, these biomarkers could pave the path to targeted therapy. Through this work, a novel explainable AI (XAI)-guided deep learning framework is proposed that assists in discovering a set of significant NSCLC-relevant biomarkers using methylation data.

METHODS

The proposed framework is divided into two blocks- the first block combines an autoencoder and a neural network to classify NSCLC instances. The second block utilizes various eXplainable AI (XAI) methods, namely IntegratedGradients, GradientSHAP, and DeepLIFT, to discover a set of seven significant biomarkers.

RESULTS

The classification performance of the biomarkers discovered using the proposed framework is evaluated by employing multiple machine learning algorithms, among which the Multilayer Perceptron (MLP) algorithm-based model outperforms others, yielding a 10-fold cross-validation accuracy of 91.53%. An improved accuracy of 96.37% is achieved by integrating RNA-Seq, CNV, and methylation data. On performing statistical analysis using the Friedman and Nemenyi tests, the MLP model is found to be significantly better than other machine learning-based models. Further, the clinical efficacy of the resultant biomarkers is established based on their potential druggability, the likelihood of predicting NSCLC patients' survival, gene-disease association, and biological pathways targeted by them. While the biomarkers C18orf18, CCNT2, THOP1, and TNPO2, are found potentially druggable, the biomarkers CCDC15, SNORA9, THOP1, and TNPO2 are found prognostically relevant. On further analysis, some of the discovered biomarkers are found to be associated with around 104 diseases. Moreover, five KEGG, ten Reactome, and three Wiki pathways are found to be triggered by the biomarkers discovered.

CONCLUSION

In summary, the proposed framework uncovers a set of clinically effective biomarkers that accurately classify NSCLC. As a future course of work, efforts would be made to combine a variety of omics data with histopathological data to unveil more precise biomarkers for devising personalized therapy.

IGF2BP2 promotes ovarian cancer growth and metastasis by upregulating CKAP2L protein expression in an m6 A-dependent manner

Ovarian cancer (OC) is the second leading cause of gynecological cancer-related death in women worldwide. N6-methyladenosine (m6 A) is the most abundant internal modification in eukaryotic RNA. Human insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), an m6 A reader, can enhance mRNA stability and promote translation by recognizing m6 A modifications. Its tumor-promoting effects have been demonstrated in several cancers. However, the roles of m6 A modification and IGF2BP2 in OC remain unclear. Here, by using methylated RNA immunoprecipitation sequencing, we demonstrated that there is widespread dysregulation of m6 A modification in OC tissues. The m6 A modification and the mRNA and protein levels of IGF2BP2 were significantly elevated in OC. Overexpression of IGF2BP2 facilitated OC cell proliferation, migration, and invasion in vitro and accelerated tumor growth and metastasis in vivo. While IGF2BP2-knockdown showed the opposite effect. Mechanistically, we identified cytoskeleton-associated protein 2-like (CKAP2L) as a target of IGF2BP2. IGF2BP2 promoted CKAP2L translation dependent on m6 A modification, rather than affecting mRNA and protein stability. Overexpression of CKAP2L rescued the tumor-suppressive effect of IGF2BP2 knockdown in OC cells. In conclusion, this study revealed the potential role of IGF2BP2 in tumor progression, at least partially via promoting the translation of CKAP2L in an m6 A-dependent manner.

RB1 aberrations predict outcomes of immune checkpoint inhibitor combination therapy in NSCLC

Introduction

Immune checkpoint inhibitors (ICI) have changed the treatment of non-small cell lung cancer (NSCLC). Furthermore, compared with monotherapy, ICI combination therapy had better efficacy and partly different mechanism. Therefore, we aim to investigate and improve biomarkers specialized for ICI combination therapy.

Methods

We enrolled 53 NSCLC patients treated with ICI combination therapy and collected their tissue and plasma samples to perform next-generation sequencing (NGS) with a 425-gene panel.

Results

The line of treatment was the only clinical factor significantly affecting objective response rate (ORR) and progression-free survival (PFS). Surprisingly, classical markers PD-L1 and TMB only had limited predictive values in the ICI combination therapy. Instead, we found RB1 mutation was significantly associated with prognosis. Patients with mutated RB1 had shorter PFS than those with wild RB1 (134d vs 219d, p=0.018). Subsequent analysis showed the RB1 related mutated cell cycle and chromosomal instability were also deleterious to prognosis (103d vs 411d, p<0.001; 138d vs 505d, p=0.018). Additionally, patients with more circulating tumor DNA (ctDNA) had significantly shorter PFS (41d vs 194d, p=0.0043).

Conclusion

This study identified that NSCLC patients with mutated RB1 were less sensitive to ICI combination therapy. RB1 mutations and following cell cycle abnormalities and chromosomal instability can potentially guide clinical management.

