Analysis of super-enhancer using machine learning and its application to medical biology.

The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.

Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets.

BACKGROUND: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days. METHODS: Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets. RESULTS: Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options. CONCLUSIONS: We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.

Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations.

BACKGROUND: In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD. METHODS: We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases. RESULTS: We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations. CONCLUSIONS: Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Histone methyltransferase SUV420H1/KMT5B contributes to poor prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has a high rate of recurrence and poor prognosis, even after curative surgery. Multikinase inhibitors have been applied for HCC patients, but their effect has been restricted. This study aims to clarify the clinical impact of SUV420H1/KMT5B, one of the methyltransferases for histone H4 at lysine 20, and elucidate the novel mechanisms of HCC progression. We retrospectively investigated SUV420H1 expression using HCC clinical tissue samples employing immunohistochemical analysis (n = 350). We then performed loss-of-function analysis of SUV420H1 with cell cycle analysis, migration assay, invasion assay and RNA sequence for Gene Ontology (GO) pathway analysis in vitro, and animal experiments with xenograft mice in vivo. The SUV420H1-high-score group (n = 154) had significantly poorer prognosis for both 5-year overall and 2-year/5-year disease-free survival than the SUV420H1-low-score group (n = 196) (p < 0.001 and p < 0.05, respectively). The SUV420H1-high-score group had pathologically larger tumor size, more tumors, poorer differentiation, and more positive vascular invasion than the SUV420H1-low-score group. Multivariate analysis demonstrated that SUV420H1 high score was the poorest independent factor for overall survival. SUV420H1 knockdown could suppress cell cycle from G1 to S phase and cell invasion. GO pathway analysis showed that SUV420H1 contributed to cell proliferation, cell invasion, and/or metastasis. Overexpression of SUV420H1 clinically contributed to poor prognosis in HCC, and the inhibition of SUV420H1 could repress tumor progression and invasion both in vitro and in vivo; thus, further analyses of SUV420H1 are necessary for the discovery of future molecularly targeted drugs.

Clinical features and impact of p53 status on sporadic mismatch repair deficiency and Lynch syndrome in uterine cancer.

The clinical features of sporadic mismatch repair deficiency (MMRd) and Lynch syndrome (LS) in Japanese patients with endometrial cancer (EC) were examined by evaluating the prevalence and prognostic factors of LS and sporadic MMRd in patients with EC. Targeted sequencing of five LS susceptibility genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) was carried out in 443 patients with EC who were pathologically diagnosed with EC at the National Cancer Center Hospital between 2011 and 2018. Pathogenic variants in these genes were detected in 16 patients (3.7%). Immunohistochemistry for MMR proteins was undertaken in 337 of the 433 (77.9%) EC patients, and 91 patients (27.0%) showed absent expression of at least one MMR protein. The 13 cases of LS with MMR protein loss (93.8%) showed a favorable prognosis with a 5-year overall survival (OS) rate of 100%, although there was no statistically significant difference between this group and the sporadic MMRd group (p = 0.27). In the MMRd without LS group, the 5-year OS rate was significantly worse in seven patients with an aberrant p53 expression pattern than in those with p53 WT (53.6% vs. 93.9%, log-rank test; p = 0.0016). These results suggest that p53 abnormalities and pathogenic germline variants in MMR genes could be potential biomarkers for the molecular classification of EC with MMRd.

Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine.

The increase in the expectations of artificial intelligence (AI) technology has led to machine learning technology being actively used in the medical field. Non-negative matrix factorization (NMF) is a machine learning technique used for image analysis, speech recognition, and language processing; recently, it is being applied to medical research. Precision medicine, wherein important information is extracted from large-scale medical data to provide optimal medical care for every individual, is considered important in medical policies globally, and the application of machine learning techniques to this end is being handled in several ways. NMF is also introduced differently because of the characteristics of its algorithms. In this review, the importance of NMF in the field of medicine, with a focus on the field of oncology, is described by explaining the mathematical science of NMF and the characteristics of the algorithm, providing examples of how NMF can be used to establish precision medicine, and presenting the challenges of NMF. Finally, the direction regarding the effective use of NMF in the field of oncology is also discussed.

Excellent concordance of the molecular classification between preoperative biopsy and final hysterectomy in endometrial carcinoma.

