Masahiko Nishiyama

N ⁶ -methyladenosine (m ⁶ A) is an abundant chemical RNA modification involved in the regulation of many biological processes. The m ⁶ A demethylase FTO (fat mass and obesity-associated protein) is known to affect body weight, but its systemic context and underlying mechanisms remain unclear. Here, we found that mice lacking or overexpressing Fto in agouti-related peptide-expressing (AgRP) neurons in the hypothalamus exhibited decreased and increased body weight, respectively. FTO demethylated m ⁶ A on mRNAs for proteins associated with membrane trafficking and alternative splicing in AgRP neurons. Downstream, FTO-modulated alternative splicing of the axonal motor protein Kif1a affected its hinge region, which is relevant to the structure and function of KIF1A. Notably, Kif1a knockdown in AgRP neurons suppressed the weight gain of mice overexpressing Fto . In addition, FTO increased the trafficking and secretion of dense-core vesicles containing neuropeptides NPY and AgRP from AgRP neurons. Collectively, these results reveal a novel regulatory FTO-KIF1A axis in the brain affecting appetite-stimulating AgRP neurons and systemic energy homeostasis, via FTO regulation of the epitranscriptome of AgRP neurons.

Background/Objective: The Empty Spiracles Homeobox 2 (EMX2) gene is a homeobox transcription factor that is critical for the development of the central nervous system and genitourinary system during embryogenesis. EMX2 has been shown to regulate cellular differentiation, migration, and proliferation through its involvement in transcriptional control. Dysregulation of EMX2 expression has been implicated in various pathological conditions, including cancer, but the precise molecular mechanisms underlying EMX2 functions in cancer remain incompletely understood. In this study, we focus on the expression profile and the prognostic significance of EMX2 in esophageal squamous cell carcinoma (ESCC). Methods/Results: The expression levels of EMX2 in clinical ESCC samples varied and appeared to be lower than those in adjacent normal tissues. In addition, EMX2 expression was detected in some of the 20 ESCC cell lines but not in others and was correlated with 5-FU sensitivity. EMX2 expression in ESCC cell lines was strongly associated with colony formation capacity in soft agar, and EMX2 knockdown decreased colony formation. Enforced expression of EMX2 decreased the side population (SP) ratio in FACS analysis but increased colony formation in SP fractions. Although it is a preliminary experiment, xenograft in immunodeficient (NOD) scid mice suggested that the forced expression of EMX2 increased tumorigenic capacity in vivo. A Kaplan–Meyer analysis of patients from whom 20 ESCC cell lines or 18 ESCC tissue samples were obtained indicated that EMX2 expression was a poor prognostic marker. Conclusion: EMX2 has a unique function in ESCC stemness and its expression is the stamped marker of poor prognosis in ESCC patients.

Sato S, et al. J Gynecol Oncol. 2024 Aug;36:e24. https://doi.org/10.3802/jgo.2025.36.e24

Background Platinum/taxane (TC) chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis, and recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact. Nevertheless, the response varies among patients and consequent recurrence, or relapse often occurs. Discovery of therapeutic response predictor to ddTCip and/or TC therapy is eagerly awaited to improve the treatment outcome. Methods Using datasets in 76 participants in our ddTCip study and published databases on patients received TC therapy, we first validated a total of 75 previously suggested markers, sought out more active biomarkers through the association analyses of genome-wide transcriptome and genotyping data with progression-free survival (PFS) and adverse events, and then developed multiplex statistical prediction models for PFS and toxicity by mainly using multiple regression analysis and the classification and regression tree (CART) algorithm. Results The association analyses revealed that SPINK1 could be a possible biomarker of ddTCip efficacy, while ABCB1 rs1045642 and ERCC1 rs11615 would be a predictor of hematologic toxicity and peripheral neuropathy, respectively. Multiple regression analyses and CART algorithm finally provided a potent efficacy prediction model using 5 gene expression data and robust multiplex toxicity prediction models-CART models using a total of 4 genotype combinations and multiple regression models using 15 polymorphisms on 12 genes. Conclusion Biomarkers and multiplex models composed here could work well in the response prediction of ddTCip and/or TC therapy, which might contribute to realize optimal selection of the key therapy.

Background: Platinum/taxane chemotherapy with debulking surgery stays the mainstay of the treatment in ovarian cancer patients with peritoneal metastasis. Recently its novel modality, intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip), was shown to have greater therapeutic impact, but consequent recurrence or relapse still often occurs. Discovery of therapeutic response predictor to ddTCip therapy is eagerly awaited to improve current treatment strategy for disseminated ovarian cancer patients. Methods: Using datasets in 76 participants in this study and 189 patients published in The Cancer Genome Atlas, we first validated a total of 75 previously suggested markers, sought out more active biomarkers through the association analyses of genome-wide transcriptome and genotyping analyses with progression-free survival (PFS)and adverse events, and then developed multiplex statistical prediction models for PFS and toxicity by mainly using multiple regression analysis and the classification and regression tree (CART) algorithm. Results: The association analyses revealed that SPINK1 expression could be a potent biomarker of ddTCip efficacy, while ABCB1 rs1045642 and ERCC1rs11615 would be a predictor of hematologic toxicity and peripheral neuropathy, respectively. Multiple regression analyses and CART algorithm finally provided a potent efficacy prediction model using 5 gene expression data and robust multiplex prediction models for adverse events: CART models using a total of 4 genotype combinations and multiple regression models using 15 polymorphisms on 12 genes. Conclusion: Our proposed biomarkers and multiplex models composed here would work well in the response prediction of ddTCip therapy, which might contribute to realize optimal selection of the key therapy.

