{Reference Type}: Journal Article
{Title}: Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy.
{Author}: Yaniz-Galende E;Zeng Q;Bejar-Grau JF;Klein C;Blanc-Durand F;Le Formal A;Pujade-Lauraine E;Chardin L;Edmond E;Marty V;Ray-Coquard I;Joly F;Ferron G;Pautier P;Berton-Rigaud D;Lortholary A;Dohollou N;Desauw C;Fabbro M;Malaurie E;Bonichon-Lamaichhane N;Bello Roufai D;Gantzer J;Rouleau E;Genestie C;Leary A;
{Journal}: Clin Cancer Res
{Volume}: 30
{Issue}: 13
{Year}: 2024 Jul 1
{Factor}: 13.801
{DOI}: 10.1158/1078-0432.CCR-23-3836
{Abstract}: UNASSIGNED: This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes.
UNASSIGNED: Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322).
UNASSIGNED: Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent.
UNASSIGNED: Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1-resistant malignancy.