OBJECTIVE: The 2023 International Federation of Gynecology and Obstetrics classification with molecular classification shows superior discriminatory ability compared to staging systems lacking molecular data. However, the accuracy of endometrial biopsy data in molecular classification remains uncertain. This study aimed to assess the concordance of molecular classifications between preoperative biopsy and hysterectomy to predict prognosis before surgical staging. METHODS: Endometrial biopsies and corresponding hysterectomy specimens were collected at the National Cancer Center Hospital between 2012 and 2023. Immunohistochemistry for p53 and mismatch repair (MMR) proteins and next-generation sequencing of all exons of polymerase epsilon (POLE) were performed. Given the limited number of POLE mut cases in prior studies, we prepared a POLE mut-enriched cohort. Cohen's kappa estimates were used to determine concordance for molecular and clinicopathological subgroup assignments. RESULTS: Among 70 patients classified into four molecular subtype groups, 33 exhibited POLE mutations, 15 showed loss of MMR protein expression, 13 had p53-abnormality, and 9 had no specific molecular profile. Concordance between biopsy and hysterectomy specimens was 100% (κ = 1.000). In contrast, histological types and grades between biopsy and surgical specimens showed moderate and substantial agreement (κ = 0.420 and κ = 0.780, respectively). CONCLUSIONS: Molecular subtypes were completely consistent with those derived from surgical specimens, demonstrating high concordance between preoperative and postoperative molecular classifications. This suggests that endometrial biopsies could reliably predict prognosis. Future studies should investigate how biopsy-based molecular profiling influences treatment planning and patient outcomes.

Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.

In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive comparison of vision transformers (ViTs) and convolutional neural networks (CNNs), the two leading techniques in the field of deep learning in medical imaging. We conducted a survey systematically. Particular attention was given to the robustness, computational efficiency, scalability, and accuracy of these models in handling complex medical datasets. The review incorporates findings from 36 studies and indicates a collective trend that transformer-based models, particularly ViTs, exhibit significant potential in diverse medical imaging tasks, showcasing superior performance when contrasted with conventional CNN models. Additionally, it is evident that pre-training is important for transformer applications. We expect this work to help researchers and practitioners select the most appropriate model for specific medical image analysis tasks, accounting for the current state of the art and future trends in the field.

A comprehensive appraisal of HER2 heterogeneity in HER2-amplified and HER2-low colorectal cancer.

BACKGROUND: This study aimed to elucidate the clinicopathological and molecular features of HER2-amplified and HER2-low colorectal cancers (CRCs). We also characterised HER2 expression statuses in CRCs focusing on their intratumoral heterogeneity and alterations in metastatic lesions to establish practical HER2 status assessment. METHODS: We evaluated 1009 CRCs for HER2 expression and HER2 amplification by immunohistochemistry and FISH, respectively, and correlated the results to clinicopathological and molecular data. For HER2-positive tumours, HER2 expression in metastatic lesions was also assessed. RESULTS: Twenty-five HER2-amplified (2.5%) and 46 HER2-low tumours (4.6%) were identified. HER2-amplified tumours consistently lacked a mucinous component and HER2-low tumours tended to be in the right colon, but no other clinicopathological features were noted. KRAS, NRAS or BRAF mutations were detected in only two HER2-amplified tumours (8%), whereas 23 HER2-low tumours (50%) had one of these mutations. Most HER2-amplified and HER2-low tumours showed a homogeneous or mosaic HER2 expression pattern and a clustered heterogeneous expression pattern was rather rare. HER2 expression was maintained in most metastatic lesions in both HER2-amplified (93%) and HER2-low tumours (81%). CONCLUSIONS: These results suggest that biopsy-based assessment of primary lesions is appropriate for the identification of CRC patients eligible for systemic HER2-targeted therapy.

Utility of molecular subtypes and genetic alterations for evaluating clinical outcomes in 1029 patients with endometrial cancer.

BACKGROUND: We investigated the utility of a molecular classifier tool and genetic alterations for predicting prognosis in Japanese patients with endometrial cancer. METHODS: A total of 1029 patients with endometrial cancer from two independent cohorts were classified into four molecular subtype groups. The primary and secondary endpoints were relapse-free survival (RFS) and overall survival (OS), respectively. RESULTS: Among the 265 patients who underwent initial surgery, classified according to immunohistochemistry, patients with DNA polymerase epsilon exonuclease domain mutation had an excellent prognosis (RFS and OS), patients with no specific molecular profile (NSMP) and mismatch repair protein deficiency had an intermediate prognosis, and those with protein 53 abnormal expression (p53abn) had the worst prognosis (P < 0.001). In the NSMP group, mutant KRAS and wild-type ARID1A were associated with significantly poorer 5-year RFS (41.2%) than other genomic characteristics (P < 0.001). The distribution of the subtypes differed significantly between patients with recurrence/progression and classified by sequencing (n = 764) and patients who underwent initial surgery (P < 0.001). Among patients with recurrence/progression, 51.4% had the opportunity to receive molecular targeted therapy. CONCLUSIONS: A molecular classifier is a useful tool for determining prognosis and eligibility for molecularly targeted therapy in patients with endometrial cancer.

