Miso Kim, Hyo Sup Shim, Sheehyun Kim, In Hee Lee, Jihun Kim, Shinkyo Yoon, Hyung-Don Kim, Inkeun Park, Jae Ho Jeong, Changhoon Yoo, Jaekyung Cheon, In-Ho Kim, Jieun Lee, Sook Hee Hong, Sehhoon Park, Hyun Ae Jung, Jin Won Kim, Han Jo Kim, Yongjun Cha, Sun Min Lim, Han Sang Kim, Choong-Kun Lee, Jee Hung Kim, Sang Hoon Chun, Jina Yun, So Yeon Park, Hye Seung Lee, Yong Mee Cho, Soo Jeong Nam, Kiyong Na, Sun Och Yoon, Ahwon Lee, Kee-Taek Jang, Hongseok Yun, Sungyoung Lee, Jee Hyun Kim, Wan-Seop Kim
J Pathol Transl Med. 2024;58(4):147-164. Published online January 10, 2024
In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.
Background Accurate molecular classification of breast core needle biopsy (CNB) tissue is important for determining neoadjuvant systemic therapies for invasive breast cancer. The researchers aimed to evaluate the concordance rate (CR) of molecular subtypes between CNBs and surgical specimens.
Methods This study was conducted with invasive breast cancer patients who underwent surgery after CNB at Seoul St. Mary’s Hospital between December 2014 and December 2017. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 were analyzed using immunohistochemistry. ER and PR were evaluated by Allred score (0–8). HER2 was graded from 0 to +3, and all 2+ cases were reflex tested with silver in situ hybridization. The labeling index of Ki67 was counted by either manual scoring or digital image analysis. Molecular subtypes were classified using the above surrogate markers.
Results In total, 629 patients were evaluated. The CRs of ER, PR, HER2, and Ki67 were 96.5% (kappa, 0.883; p<.001), 93.0% (kappa, 0.824; p<.001), 99.7% (kappa, 0.988; p<.001), and 78.7% (kappa, 0.577; p<.001), respectively. Digital image analysis of Ki67 in CNB showed better concordance with Ki67 in surgical specimens (CR, 82.3%; kappa, 0.639 for digital image analysis vs. CR, 76.2%; kappa, 0.534 for manual counting). The CRs of luminal A, luminal B, HER2, and triple negative types were 89.0%, 70.0%, 82.9%, and 77.2%, respectively.
Conclusions CNB was reasonably accurate for determining ER, PR, HER2, Ki67, and molecular subtypes. Using digital image analysis for Ki67 in CNB produced more accurate molecular classifications.
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