News Express: UM offers precise treatment option for non-small cell lung cancer patients

新聞快訊: 澳大為非小細胞肺癌患者提供精準治療方案

 

免疫治療無應答相關的亞群:研究發現治療無應答的特定免疫細胞亞群的存在,特別是CD8+CD101hiTIM3+(CCT T)細胞,可以有效預測治療的有效性
The presence of specific immune cell subsets, in particular CD8+CD101hiTIM3+ (CCT T) cells, can predict treatment efficacy

 


澳大為非小細胞肺癌患者提供精準治療方案

澳門大學健康科學學院教授梁麗嫻的研究團隊揭示了可有效反應非小細胞肺癌(NSCLC)患者對於免疫檢查點抑制劑(ICB)應答率的預測標誌物,可用於早期和及時監測免疫治療療效,能為非小細胞肺癌患者提供一種無創且精準的治療方案。相關研究成果已發表在知名期刊《自然通訊》上。

目前,ICB是NSCLC患者的最後治療選擇之一,雖然其對於腫瘤的抑制效果顯著,但是並不是所有患者都可以從中受益,所以在早期發現和預測治療應答率的標誌物對於患者的選擇至關重要。為了實現ICB治療的更好效果,目前已有很多研究報導了細胞程式死亡受體 -1(PD-1)單抗的預測性標誌物,例如腫瘤浸潤性T細胞的比例、組織活檢中細胞程式死亡配體 -1(PD-L1)的高表達、微衛星不穩定性(MSI)、Kelch樣環氧氯丙烷相關蛋白1(KEAP1) 和絲氨酸/蘇氨酸蛋白激酶11(STK11)的突變以及高腫瘤突變負荷(TMB)。但是這些指標或因觀察時間有限、檢測患者數目不足、缺少客觀生物資訊學統計等的影響,導致對於預測免疫治療應答的指標仍是不盡如人意,其中主要原因是抗PD-1免疫治療在治療週期內是動態變化的過程,因此需要長時間縱向觀察,以追蹤與治療應答率相關的標誌物。目前,全球尚未有可有效預測應答率的無創檢測方法,例如通過抽血檢測應答細胞類型來預測ICB治療療效,梁麗嫻的研究團隊實現了這一點,為初步理解獲得性耐藥的免疫機制提供了方向。

該研究對於25位患者進行了至少30個月的跟蹤,運用前沿的高維度CyTOF和多重細胞因數方法對患者的血液樣品進行檢測,深入探究免疫治療無應答人群的免疫細胞類型以及免疫系統功能特性,通過高維度生物資訊學綜合分析,團隊確定了可以有效預測抗PD-1治療效果的血液生物標誌物。研究發現治療無應答特定免疫細胞亞群的存在,特別是CD8+CD101hiTIM3+(CCT T)細胞,可以有效預測治療的有效性。這項研究的發現對於NSCLC治療的未來發展具有深遠的影響。研究人員通過運用先進技術分析免疫反應,確定了治療有效性的新預測標誌物。這些見解可以指導精準治療,並有助於更好地理解治療抵抗機制。

梁麗嫻與廣州中醫藥大學第二附屬醫院、中醫證候全國重點實驗室主任劉良和澳門鏡湖醫院醫生曹亞兵為該研究的共同通訊作者。梁麗嫻、廣州中醫藥大學第二附屬醫院教授李潤澤和澳門科技大學教授范星星同為該研究的第一作者。該研究由澳門科學技術發展基金資助(檔案編號:0063/2022/A2和001/2020/ALC),並獲國家中醫藥管理局2020青年岐黃學者、強生治療基金(檔案編號:ICD#1101175)和粵港澳聯合實驗室專案(檔案編號:2020B1212030006)資助。該研究也得到澳門大學研究啟動基金(檔案編號:SRG2022-00020-FHS)、澳門大學健康科學學院(檔案編號:82204677)、廣州市科技專案(檔案編號:SL2022A04J00459)和濕證國家實驗室項目(檔案編號:SZ2022KF20)的資助。研究文章全文可瀏覽:https://www.nature.com/articles/s41467-023-40631-0。