Tumor microenvironment-mediated immune profiles and efficacy of anti-PD-L1 antibody plus chemotherapy stratified by DLL3 expression in small-cell lung cancer.

BACKGROUND: Delta-like ligand 3 (DLL3) is a therapeutic target in small-cell lung cancer (SCLC). However, how DLL3 expression status affects the tumor microenvironment (TME) and clinical outcomes in SCLC remains unclear. METHODS: This retrospective study included patients with postoperative limited-stage (LS)-SCLC and extensive-stage (ES)-SCLC treated with platinum and etoposide (PE) plus anti-programmed cell death ligand 1 (PD-L1) antibody. We investigated the relationship of DLL3 expression with TME, mutation status, tumor neoantigens, and immunochemotherapy. RESULTS: In the LS-SCLC cohort (n = 59), whole-exome sequencing revealed that DLL3High cases had significantly more neoantigens (P = 0.004) and a significantly higher rate of the signature SBS4 associated with smoking (P = 0.02) than DLL3Low cases. Transcriptome analysis in the LS-SCLC cohort revealed that DLL3High cases had significantly suppressed immune-related pathways and dendritic cell (DC) function. SCLC with DLL3High had significantly lower proportions of T cells, macrophages, and DCs than those with DLL3Low. In the ES-SCLC cohort (n = 30), the progression-free survival associated with PE plus anti-PD-L1 antibody was significantly worse in DLL3High cases than in DLL3Low cases (4.7 vs. 7.4 months, P = 0.01). CONCLUSIONS: Although SCLC with DLL3High had a higher neoantigen load, these tumors were resistant to immunochemotherapy due to suppressed tumor immunity by inhibiting antigen-presenting functions.

Clinical impact of genetic alterations of CTNNB1 in patients with grade 3 endometrial endometrioid carcinoma.

To identify prognostic factors in patients with grade 3 (high-grade) endometrial endometrioid carcinoma, we evaluated the spectrum of genomic alterations and examined whether previously reported molecular subtypes of endometrial carcinoma were adapted to clinical outcome prediction. Seventy-five Japanese patients with grade 3 endometrial endometrioid carcinoma, who underwent a potentially curative resection procedure between 1997 and 2018 at the National Cancer Center Hospital, were included. We classified the patients into four risk groups of the disease based on the Proactive Molecular Risk Classifier for Endometrial Cancer. Genomic alterations in PTEN, ARID1A, TP53, and PIK3CA were detected in more than 30% of the patients. Overall survival and recurrence-free survival of patients with genomic alterations in CTNNB1 were poorer than those of patients with wild-type CTNNB1 (p = 0.006 and p = 0.004, respectively). Compared with that of alterations prevalent in Caucasians, the frequency of genomic alterations in POLE and TP53 was higher in our study than in The Cancer Genome Atlas dataset (p = 0.01 and p = 0.01, respectively). The tendency for recurrence-free survival in the POLE exonuclease domain mutation group was better than that in the TP53 mutation and mismatch repair-deficient groups (p = 0.08 and p = 0.07, respectively), consistent with the Proactive Molecular Risk Classifier for Endometrial Cancer risk classifier definition. The CTNNB1 mutation is a potential novel biomarker for the prognosis of patients with grade 3 endometrial endometrioid carcinoma, and prognosis classification using Proactive Molecular Risk Classifier for Endometrial Cancer may help screen Japanese patients with the disease.

Clinicopathological and molecular characteristics of RSPO fusion-positive colorectal cancer.

