Immune Modeling Analysis Reveals Immunologic Signatures Associated With Improved Outcomes in High Grade Serous Ovarian Cancer

Abstract

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy worldwide, as patients are typically diagnosed at a late stage and eventually develop chemoresistant disease following front-line platinum-taxane based therapy. Only modest results have been achieved with PD-1 based immunotherapy in ovarian cancer patients, despite the fact that immunological responses are observed in EOC patients. Therefore, the goal of this present study was to identify novel immune response genes and cell subsets significantly associated with improved high grade serous ovarian cancer (HGSOC) patient prognosis. A transcriptomic-based immune modeling analysis was employed to determine levels of 8 immune cell subsets, 10 immune escape genes, and 22 co-inhibitory/co-stimulatory molecules in 26 HGSOC tumors. Multidimensional immune profiling analysis revealed CTLA-4, LAG-3, and Tregs as predictive for improved progression-free survival (PFS). Furthermore, the co-stimulatory receptor ICOS was also found to be significantly increased in patients with a longer PFS and positively correlated with levels of CTLA-4, PD-1, and infiltration of immune cell subsets. Both ICOS and LAG-3 were found to be significantly associated with improved overall survival in The Cancer Genome Atlas (TCGA) ovarian cancer cohort. Finally, PVRL2 was identified as the most highly expressed transcript in our analysis, with immunohistochemistry results confirming its overexpression in HGSOC samples compared to normal/benign. Results were corroborated by parallel analyses of TCGA data. Overall, this multidimensional immune modeling analysis uncovers important prognostic immune factors that improve our understanding of the unique immune microenvironment of ovarian cancer.

Adaptive transcriptomic and immune infiltrate responses in the tumor immune microenvironment following neoadjuvant chemotherapy in high grade serous ovarian cancer reveal novel prognostic associations and activation of pro-tumorigenic pathways

“…reported better responses in patients with higher immunoscores in TCGA and OV.AU datasets, although this was not as striking for TCGA patients ( 30 ). However, our results here are in agreement with several other studies, including one from our own lab, that demonstrated no prognostic significance of TILs alone in pre- and/or post-NACT samples ( 10 , 18 , 23 , 24 ). Reasons for these discrepancies could be related to detection method, examination of localization and specific effector subsets of TILs in different studies, number of samples analyzed, or biological variability in patient cohorts.…”

CD4+ T cell and M2 macrophage infiltration predict dedifferentiated liposarcoma patient outcomes

“…In a recent publication by James et al, exploring immunological signatures in high-grade serous ovarian cancer, the results generated using the ImmunoPrism platform were correlated with the results from an expanded The Cancer Genome Atlas (TCGA) cohort using traditional RNA-seq differential expression analysis methods. 23 …”

“…In a recent publication by James et al, exploring immunological signatures in high-grade serous ovarian cancer, the results generated using the Immu-noPrism platform were correlated with the results from an expanded The Cancer Genome Atlas (TCGA) cohort using traditional RNA-seq differential expression analysis methods. 23 For this study, the potential analytes considered when building the Immunoscore include levels of (1) individual immune cell models (listed above, and reported as a percentage of total cell content of the tissue analyzed), (2) the total immune cell content (listed above, and reported as a percentage of the total cell content of the tissue analyzed), and (3) the expression of immune escape genes (listed above, and reported as transcripts per million, TPM).…”

Update on lymphocyte-activation gene 3 (LAG-3) in cancers: from biological properties to clinical applications

“…[96] Higher LAG-3 expression in tumor tissues is related to an adverse prognosis in most types of cancer, including pancreatic cancer, [97] high-grade soft-tissue sarcoma, [98] salivary gland carcinomas, [99] clear cell renal cell carcinoma, [100] HNSCC, [101] esophageal squamous cell carcino-ma, [52] and oral squamous cell carcinoma. [102] In contrast, higher LAG-3 expression correlates with longer survival in other types of cancer, such as high-grade serous ovarian cancer, [103] blood cancer, [104] esophageal adenocarcinoma, [105] and advanced gastric cancer. [90] Studies on the association of LAG-3 with prognosis in patients with NSCLC, colorectal cancer, and breast cancer have yielded contradictory results.…”