Visualization of Metastatic Lung Cancer with TiNIR

Seul-Ki Mun; Hyun Bo Sim; Ji Yeon Han; Hyeongyeong Kim; Dae-Han Park; Dong-Jo Chang; Sung-Tae Yee; Young-Tae Chang; Jong-Jin Kim

doi:10.3390/tomography9040096

Visualization of Metastatic Lung Cancer with TiNIR

Tomography. 2023 Jun 21;9(4):1187-1195. doi: 10.3390/tomography9040096.

Authors

Seul-Ki Mun^{1

2}, Hyun Bo Sim¹, Ji Yeon Han¹, Hyeongyeong Kim¹, Dae-Han Park¹, Dong-Jo Chang², Sung-Tae Yee², Young-Tae Chang^{3

4}, Jong-Jin Kim¹

Affiliations

¹ Department of Biomedical Science, Sunchon National University, 255 Jungang-ro, Suncheon 57922, Republic of Korea.
² Department of Pharmacy, Sunchon National University, 255 Jungang-ro, Suncheon 57922, Republic of Korea.
³ School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Republic of Korea.
⁴ Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang 37673, Republic of Korea.

Abstract

The development of efficient biomarkers and probes for monitoring and treating cancer, specifically metastatic cancer, is a critical research area that can have a significant impact on both patient outcomes and drug discovery. In this context, TiNIR has been developed to detect tumor-initiating cells (TICs), with heme oxygenase 2 (HO2) as a promising therapeutic biomarker for tumor-initiating cells. In this study, TiNIR has demonstrated its effectiveness as an in vivo metastatic lung cancer tracker, highlighting its potential as a valuable tool in cancer research and therapy. The development of innovative approaches that selectively target metastatic cancers represents a promising avenue for improving survival rates and enhancing the quality of life of cancer patients.

Keywords: TiNIR; biomarkers; heme oxygenase 2 (HO2); metastatic lung cancer; probe.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Humans
Lung Neoplasms*
Quality of Life*

Grants and funding

This research was supported by the Sunchon National University Research Fund in 2021 (Grant number: 2021-0251) and a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2021R1C1C1006874). This research was supported by Basic Science Research Institute Fund (2021R1A6A1A10042944) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2023R1A2C300453411).