BACKGROUND: RSPO fusions that lead to WNT pathway activation are potential therapeutic targets in colorectal cancer (CRC), but their clinicopathological significance remains unclear. METHODS: We screened 1019 CRCs for RSPO fusions using multiplex reverse transcription-PCR. The RSPO fusion-positive tumours were subjected to whole-exome sequencing (WES). RESULTS: Our analysis identified 29 CRCs with RSPO fusions (2.8%), consisting of five with an EIF3E-RSPO2 fusion and 24 with PTPRK-RSPO3 fusions. The patients were 17 women and 12 men. Thirteen tumours (45%) were right-sided. Histologically, approximately half of the tumours (13/29, 45%) had a focal or extensive mucinous component that was significantly more frequent than the RSPO fusion-negative tumours (13%; P = 8.1 × 10-7). Four tumours (14%) were mismatch repair-deficient. WES identified KRAS, BRAF, and NRAS mutations in a total of 27 tumours (93%). In contrast, pathogenic mutations in major WNT pathway genes, such as APC, CTNNB1 and RNF43, were absent. RSPO fusion status did not have a statistically significant influence on the overall or recurrence-free survival. These clinicopathological and genetic features were also confirmed in a pooled analysis of previous studies. CONCLUSION: RSPO fusion-positive CRCs constitute a rare subgroup of CRCs with several characteristic clinicopathological and genetic features.

Epithelial Expression of YAP and TAZ Is Sequentially Required in Lung Development.

TAZ (transcriptional coactivator with PDZ-binding motif) and YAP (Yes-associated protein) are key molecules of the Hippo pathway. Recent studies revealed that these molecules are essential in lung development; however, the precise signaling cascade involving these molecules and the differences in their roles during lung development remain unknown. We aimed to investigate YAP and TAZ functions using lung epithelium-specific Taz and Yap conditional knockout mice. We generated lung epithelium-specific Taz and Yap conditional knockout mice and investigated the functions of YAP and TAZ in lung development. Selective TAZ deficiency in mouse lung epithelial cells resulted in abnormal alveolarization, which mimics lung emphysema, in adults, whereas YAP deficiency caused disruption of bronchial morphogenesis during the embryonic stage. We report that TAZ and YAP are sequentially expressed in the lung and that this could explain their different phenotypes. Furthermore, we report that YAP stimulates Shh (Sonic hedgehog) expression and regulates the FGF (fibroblast growth factor)-SHH feedback loop, thereby contributing to normal bronchial morphogenesis. We also found that TGF-ß (transforming growth factor-ß) stimulation induced Shh expression in the lung epithelial cells, and both TAZ and YAP are essential in this novel pathway. Our results provide a novel insight into the molecular mechanisms underlying lung development and contribute to a better understanding of the characteristics of TAZ and YAP.

Genomic alterations in STK11 can predict clinical outcomes in cervical cancer patients.

OBJECTIVE: Cervical cancer is the fourth most common cause of cancer-related deaths in Asian women, due to its poor prognosis. This study aimed to decipher genomic alteration profiles of a cohort of Japanese cervical cancer patients to understand why certain patients benefited from molecular targeted therapies and their prognostic significance. METHODS: During 2008-2018, 154 cervical cancer patients underwent a potentially curative resection procedure at the National Cancer Center Hospital. Genomic DNA samples were analyzed using Ion AmpliSeq™ Cancer Hotspot Panel v2. Alterations in the copy number of PIK3CA, ERBB2, PTEN, and STK11 were detected using the TaqMan assay. HPV-positive results were confirmed by genomic testing and in situ hybridization assay. RESULTS: The frequency of genomic alterations in PIK3CA (36%), STK11 (16%), PTEN (11%), TP53 (11%), and KRAS (8%) was >5%. KRAS mutations were preferentially detected in patients with adenocarcinomas, and the frequency of PIK3CA mutations in patients with squamous cell carcinomas was higher than that in patients with other histological cancer types. HPV-positive results were observed in 139/154 (90.3%) patients, and TP53 mutants were detected in HPV-negative specimens. In this study, the overall survival of patients with genomic alterations in STK11 was worse than in patients with wild-type STK11 (hazard ratio = 10.6, P = 0.0079) and TCGA dataset (hazard ratio = 2.46, P = 0.029). CONCLUSIONS: More than one-third of Japanese cervical cancer patients exhibit mutations targeted by molecular targeted therapies. We have proposed the prognostic value of STK11 genomic alterations.

Histone methyltransferase SMYD2 selective inhibitor LLY-507 in combination with poly ADP ribose polymerase inhibitor has therapeutic potential against high-grade serous ovarian carcinomas.

