Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background/Aims: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC. Methods: We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines. Results: Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845). Conclusions AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.