PDL1 expression is associated with longer postoperative, survival in adrenocortical carcinoma

Abstract

Adrenocortical carcinomas (ACCs) are heterogeneous cancers associated with a very poor prognosis. The improvement of prognostic tools and systemic therapy are urgently needed. Targeting the immune system using checkpoint inhibitors such as PD1/PDL1 inhibitors is an attractive novel therapeutic strategy for poor-prognosis tumors. Multiple clinical trials are ongoing, including in advanced ACC. However, PDL1 expression has been studied in ACC in only one heterogeneous series of 28 clinical samples. Here, we have retrospectively analyzed PDL1 mRNA expression in 146 clinical ACC samples and searched for correlations between expression and biological and clinicopathological data, including post-operative disease-free survival (DFS). PDL1 mRNA expression was heterogeneous across samples. "PDL1-high" tumors were not associated with the classical prognostic variables but were associated with longer DFS in both uni-and multivariate analyses. High PDL1 mRNA expression was associated with biological signs of the cytotoxic local immune response. Supervised analysis between "PDL1-high" and "PDL1-low" tumors identified a robust 370-gene signature whose ontology analysis suggested the existence in "PDL1-high" tumors of a cytotoxic T-cell response, however, associated with some degree of T-cell exhaustion. In conclusion, PDL1 mRNA expression refines the prognostication in ACC and high expression is associated with longer DFS. Clinical validation at the protein level and functional validation are required to fully understand the role of PDL1 in ACC. Reactivation of dormant tumor-infiltrating lymphocytes by PDL1-inhibitors could represent a promising strategy in "PDL1-high" ACCs, supporting the ongoing clinical trials.

Adrenocortical Carcinoma: Updates of Clinical and Pathological Features after Renewed World Health Organisation Classification and Pathology Staging

“…In addition, large tumour size and cortisol-secreting tumour were additional factors for ACC-specific death [ 49 ]. Moreover, there are many predictive features proposed for the prognosis of patients with ACC such as mitotic grading [ 52 ], Ki-67 index [ 75 ], mi-RNAs expression [ 76 ], expression of PDL-1 [ 77 ], SF-1 [ 78 ] and sterol-O-acyl transferase 1 (SOAT1) [ 79 ]. Preliminary data also shows that for localised ACC, molecular makers (expression, methylation, and chromosome alterations) could predict cancer recurrence [ 9 ].…”

Identification of Metabolism-Associated Prostate Cancer Subtypes and Construction of a Prognostic Risk Model

“…Many cancer-promoting factors play a role in the EMT pathway (43). For instance, the expression of PDL1 can affect the prognosis of adrenocortical carcinoma (44). Regardless of stromal or immune cells, the C2 and C3 subtypes displayed more characteristics of TME.…”

Cancer-testis Antigen FATE1 Expression in Adrenocortical Tumors Is Associated with A Pervasive Autoimmune Response and Is A Marker of Malignancy in Adult, but Not Children, ACC

“…In pediatric ACC, MHC class II expression by tumor-infiltrating hematopoietic cells and the number of CD8 + T-lymphocytes are important prognostic indicators [13,20]. Even if in general only a small percentage of ACC tumor cells express PDL1, as detected by IHC [17,18], higher levels of PDL1 mRNA expression are significantly correlated with an inflammatory gene expression signature and longer DFS of adult patients with ACC [21]. Furthermore, an unpublished study from the Würzburg group has shown that the number of tumor-infiltrating CD4 + and CD8 + T-lymphocytes are stage-independent prognostic indicators in patients with ACC and that glucocorticoid excess is associated with T-cell depletion and unfavorable prognosis [22].…”

“…The three other data sets (110 ACC and 18 normal adrenal samples) were not annotated for both expression and prognostic/survival data. Data analysis required pre-analytic processing, as previously described [21]. To explore more-in-depth the biological pathways associated with FATE1 mRNA expression in ACC, we applied a supervised analysis to the whole TCGA data set as a learning set (n = 79) and compared the expression profiles of all genes between tumors with low versus high FATE1 mRNA expression using a moderated t-test with the following significance thresholds: p < 0.05, q < 0.25 and fold change (FC) higher than |2×|.…”