Pan-cancer analysis reveals the prognostic and immunotherapeutic value of cytoskeleton-associated protein 2-like

Cytoskeleton-associated protein 2-like (CKAP2L), a cell cycle-related protein, is correlated to tumor progression in some tumors. But there were no pan-cancer studies on CKAP2L, and its role in cancer immunotherapy is also unclear. The expression levels, expression activity, genomic alterations, DNA methylation and functions of CKAP2L in various tumors, as well as the associations between CKAP2L expression and patient prognosis, chemotherapy sensitivity, and tumor immune microenvironment, were all analyzed in a comprehensive pan-cancer analysis of CKAP2L by various databases, analysis websites, and R software. The experiments were also conducted to verify the analysis results. In the majority of cancers, CKAP2L expression and activity were markedly elevated. Elevated CKAP2L expression led to poor prognostic outcomes in patients, and is an independent risk factor for most tumors. Elevated CKAP2L causes decreased sensitivity to chemotherapeutic agents. Knockdown of CKAP2L significantly inhibited the proliferation and metastasis capacity of the KIRC cell lines and resulted in cell cycle G2/M arrest. In addition, CKAP2L was closely related to immune subtypes, immune cell infiltration, immunomodulators and immunotherapy markers (TMB, MSI), patients with high CKAP2L expression were more sensitive to immunotherapy in the IMvigor210 cohort. The results indicate that CKAP2L is a pro-cancer gene that serves as a potential biomarker for predicting patient outcomes. By inducing cells to transition from the G2 phase to the M phase, CKAP2L may promote cell proliferation and metastasis. Furthermore, CKAP2L is closely related to the tumor immune microenvironment and can be used as a biomarker to predict tumor immunotherapy.

Prognostic significance of CKAP2L expression in patients with clear cell renal cell carcinoma

Background: Cytoskeleton-associated protein 2-like protein (CKAP2L) is thought to promote the progression of glioma, breast cancer, and ovarian cancer. However, the role of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma (ccRCC) is still unclear. The study aimed to investigate the roles and mechanisms of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma. Methods: The level of cytoskeleton-associated protein 2-like protein in tumors was explored by using UALCAN and Oncomine databases. Gene expression datasets of clear cell renal cell carcinoma from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) were also used to validate the cytoskeleton-associated protein 2-like protein level in clear cell renal cell carcinoma. Survival analysis was performed to investigate the relationship between cytoskeleton-associated protein 2-like protein level and prognosis of clear cell renal cell carcinoma patients. Cox regression analysis was used for identifying the independent prognostic factors. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), protein-protein interaction analysis, co-expression analysis, and immune infiltration analysis were used to explore the potential mechanisms of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma. Moreover, the levels of cytoskeleton-associated protein 2-like protein in clinical clear cell renal cell carcinoma tissues were also measured using RT-PCR, immunohistochemical analysis, and Western blotting. M1 macrophages and CD4⁺ T cells were also detected by immunohistochemistry between tumor and normal tissues. Results: The level of cytoskeleton-associated protein 2-like protein was upregulated in clear cell renal cell carcinoma according to multiple databases and experimental verification. Upregulated cytoskeleton-associated protein 2-like protein is an independent prognostic factor, which might activate the JAK-STAT signaling pathway, the P53 signaling pathway, the TGF-β signaling pathway, the WNT signaling pathway, etc., in clear cell renal cell carcinoma. Protein-protein interaction analysis and co-expression analysis suggest that cytoskeleton-associated protein 2-like protein might interact with some proliferation proteins. Immune infiltration analysis indicates that cytoskeleton-associated protein 2-like protein may affect the level of activated CD4⁺ memory T cells, M1 macrophages, CD8⁺ T cells, and neutrophils in clear cell renal cell carcinoma. More M1 macrophage infiltrations in tumor tissues with higher cytoskeleton-associated protein 2-like protein were validated by clear cell renal cell carcinoma tumor tissues. Conclusion: Cytoskeleton-associated protein 2-like protein is upregulated in clear cell renal cell carcinoma tissues, which may promote progression of the disease. Cytoskeleton-associated protein 2-like protein is a potential target for prognostic markers and a potential treatment target in clear cell renal cell carcinoma.

High expression of KNL1 in prostate adenocarcinoma is associated with poor prognosis and immune infiltration

Prostate adenocarcinoma (PRAD) is a common malignancy with increasing morbidity and mortality. Kinetochore scaffold 1 (KNL1) has been reported to be involved in tumor progression and prognosis in other tumors, but its role in PRAD has not been reported in detail. KNL1 expression analysis, clinicopathological parameters analysis, prognostic correlation analysis, molecular interaction network and functional abdominal muscle analysis and immune infiltration analysis by using multiple online databases and downloaded expression profile. The results suggest that KNL1 is highly expressed in PRAD, which is associated with worse prognosis in PRAD patients. KnL1-related genes are highly enriched in mitotic function, which is considered to be highly related to the development of cancer. Finally, KNL1 expression is associated with a variety of tumor infiltrating immune cells, especially Treg and Th2 cells. In conclusion, our findings provide preliminary evidence that KNL1 may be an independent prognostic predictor of PRAD and is associated with immune infiltration.