Background An international retrospective cohort study was conducted to clarify the survival advantage of combination therapy with locoregional and systemic therapy (ST) in oligometastatic breast cancer (BC). Methods Patients with oligometastatic BC diagnosed from 2007 to 2012 were enrolled in center hospitals in China, Korea and Japan. It was defined as a low-volume metastatic disease at up to five sites and not necessarily in the same organ. Cases with brain, pleural, peritoneal and pericardial metastases were excluded. The primary endpoint was overall survival (OS) from the initial diagnosis of oligometastases. OS was summarized using the Kaplan–Meier method. A multivariable Cox regression model was used to estimate the hazard ratio (HR) for clinicopathological factors. Results Among 1,295 cases registered from February 2018 to May 2019, 932 remained for analysis after the exclusion of unavailable cases and locoregional recurrence. One metastatic site was found in 400 cases, 2 in 243, 3 in 130, 4 in 86 and 5 in 73. At the median follow-up of 4.5 years, 5-year OS was 54.7% and 39.7% for 321 cases in the combination therapy group and 611 cases in the ST group, respectively. An adjusted HR was 0.66 (95% confidence interval: 0.55, 0.79). Some types of ST without chemotherapy alone, younger age, ECOG performance status 0, early-stage BC, non-triple negative subtype, fewer metastatic sites and longer duration of surgery to relapse were significantly favorable prognostic factors. Conclusion Combination therapy may be considered for longer survival under some conditions in oligometastatic BC.

Background: In advanced or metastatic ovarian cancer patients, the therapeutic impact of molecular targeted agents and immunotherapy is limited, and current chemotherapeutic algorithm is still far from personalized medicine. We recently demonstrated that intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip) therapy is a promising front-line chemotherapy even in the patients with residual peritoneal tumors, which led us to this theranostic study for biomarker discovery to realize the precision medicine (ID: UMIN000001713 on Feb 16 th , 2009). Methods: We first validated previously suggested markers (41 genes and 3 predictive models for the therapeutic efficacy and 31 polymorphisms for the toxicity), sought out more active effective biomarkers through genome-wide transcriptome and genotyping analyses, and then developed multiplex statistical prediction models for progression free-survival (PFS) and toxicity. Multiple regression analysis following forward stepwise method and Classification and Regression Trees (CART) algorithm were mainly employed to develop multiplex prediction models. Results: The association analyses with PFS in 76 patients followed by the validation study using data sets in 189 patients published in The Cancer Genome Atlas revealed that SPINK1 expression could be a possible predictive biomarker of ddTCip efficacy even when used alone, and multiple regression analyses provided a potent efficacy prediction model using expression data of 5 genes. SPINK1 appeared to be a critical resistant determinant of ddTCip therapy, which indicates the potential of SPINK1 also to be a novel therapeutic target. As for the toxicity prediction, ABCB1rs1045642 and ERCC1rs11615 polymorphisms appeared to closely associate with grade2-4 hematologic toxicity and peripheral neuropathy, respectively. We further successfully composed robust multiplex prediction models for the adverse events-CART models using a total of 4 genotype combinations and further powerful multiple regression models using 15 polymorphisms on 12 genes-. Conclusions: We newly proposed SPINK1 expression as a powerful predictive biomarker of the efficacy for ddTCip therapy and confirmed the predictive values of ABCB1 and/or ERCC1 polymorphisms for the toxicity. Multiplex prediction models composed herein were also found to work well for the prediction of therapeutic response. These may raise the potential to realize a precision medicine in the essential treatment for metastatic ovarian cancer patients.

Background:In advanced or metastatic ovarian cancer patients, the therapeutic impact of molecular targeted agents and immunotherapy is limited, and current chemotherapeutic algorithms are still far from personalized medicine.We recently demonstrated that intraperitoneal carboplatin with dose-dense paclitaxel (ddTCip) therapy is a promising front-line chemotherapy even in patients with residual peritoneal tumors, which led us to this theranostic study for biomarker discovery to realize precision medicine (ID: UMIN000001713 on Feb 16^th, 2009).Methods:We first validated previously suggested markers (41 genes and 3 predictive models for therapeutic efficacy and 31 polymorphisms for toxicity), sought out more active effective biomarkers through genome-wide transcriptome and genotyping analyses, and then developed multiplex statistical prediction models for progression-free survival (PFS) and toxicity. Multiple regression analysis following the forward stepwise method and the classification and regression tree (CART) algorithm were mainly employed to develop multiplex prediction models.Results:The association analyseswith PFS in 76 patients followed by the validation study using data sets in 189 patients published in The Cancer Genome Atlas revealed thatSPINK1expression could be a possible predictive biomarker of ddTCip efficacy even when used alone, and multiple regression analyses provided a potent efficacy prediction model using expression data of 5 genes. SPINK1 appeared to be a critical resistant determinant of ddTCip therapy, which indicates the potential of SPINK1 as a novel therapeutic target. For toxicity prediction, ABCB1 rs1045642 and ERCC1 rs11615 polymorphisms appeared to be closely associated with grade 2-4 hematologic toxicity and peripheral neuropathy, respectively. We further successfully composed robust multiplex prediction models for adverse events - CART models using a total of 4 genotype combinations and further powerful multiple regression models using 15 polymorphisms on 12 genes-.Conclusions:We newly proposedSPINK1expression as a powerful predictive biomarker of the efficacy of ddTCip therapy and confirmed the predictive values ofABCB1and/orERCC1polymorphisms for toxicity. The multiplex prediction models composed herein were also found to work well for the prediction of therapeutic response.These findings may raise the potential to realize precision medicine in the essential treatment for metastatic ovarian cancer patients.

Background: Hypopharyngeal cancer is a relatively rare malignancy with poor prognosis. Current chemotherapeutic algorithm is still far from personalized medicine, and the identification of the truly active therapeutic biomarkers and/or targets is eagerly awaited. Methods: Venturing to focus on the conventional key chemotherapeutic drugs, we identified the most correlative genes (and/or proteins) with cellular sensitivity to docetaxel (TXT), cisplatin (CDDP) and 5-fluorouracil (5-FU) in the expression levels, through 3 steps approach: genome-wide screening, confirmation study on the quantified expression levels, and knock-down and transfection analyses of the candidates. The probable action pathways of selected genes were examined by Ingenuity Pathway Analysis using a large-scale database, The Cancer Genome Atlas. Results: The first genome-wide screening study derived 16 highly correlative genes with cellular drug sensitivity in 15 cell lines (|R| > 0.8, P < 0.01 for CDDP and 5-FU; |R| > 0.5, P < 0.05 for TXT). Among 10 genes the observed correlations were confirmed in the quantified gene expression levels, and finally knock-down and transfection analyses provided 4 molecules as the most potent predictive markers-AGR2 (anterior gradient 2 homolog gene), and PDE4D (phosphodiesterase 4D, cAMP-specific gene) for TXT; NINJ2 (nerve Injury-induced protein 2); CDC25B (cell division cycle 25 homolog B gene) for 5-FU- in both gene and protein expression levels. Overexpression of AGR2, PDE4D signified worse response to TXT, and the repressed expression sensitized TXT activity. Contrary to the findings, in the other 2 molecules, NINJ2 and CDC25, there observed opposite relationship to cellular drug response to the relevant drugs. IPA raised the potential that each selected molecule functionally interacts with main action pathway (and/or targets) of the relevant drug such as tubulin β chain genes for TXT, DNA replication pathway for CDDP, and DNA synthesis pathway and thymidylate synthetase gene for 5-FU. Conclusion: We newly propose 4 molecules -AGR2, PDE4D,NINJ2 and CDC25B) as the powerful exploratory markers for prediction of cellular response to 3 key chemotherapeutic drugs in hypopharyngeal cancers and also suggest their potentials to be the therapeutic targets, which could contribute to the development of precision medicine of the essential chemotherapy in hypopharyngeal patients. (339 words).

Cancer-associated fibroblasts (CAFs) play vital roles in tumor progression by promoting epithelial-to-mesenchymal transition, angiogenesis, and immunosuppression. In the present study, we sought to identify the key regulators of the pro-tumoral functions of CAFs in head and neck squamous cell carcinoma (HNSCC). mRNA expression data obtained from The Cancer Genome Atlas revealed that CAF-specific mRNA expression correlated with genes that relate to an immunosuppressive microenvironment in a HNSCC cohort. RNA sequencing of CAFs and normal fibroblasts isolated from HNSCC specimens identified 1127 differentially expressed genes (DEGs) and several upregulated pathways in CAFs. Among the 1127 DEGs, we identified 13 immune function-related genes and focused on AKT3 as a potential regulator of CAFs. The targeted depletion of AKT3 in CAFs revealed that AKT3 promotes their myofibroblastic phenotype. AKT3-transduced CAFs exhibited downregulated the expression of immunosuppressive cytokine genes, impairing T-cell suppression and pro-tumoral macrophage induction. The immunohistochemistry of 72 HNSCC patients showed that AKT3 expression in CAFs positively correlated with tumor infiltration by CAFs, tumor-associated macrophages, dendritic cells, and T cells. Moreover, AKT3 expression in CAFs was an independent prognostic factor for overall survival. In conclusion, AKT3 is a potential target for cancer therapy that inhibits the pro-tumoral function of CAFs and reverses CAF-mediated immunosuppression.