Need Help?

Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001008128 Illumina HiSeq 2500 372
EGAD00001008129 Illumina HiSeq 4000 152
EGAD00001008130 1
Publications Citations
Multiomics identifies metabolic subtypes based on fatty acid degradation allocating personalized treatment in hepatocellular carcinoma.
Hepatology 79: 2024 289-306
4
PD-1<sup>-</sup> CD45RA<sup>+</sup> effector-memory CD8 T cells and CXCL10<sup>+</sup> macrophages are associated with response to atezolizumab plus bevacizumab in advanced hepatocellular carcinoma.
Nat Commun 14: 2023 7825
4
HKDC1 promotes tumor immune evasion in hepatocellular carcinoma by coupling cytoskeleton to STAT1 activation and PD-L1 expression.
Nat Commun 15: 2024 1314
3