Immune Phenotyping Identified as Promising Predictive Biomarker by Lunit AI in Biliary Tract Cancer - New Publication in CCR
Immune Phenotyping Identified as Promising Predictive Biomarker by Lunit AI in Biliary Tract Cancer - New Publication in CCR
- AI-based tumor microenvironment classification utilizing Lunit SCOPE IO shows promise for guiding treatment decisions in advanced BTC
- 利用 Lunit SCOPE IO 進行基於人工智能的腫瘤微環境分類，有望指導晚期 BTC 的治療決策
SEOUL, South Korea, Sept. 3, 2024 /PRNewswire/ -- Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced that Lunit SCOPE IO has demonstrated significant potential in predicting immunotherapy response for patients with advanced biliary tract cancer (BTC), via AI-powered analysis of immune phenotype and tumor-infiltrating lymphocytes (TILs). The groundbreaking study, conducted in collaboration with researchers from Asan Medical Center and Severance Hospital in Seoul, Korea, was recently published in Clinical Cancer Research (CCR), an AACR journal.
韓國首爾，2024年9月3日 /PRNewswire/--由人工智能驅動的癌症診斷和治療解決方案的領先提供商Lunit（KRX: 328130.KQ）今天宣佈，通過對免疫表型和腫瘤浸潤淋巴細胞的人工智能分析，Lunit SCOPE IO在預測晚期膽道癌（BTC）患者的免疫療法反應方面顯示出巨大潛力（KRX: 328130.KQ）TIL）。這項開創性的研究是與韓國首爾峨山醫學中心和塞弗蘭斯醫院的研究人員合作進行的，是 最近發表在《臨床癌症研究》（CCR）上，一本 AACR 期刊。
BTC is known for its poor prognosis, with limited treatment options available. While recent studies have shown promise in combining immunotherapy, such as anti-PD-1 inhibitors with standard chemotherapy, there has been a lack of effective predictive tools to guide treatment decisions.
BTC以其預後不佳而聞名，可用的治療選擇有限。儘管最近的研究表明，將抗PD-1抑制劑等免疫療法與標準化療相結合有希望，但缺乏有效的預測工具來指導治療決策。
The study analyzed pre-treatment pathology samples (H&E slides) from 339 patients with advanced BTC who received anti-PD-1 monotherapy as second-line or later treatment. Using Lunit SCOPE IO, researchers performed a detailed analysis of the tumor microenvironment, classifying patients' immune phenotypes into three categories: inflamed (high intratumoral TIL), immune-excluded (low intratumoral TIL and high stromal TIL), and immune desert (low TIL overall). Immune phenotypes are an emerging pan-cancer biomarker with support from leaders of the immuno-oncology community.[1]
該研究分析了339名晚期BTC患者的治療前病理樣本（H＆E幻燈片），這些患者接受了抗PD-1單一療法作爲二線或後續治療。研究人員使用Lunit SCOPE IO對腫瘤微環境進行了詳細分析，將患者的免疫表型分爲三類：發炎（高腫瘤內TIL）、免疫排除（低腫瘤內TIL和高間質TIL）和免疫沙漠（總體上低TIL）。免疫表型是一種新興的泛癌生物標誌物，得到了免疫腫瘤學界領導人的支持。[1]
Key findings include:
主要發現包括：
- Patients classified as having an "inflamed" immune phenotype showed significantly better treatment outcomes compared to those with non-inflamed phenotypes, as consistent with previously published studies.[2]
- The inflamed group demonstrated both longer overall survival (12.6 vs. 5.1 months) and progression-free survival (4.5 vs. 1.9 months), as well as higher overall response rates (27.5% vs. 7.7%).
- Lunit SCOPE IO provided objective and efficient assessment of the tumor microenvironment, overcoming limitations of manual evaluation demonstrating high feasibility for AI-powered analysis of immune phenotype and TIL.
