LBPO.CL02 · 临床研究 · Late-Breaking
单细胞分辨率的空间免疫结构可预测晚期HCC对atezolizumab联合bevacizumab的疗效
Spatial immune architecture at single-cell resolution predicts response to atezolizumab plus bevacizumab in advanced HCC
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:Atezolizumab+bevacizumab(atezo+bev)是晚期肝细胞癌(aHCC)的一线治疗方案,客观应答率约为30%。单细胞研究发现应答与CD8⁺ T效应细胞(CD8_Tex和Temra)和CXCL10⁺巨噬细胞(Macro_CXCL10)相关,而耐药与TREM2⁺巨噬细胞(Macro_TREM2)和CD14⁺单核细胞(Mono_CD14)相关。我们假设,除细胞组成外,肿瘤微环境(TME)内的免疫空间组织决定了对atezo+bev的应答。
方法:对27例aHCC(9例atezo+bev应答者和18例耐药者)使用Xenium Prime 5,000基因panel(10x Genomics)并定制额外100个基因进行单细胞空间转录组学(ST)分析。对于局部组织组织结构,使用dbscan软件包计算细胞间距离[半径(r)=300μm]。免疫细胞簇定义为100μm内≥3个免疫细胞组成的群体,并通过基于密度的算法进行识别。该空间聚类同时使用ST和多重免疫组织化学(mIHC)数据进行评估。分析了细胞间相互作用(邻域)(r=25μm)。使用基于空间邻域的方法评估配体-受体相互作用。
结果:27例aHCC的ST产生了460万个细胞。在应答者中,CD8_Tex和Temra以及Macro_CXCL10细胞定位于肿瘤内部并更靠近癌细胞(分别为p=0.02、p=0.08和p=0.1)。此外,在应答者中,肿瘤肝细胞表现出显著富集的淋巴样邻域组成以及显著更高的免疫招募相互作用率,包括PDL1-PD1、CXCL9-CXCR3和CXCL10-CXCR3(p<0.05)。无应答者富集于含TREM2⁺巨噬细胞的簇。具体而言,他们表现出Macro_TREM2纯簇(10% vs 0%,p=0.009)、混合Macro_TREM2-Mono_CD14簇(27% vs 5%,p=0.03)以及混合Macro_TREM2-CD8⁺ T细胞簇(38% vs 22%,p=0.04)。这伴随着CXCL12-CXCR4趋化因子轴的富集,与免疫抑制性TME一致。使用mIHC,我们确认了Macro_TREM2纯簇(p=0.02)和Macro_TREM2-CD8⁺混合簇(p=0.03)的富集。
结论:HCC中atezo+bev的应答以肿瘤内效应CD8⁺ T细胞和CXCL10_Macro、富集于淋巴样邻域的肿瘤肝细胞以及免疫招募的配体-受体相互作用为特征,而耐药则由TREM2_Macro簇和CXCL12-CXCR4信号驱动。这些发现确定了空间免疫组织是atezo+bev应答的关键决定因素。
查看英文原文 English abstract
Background: Atezolizumab+bevacizumab (atezo+bev) is a first-line therapy for advanced hepatocellular carcinoma (aHCC) with ~30% objective responses. Single-cell studies identified responses linked to CD8⁺ T effector cells (CD8_Tex and Temra) and CXCL10⁺ macrophages (Macro_CXCL10), and resistance to TREM2⁺ macrophages (Macro_TREM2) and CD14⁺ monocytes (Mono_CD14). We hypothesized that, beyond cell composition, immune spatial organization within the tumor microenvironment (TME) determines response to atezo+bev.
Methods: Single-cell spatial transcriptomics (ST) was performed on 27 aHCCs (9 atezo+bev responders and 18 resistant) using the Xenium Prime 5.000-gene panel (10x Genomics) customized with 100 additional genes. For local tissue organization, distances between cells were computed using the dbscan package [radius(r)=300µm]. Immune cell clusters were defined as groups of ≥3 immune cells within 100 µm, and were identified through a density-based algorithm. This spatial clustering was assessed using both ST and multiplexed immunohistochemistry (mIHC) data. Cell-to-cell interactions (neighborhoods) were analyzed (r=25µm). Ligand-receptor interactions were evaluated using a spatial neighborhood-based approach.