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https://www.um.edu.mo/zh-hant/news-and-press-releases/presss-release/detail/57052/


UM offers precise treatment option for non-small cell lung cancer patients

A research team led by Elaine Leung Lai Han, professor in the Faculty of Health Sciences (FHS) at the University of Macau (UM), has unveiled critical insights into the responding phenotype of the effectiveness of immune checkpoint blockade (ICB) therapy for non-small cell lung cancer (NSCLC) patients. They identified a set of immune subtypes that are enriched in non-responders to ICB therapy, which can provide a non-invasive and feasible method for early and timely monitoring of treatment response. The research results have been published in the renowned journal Nature Communications.

Although ICB therapy is known to produce durable clinical responses in a selected group of NSCLC patients, not all patients can benefit from it. Therefore, early identification of progression is crucial for treatment selection for patients. To achieve better effectiveness with ICB therapy, parameters indicating favourable response are critically needed. Several predictors of the response to programmed death-1 (PD-1) blockade have been reported, such as the presence of tumour-infiltrating T cells, high programmed death-ligand 1 (PD-L1) expression in biopsies, microsatellite instability (MSI), Kelch-like ECH-associated protein 1 (KEAP1) and Serine/Threonine kinase 11 (STK11) mutations test and the tumour mutational burden (TMB). However, these parameters are hampered by the limited longitudinal observation window, the small number of parameters, and the lack of systematic, unbiased bioinformatic pipelines, which has resulted in a paucity of indicators predicting response state to date. Longitudinal investigation is important to trace markers associated with acquired resistance since the anti-PD1-mediated immune response is dynamic during treatment cycles. Currently, it is unclear whether non-invasive approaches, such as peripheral blood mononuclear cell (PBMC) profiling, can be used to predict responses to ICB therapy by identifying the relevant responding cell types. Prof Leung’s research team has made a breakthrough and their study provides new insights for understanding the underlying immunological mechanisms of primary and acquired resistance.

The study followed 25 NSCLC patients for at least 30 months and used innovative high-dimensional CyTOF and multiplex cytokine approaches to examine patients’ blood samples. This allowed the researchers to gain insights into immune populations, their molecular profiles, and functional characteristics. By analysing immune cell responses, the research team identified key markers that can predict the efficacy of anti-PD-1 therapy. The study discovered that the presence of specific immune cell subsets, in particular CD8+CD101hiTIM3+ (CCT T) cells, can predict treatment efficacy. The findings have far-reaching implications for the future development of NSCLC treatment. By utilising advanced techniques to analyse the immune response, the researchers have identified novel predictive markers for treatment efficacy. These insights shed light on precision therapy and contribute to a better understanding of treatment resistance mechanisms.

Prof Leung, Prof Liu Liang at the Second Affiliated Hospital of the Guangzhou University of Chinese Medicine, and Cao Yabing, a doctor at Kiang Wu Hospital in Macao, are the co-corresponding authors. Prof Leung, Prof Li Run-Ze at the Second Affiliated Hospital of the Guangzhou University of Chinese Medicine, and Prof Fan Xing-Xing at the Macau University of Science and Technology share the first authorship. The research project was supported by the Science and Technology Development Fund of the Macao SAR (File no: 0063/2022/A2 and 001/2020/ALC), 2020 ‘Qi-Huang’ Young Scholar programme of the National Administration of Traditional Chinese Medicine, Janssen Therapeutic Fund (File no: ICD#1101175), 2020 Guangdong Provincial Science and Technology Innovation Strategy Special Fund of the Guangdong-Hong Kong-Macao Joint Lab (File no: 2020B1212030006), Start-up Research Grant of UM (File no: SRG2022-00020-FHS), Faculty of Health Sciences of UM (File no: 82204677), Science and Technology Projects in Guangzhou (File no: SL2022A04J00459), and Technology Research Projects of State Key Laboratory of Dampness Syndrome of Chinese Medicine (File no: SZ2022KF20). The full version of the research paper can be viewed at https://www.nature.com/articles/s41467-023-40631-0.

To read the news on UM’s official website, please visit the following link:
https://www.um.edu.mo/news-and-press-releases/press-release/detail/57052/