| Autor: |
Van Neste L; Immunis.AI, Royal Oak, MI 48067, USA., Wojno KJ; Immunis.AI, Royal Oak, MI 48067, USA., Henao R; Infinia ML, Duke University, Durham, NC 27708, USA.; Duke University, Durham, NC 27708, USA., Mane S; Yale University Center for Genomic Analysis, New Haven, CT 06511, USA., Korman H; Comprehensive Urology Center, Royal Oak, MI 48073, USA.; School of Medicine, Wayne State University, Detroit, MI 48201, USA., Hafron J; Michigan Institute of Urology, St. