医学部 呼吸器内科学

Naozumi Hashimoto

  (橋本 直純)

Profile Information

Affiliation
Professor, Department of Respiratory Medicine, Fujita Health University
Degree
医学博士(名古屋大学)
PhD(Nagoya University)

J-GLOBAL ID
200901065007367549
researchmap Member ID
6000010184

Papers

 144
  • Junji Koyama, Masahiro Morise, Taiki Furukawa, Shintaro Oyama, Reiko Matsuzawa, Ichidai Tanaka, Keiko Wakahara, Hideo Yokota, Tomoki Kimura, Yoshimune Shiratori, Yasuhiro Kondoh, Naozumi Hashimoto, Makoto Ishii
    BMC cancer, 24(1) 1417-1417, Nov 18, 2024  
    BACKGROUND: Multiple first-line treatment options have been developed for advanced non-small cell lung cancer (NSCLC) in each subgroup determined by predictive biomarkers, specifically driver oncogene and programmed cell death ligand-1 (PD-L1) status. However, the methodology for optimal treatment selection in individual patients is not established. This study aimed to develop artificial intelligence (AI)-based personalized survival prediction model according to treatment selection. METHODS: The prediction model was built based on random survival forest (RSF) algorithm using patient characteristics, anticancer treatment histories, and radiomics features of the primary tumor. The predictive accuracy was validated with external test data and compared with that of cox proportional hazard (CPH) model. RESULTS: A total of 459 patients (training, n = 299; test, n = 160) with advanced NSCLC were enrolled. The algorithm identified following features as significant factors associated with survival: age, sex, performance status, Brinkman index, comorbidity of chronic obstructive pulmonary disease, histology, stage, driver oncogene status, tumor PD-L1 expression, administered anticancer agent, six markers of blood test (sodium, lactate dehydrogenase, etc.), and three radiomics features associated with tumor texture, volume, and shape. The C-index of RSF model for test data was 0.841, which was higher than that of CPH model (0.775, P < 0.001). Furthermore, the RSF model enabled to identify poor survivor treated with pembrolizumab because of tumor PD-L1 high expression and those treated with driver oncogene targeted therapy according to driver oncogene status. CONCLUSIONS: The proposed AI-based algorithm accurately predicted the survival of each patient with advanced NSCLC. The AI-based methodology will contribute to personalized medicine. TRIAL REGISTRATION: The trial design was retrospectively registered study performed in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Nagoya University Graduate School of Medicine (approval: 2020 - 0287).
  • Takayuki Okuji, Shintaro Iwama, Tomoko Kobayashi, Yoshinori Yasuda, Masaaki Ito, Ayana Yamagami, Masahiko Ando, Tetsunari Hase, Hirofumi Shibata, Takahiro Hatta, Xin Zhou, Takeshi Onoue, Yohei Kawaguchi, Takashi Miyata, Mariko Sugiyama, Daisuke Hagiwara, Hidetaka Suga, Ryoichi Banno, Yuichi Ando, Naozumi Hashimoto, Hiroshi Arima
    Nagoya journal of medical science, 86(3) 452-463, Aug, 2024  
    The presence of anti-thyroid antibodies (ATAs) is a biomarker for the development of thyroid dysfunction induced by anti-programmed cell death-1 antibodies (PD-1-Abs). While patients with thyroid dysfunction reportedly showed better overall survival (OS), it remains unknown if ATAs at baseline can predict OS. Therefore, in this study, we examined the association of ATAs at baseline with OS in non-small cell lung cancer (NSCLC) patients with different levels of programmed cell death-1 ligand 1 (PD-L1) positivity associated with PD-1-Ab treatment efficacy. A total of 81 NSCLC patients treated with PD-1-Abs were evaluated for ATAs at baseline and prospectively for OS. Among the 81 patients, 49 and 32 patients had ≥50% (group A) and <50% (group B) PD-L1 positivity, respectively. Median OS did not differ significantly between patients with (n = 13) and without (n = 36) ATAs at baseline in group A. In contrast, median OS was significantly longer in patients with (n = 10) versus without (n = 22) ATAs at baseline in group B (not reached vs 378 days, respectively; 95% CI, 182 to 574 days, p = 0.049). These findings suggest that the presence of ATAs at baseline is a biomarker to predict better treatment efficacy of PD-1-Abs in NSCLC patients with low PD-L1 positivity, while the difference in OS in those with high PD-L1 positivity may be masked by increased tumor expression of PD-L1.
  • Jun Fukihara, Koji Sakamoto, Yoshiki Ikeyama, Taiki Furukawa, Ryo Teramachi, Kensuke Kataoka, Yasuhiro Kondoh, Naozumi Hashimoto, Makoto Ishii
    Respiratory research, 25(1) 202-202, May 10, 2024  
    BACKGROUND: Extracellular mitochondrial DNA (mtDNA) is released from damaged cells and increases in the serum and bronchoalveolar lavage fluid (BALF) of idiopathic pulmonary fibrosis (IPF) patients. While increased levels of serum mtDNA have been reported to be linked to disease progression and the future development of acute exacerbation (AE) of IPF (AE-IPF), the clinical significance of mtDNA in BALF (BALF-mtDNA) remains unclear. We investigated the relationships between BALF-mtDNA levels and other clinical variables and prognosis in IPF. METHODS: Extracellular mtDNA levels in BALF samples collected from IPF patients were determined using droplet-digital PCR. Levels of extracellular nucleolar DNA in BALF (BALF-nucDNA) were also determined as a marker for simple cell collapse. Patient characteristics and survival information were retrospectively reviewed. RESULTS: mtDNA levels in serum and BALF did not correlate with each other. In 27 patients with paired BALF samples obtained in a stable state and at the time of AE diagnosis, BALF-mtDNA levels were significantly increased at the time of AE. Elevated BALF-mtDNA levels were associated with inflammation or disordered pulmonary function in a stable state (n = 90), while being associated with age and BALF-neutrophils at the time of AE (n = 38). BALF-mtDNA ≥ 4234.3 copies/µL in a stable state (median survival time (MST): 42.4 vs. 79.6 months, p < 0.001) and ≥ 11,194.3 copies/µL at the time of AE (MST: 2.6 vs. 20.0 months, p = 0.03) were associated with shorter survival after BALF collection, even after adjusting for other known prognostic factors. On the other hand, BALF-nucDNA showed different trends in correlation with other clinical variables and did not show any significant association with survival time. CONCLUSIONS: Elevated BALF-mtDNA was associated with a poor prognosis in both IPF and AE-IPF. Of note, at the time of AE, it sharply distinguished survivors from non-survivors. Given the trends shown by analyses for BALF-nucDNA, the elevation of BALF-mtDNA might not simply reflect the impact of cell collapse. Further studies are required to explore the underlying mechanisms and clinical applications of BALF-mtDNA in IPF.
  • Takuya Okamura, Sayako Morikawa, Tomoya Horiguchi, Kumiko Yamatsuta, Toshikazu Watanabe, Aki Ikeda, Yuri Maeda, Takuma Ina, Hideaki Takahashi, Ryoma Moriya, Yasuhiro Goto, Sumito Isogai, Naoki Yamamoto, Shotaro Okachi, Naozumi Hashimoto, Kazuyoshi Imaizumi
    Respiration; international review of thoracic diseases, Feb 22, 2024  
    INTRODUCTION: Increasing numbers of cases of mild asymptomatic pulmonary alveolar proteinosis (PAP) are being reported with the recent increase in chest computed tomography (CT). Bronchoscopic diagnosis of mild PAP is challenging because of the patchy distribution of lesions, which makes it difficult to obtain sufficient biopsy samples. Additionally, the pathological findings of mild PAP, particularly those that differ from severe PAP, have not been fully elucidated. This study aimed to clarify the pathological findings of mild PAP and the usefulness of optical biopsy using probe-based confocal laser endomicroscopy (pCLE). METHODS: We performed bronchoscopic optical biopsy using pCLE and tissue biopsy in five consecutive patients with PAP (three with mild PAP and two with severe PAP). We compared the pCLE images of mild PAP with those of severe PAP by integrating clinical findings, tissue pathology, and chest computed tomography images. RESULTS: pCLE images of PAP showed giant cells with strong fluorescence, amorphous substances, and thin alveolar walls. Images of affected lesions in mild PAP were equivalent to those obtained in arbitrary lung lesions in severe cases. All three patients with mild PAP spontaneously improved or remained stable after ≥3 years of follow-up. Serum autoantibodies to granulocyte-macrophage colony-stimulating factor were detected in all five cases. CONCLUSION: Optical biopsy using pCLE can yield specific diagnostic findings, even in patients with mild PAP. pCLE images of affected areas in mild and severe PAP showed similar findings, indicating that the dysfunction level of pathogenic alveolar macrophages in affected areas is similar between both disease intensities.
  • Ken Akao, Yuko Oya, Takaya Sato, Aki Ikeda, Tomoya Horiguchi, Yasuhiro Goto, Naozumi Hashimoto, Masashi Kondo, Kazuyoshi Imaizumi
    Exploration of targeted anti-tumor therapy, 5(4) 826-840, 2024  
    Despite innovative advances in molecular targeted therapy, treatment strategies using immune checkpoint inhibitors (ICIs) for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) have not progressed significantly. Accumulating evidence suggests that ICI chemotherapy is inadequate in this population. Biomarkers of ICI therapy, such as programmed cell death ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs), are not biomarkers in patients with EGFR mutations, and the specificity of the tumor microenvironment has been suggested as the reason for this. Combination therapy with PD-L1 and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors is a concern because of its severe toxicity and limited efficacy. However, early-stage NSCLC may differ from advanced-stage NSCLC. In this review, we comprehensively review the current evidence and summarize the potential of ICI therapy in patients with EGFR mutations after acquiring resistance to treatment with EGFR-tyrosine kinase inhibitors (TKIs) with no T790M mutation or whose disease has progressed on osimertinib.

Misc.

 118

Presentations

 9

Research Projects

 14

Social Activities

 1