Dysfunction of histone methylation is known to be related to cancer progression. The histone methyltransferase SMYD2 methylates histone protein H3 and non-histone proteins, including poly ADP ribose polymerase 1 (PARP1). There have been reports of SMYD2 overexpression in several types of cancers. However, there are no reports regarding its role in high-grade serous ovarian carcinomas (HGSOCs). Therefore, we investigated the expression profile and conducted functional analysis on SMYD2 in HGSOC cells. In addition, we verified whether SMYD2 inhibition increases the susceptibility of HGSOC cells to PARP inhibitors. We analyzed the expression of histone methyltransferase SMYD2 by quantitative real-time polymerase chain reaction and immunohistochemistry using HGSOC clinical tissues (n = 35). We performed functional analyses, including cell proliferation assay, cell cycle analysis, and immunoblotting, after treatment with SMYD2 siRNAs and SMYD2 selective inhibitor LLY-507 in HGSOC cells. We also performed colony-formation assay after combination treatment with LLY-507 and PARP inhibitor olaparib in HGSOC cells. The expression profiles of SMYD2 showed significant overexpression of SMYD2 in HGSOC clinical tissues. The knockdown or inhibition of SMYD2 by siRNAs or LLY-507, respectively, suppressed cell growth by increasing the proportion of apoptotic cells. LLY-507 showed additive effect with olaparib in the colony-formation assay. These findings suggest that LLY-507 can be used alone or in combination with a PARP inhibitor for the treatment of patients with HGSOC.

The histone methyltransferase WHSC1 is regulated by EZH2 and is important for ovarian clear cell carcinoma cell proliferation.

BACKGROUND: Wolf-Hirschhorn syndrome candidate gene-1 (WHSC1), a histone methyltransferase, has been found to be upregulated and its expression to be correlated with expression of enhancer of zeste homolog 2 (EZH2) in several cancers. In this study, we evaluated the role of WHSC1 and its therapeutic significance in ovarian clear cell carcinoma (OCCC). METHODS: First, we analyzed WHSC1 expression by quantitative PCR and immunohistochemistry using 23 clinical OCCC specimens. Second, the involvement of WHSC1 in OCCC cell proliferation was evaluated by MTT assays after siRNA-mediated WHSC1 knockdown. We also performed flow cytometry (FACS) to address the effect of WHSC1 on cell cycle. To examine the functional relationship between EZH2 and WHSC1, we knocked down EZH2 using siRNAs and checked the expression levels of WHSC1 and its histone mark H3K36m2 in OCCC cell lines. Finally, we checked WHSC1 expression after treatment with the selective inhibitor, GSK126. RESULTS: Both quantitative PCR and immunohistochemical analysis revealed that WHSC1 was significantly overexpressed in OCCC tissues compared with that in normal ovarian tissues. MTT assay revealed that knockdown of WHSC1 suppressed cell proliferation, and H3K36me2 levels were found to be decreased in immunoblotting. FACS revealed that WHSC1 knockdown affected the cell cycle. We also confirmed that WHSC1 expression was suppressed by EZH2 knockdown or inhibition, indicating that EZH2 is upstream of WHSC1 in OCCC cells. CONCLUSIONS: WHSC1 overexpression induced cell growth and its expression is, at least in part, regulated by EZH2. Further functional analysis will reveal whether WHSC1 is a promising therapeutic target for OCCC.

Effects of SMYD2-mediated EML4-ALK methylation on the signaling pathway and growth in non-small-cell lung cancer cells.

A specific subtype of non-small-cell lung cancer (NSCLC) characterized with an EML4-ALK fusion gene, which drives constitutive oncogenic activation of anaplastic lymphoma kinase (ALK), shows a good clinical response to ALK inhibitors. We have reported multiple examples implying the biological significance of methylation on non-histone proteins including oncogenic kinases in human carcinogenesis. Through the process to search substrates for various methyltransferases using an in vitro methyltransferase assay, we found that a lysine methyltransferase, SET and MYND domain-containing 2 (SMYD2), could methylate lysine residues 1451, 1455, and 1610 in ALK protein. Knockdown of SMYD2 as well as treatment with a SMYD2 inhibitor in two NSCLC cell lines with an EML4-ALK gene significantly attenuated the phosphorylation levels of the EML4-ALK protein. Substitutions of each of these three lysine residues to an alanine partially or almost completely diminished in vitro methylation of ALK. In addition, we found that exogenous introduction of EML4-ALK protein with the substitution of lysine 1610 to an alanine in these two cell lines reduced the phosphorylation levels of AKT, one of the downstream oncogenic molecules in the EML4-ALK pathway, and suppressed the growth of the two cell lines. We further showed that the combination of a SMYD2 inhibitor and an ALK inhibitor additively suppressed the growth of these two NSCLC cells, compared with single-agent treatment. Our results shed light on a novel mechanism that modulates the kinase activity of the ALK fused gene product and imply that SMYD2-mediated ALK methylation might be a promising target for development of a novel class of treatment for tumors with the ALK fused gene.