The genomic response of human granulosa cells (KGN) to melatonin and specific agonists/antagonists to the melatonin receptors

Melatonin is a known modulator of follicle development; it acts through several molecular cascades via binding to its two specific receptors MT1 and MT2. Even though it is believed that melatonin can modulate granulosa cell (GC) functions, there is still limited knowledge of how it can act in human GC through MT1 and MT2 and which one is more implicated in the effects of melatonin on the metabolic processes in the dominant follicle. To better characterize the roles of these receptors on the effects of melatonin on follicular development, human granulosa-like tumor cells (KGN) were treated with specific melatonin receptor agonists and antagonists, and gene expression was analyzed with RNA-seq technology. Following appropriate normalization and the application of a fold change cut-off of 1.5 (FC 1.5, p ≤ 0.05) for each treatment, lists of the principal differentially expressed genes (DEGs) are generated. Analysis of major upstream regulators suggested that the MT1 receptor may be involved in the melatonin antiproliferative effect by reprogramming the metabolism of human GC by activating the PKB signaling pathway. Our data suggest that melatonin may act complementary through both MT1 and MT2 receptors to modulate human GC steroidogenesis, proliferation, and differentiation. However, MT2 receptors may be the ones implicated in transducing the effects of melatonin on the prevention of GC luteinization and follicle atresia at the antral follicular stage through stimulating the PKA pathway.

CKAP2L, a crucial target of miR-326, promotes prostate cancer progression

Background

The overexpression of aberrant cell cycle signaling pathway associated protein has been implicated in multiple malignancies and the identification of all-important one among is the crux of the precise targeted therapy. CKAP2L (Cytoskeleton Associated Protein 2 Like) plays a newish role in cancer progression through activation of the process of cell cycle and mitosis. In this study, we aim to delineate the prominent dysregulated expression of CKAP2L and comprehensively reveal its deregulation in prostate cancer. 

Method

CKAP2L expression was examined in the normal and tumor tissues of prostate cancer patients with RT-QPCR and Western blot. IHC showed the different expression in normal prostate tissue, tissue of BPH, low Gleason Score and high Gleason Score prostate cancer patients. Transwell, colony formation, MTT and flow cytometry were performed to detected the changes in cellular function in vitro. The xenograft model was conducted for the changes in vivo. Dual luciferase and RIP proved the binding relation between CKAP2L and miR-326.

Results

In multiple datasets, CKAP2L was found upregulated and positively associated with Gleason grade and poor clinical outcomes of patients. shRNA mediated silence of CKAP2L suppressed cell proliferation, impaired monolayer formation, inhibited cell invasion. CKAP2L was confirmed to be the direct target of miR-326, which had a carcinostatic effect by binding the 3’untranslated regions (3’UTRs) of CKAP2L mRNA. The deletion of CKAP2L resulted in reduced expression of genes involved in the mitotic cell cycle such as multiple cyclin-dependent kinases and cyclins, but also several genes encoding proteins involved in chromosome segregation and spindle assembly.

Conclusion

Taken together, CKAP2L plays a carcinogenic role in prostate cancer by regulates the expression of cycle-associated proteins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09762-3.

Development of a Gene Risk Signature for Patients of Pancreatic Cancer

BACKGROUND

Pancreatic cancer is a highly malignant solid tumor with a high lethality rate, but there is a lack of clinical biomarkers that can assess patient prognosis to optimize treatment.

METHODS

Gene-expression datasets of pancreatic cancer tissues and normal pancreatic tissues were obtained from the GEO database, and differentially expressed genes analysis and WGCNA analysis were performed after merging and normalizing the datasets. Univariate Cox regression analysis and Lasso Cox regression analysis were used to screen the prognosis-related genes in the modules with the strongest association with pancreatic cancer and construct risk signatures. The performance of the risk signature was subsequently validated by Kaplan-Meier curves, receiver operating characteristic (ROC), and univariate and multivariate Cox analyses.

RESULT

A three-gene risk signature containing CDKN2A, BRCA1, and UBL3 was established. Based on KM curves, ROC curves, and univariate and multivariate Cox regression analyses in the TRAIN cohort and TEST cohort, it was suggested that the three-gene risk signature had better performance in predicting overall survival.

CONCLUSION

This study identifies a three-gene risk signature, constructs a nomogram that can be used to predict pancreatic cancer prognosis, and identifies pathways that may be associated with pancreatic cancer prognosis.