- 與非發炎表型的患者相比，被歸類爲 「發炎」 免疫表型的患者表現出明顯更好的治療效果，這與先前發表的研究一致。[2]
- 發炎組表現出更長的總存活率（12.6個月對5.1個月）和無進展存活率（4.5對1.9個月），以及更高的總體緩解率（27.5％對7.7％）。
- Lunit SCOPE IO 提供了對腫瘤微環境的客觀高效評估，克服了手動評估的侷限性，表明人工智能驅動的免疫表型和 TIL 分析具有很高的可行性。
Notably, this study suggests immune phenotyping can serve as a predictive biomarker for possible response to immunotherapy in BTC, addressing a long-standing gap in personalized treatment approaches for this class of cancers with a high unmet need.
值得注意的是，這項研究表明，免疫表型可以作爲BTC對免疫療法可能產生的反應的預測生物標誌物，從而解決了針對此類需求未得到滿足的癌症的個性化治療方法中長期存在的差距。
"Lunit SCOPE IO represents a significant advancement in the precision medicine landscape for cancer treatment," said Brandon Suh, CEO at Lunit. "By providing a deeper understanding of the tumor microenvironment, particularly immune phenotyping, our AI technology empowers clinicians to make informed treatment decisions, identifying patients most likely to benefit from immunotherapy and opening new avenues for personalized treatment strategies in challenging cancer types."
Lunit首席執行官Brandon Suh表示：「Lunit SCOPE IO代表了癌症治療精準醫療領域的重大進步。」「通過更深入地了解腫瘤微環境，尤其是免疫表型分析，我們的人工智能技術使臨床醫生能夠做出明智的治療決策，識別最有可能從免疫療法中受益的患者，併爲挑戰癌症類型的個性化治療策略開闢新的途徑。」
About Lunit
關於 Lunit
Founded in 2013, Lunit is a medical AI company on a mission to conquer cancer. We harness AI-powered medical image analytics and AI biomarkers to ensure accurate diagnosis and optimal treatment for each cancer patient. Our FDA-cleared Lunit INSIGHT suite for cancer screening serves over 3,500 hospitals and medical institutions across 50+ countries.
Lunit 成立於 2013 年，是一家醫療人工智能公司，其使命是戰勝癌症。我們利用人工智能驅動的醫學圖像分析和人工智能生物標誌物，確保爲每位癌症患者提供準確的診斷和最佳治療。我們經美國食品藥品管理局批准的Lunit Insight癌症篩查套件爲50多個國家的3500多家醫院和醫療機構提供服務。
Our clinical studies have been published in top journals, including the Journal of Clinical Oncology and the Lancet Digital Health, and presented at global conferences such as the ASCO and RSNA. In 2024, Lunit acquired Volpara Health Technologies, setting the stage for unparalleled synergy and accuracy, particularly in breast health and screening technologies. Headquartered in Seoul, South Korea, with a network of offices worldwide, Lunit leads the global fight against cancer. Discover more at lunit.io.
我們的臨床研究已發表在頂級期刊上，包括《臨床腫瘤學雜誌》和《柳葉刀數字健康》，並在ASCO和RSNA等全球會議上發表。2024年，Lunit收購了Volpara Health Technologies，爲無與倫比的協同作用和準確性奠定了基礎，尤其是在乳房健康和篩查技術方面。Lunit總部位於韓國首爾，在全球設有辦事處網絡，領導全球抗擊癌症。在以下網址了解更多 lunit.io。
[1] The cancer-immunity cycle: Indication, genotype, and immunotype, Immunity, 2023: Link
[2] Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types, JITC, 2024: Link
[1] 癌症免疫週期：適應症、基因型和免疫型，《免疫》，2023年： 鏈接
[2] 發炎的免疫表型可預測免疫檢查點抑制劑治療在多種癌症類型中的良好臨床結果，JITC，2024年： 鏈接
SOURCE Lunit
來源 Lunit