Results: ST of 27 aHCCs yielded 4.6 million cells. In responders, CD8_Tex and Temra, and Macro_CXCL10 cells localized within the tumor and were closer to cancer cells ( p=0.02 , p=0.08 , and p=0.1 , respectively). Furthermore, in responders, tumor hepatocytes exhibited a significantly enriched lymphoid neighborhood composition and significantly higher rates of immune-recruting interactions, including PDL1-PD1, CXCL9-CXCR3 and CXCL10-CXCR3 (p<0.05). Non-responders were enriched in TREM2⁺ macrophage-containing clusters. Specifically, they showed Macro_TREM2-pure clusters (10% vs 0%, p=0.009), mixed Macro_TREM2-Mono_CD14 clusters (27% vs 5%, p=0.03), and mixed Macro_TREM2-CD8⁺ T-cell clusters (38% vs 22%, p=0.04). This was accompanied by enrichment of the CXCL12-CXCR4 chemokine axis, consistent with an immunosuppressive TME. Using mIHC, we confirmed enrichment of Macro_TREM2-pure (p=0.02) and Macro_TREM2-CD8⁺ mixed clusters (p=0.03).
Conclusions: Atezo+bev response in HCC is marked by intratumoral effector CD8⁺ T cells and CXCL10_Macro, tumor hepatocytes enriched in lymphoid neighborhoods, and immune-recruiting ligand-receptor interactions, whereas resistance is driven by TREM2_Macro clusters and CXCL12-CXCR4 signaling. These findings identify spatial immune organization as a key determinant of response to atezo+bev.
利益披露 Disclosure
A. Vila-Escoda, None..
M. Piqué-Gili, None..
M. Casado-Pelaez, None..
R. Pinyol, None..
A. Hernández de Sande, None..
V. Davalos, None..
A. Gris-Oliver, None..
C. Montironi, None..
J. Peix, None..
D. Grases, None..
E. Mauro, None..
G. Cano-Segarra, None..
S. Cappuyns, None..
I. Figueiredo, None..
G. Ioannou, None..
E. Gonzalez-Kozlova, None..
T. Meyer, None..
A. Lachenmayer, None..
J. Marquardt, None..
H. Reeves, None..
J. Edeline, None..
F. Finkelmeier, None..
J. Trojan, None..
S. Gnjatic, None..
J. Blanc, None..
R. Hubner, None.
M. Pinter,
AstraZeneca Other, speaker honoraria
consultant/advisory board member.
Bayer Other, speaker honoraria
consultant/advisory board member.
BMS Other, speaker honoraria
consultant/advisory board member.
Eisai Other, speaker honoraria
consultant/advisory board member.
Ipsen Other, speaker honoraria
consultant/advisory board member.
Lilly Other, speaker honoraria
consultant/advisory board member.
MSD Other, speaker honoraria
consultant/advisory board member.
Roche speaker honoraria
consultant/advisory board member.
T. Luedde, None..
A. Vogel, None..
D. Sia, None..
V. Mazzaferro, None..
M. Esteller, None..
J. Dekervel, None..
E. Porta-Pardo, None.
J. Llovet,
Genentech Other, Consultancy/Sponsored Lectures.
Roche Other, Consultancy / Sponsored Lectures.
Eisai inc Other, Consultancy / Sponsored Lectures.
Merck Other, Consultancy / Sponsored Lectures.
Astrazeneca Other, Consultancy / Sponsored Lectures.
Bayer Pharmaceuticals Other, Consultancy / Sponsored Lectures.
Abbvie Other, Consultancy / Sponsored Lectures.
Sanofi Other, Consultancy / Sponsored Lectures.
Moderna Other, Consultancy / Sponsored Lectures.
Glycotest Other, Consultancy / Sponsored Lectures.
Exelixis Other, Consultancy / Sponsored Lectures.
Boehringer Ingelheim Other, Consultancy / Sponsored Lectures.
Brystol Myers Squibb Other, Data Safety Monitoring Board for Industry or commercial enterprise.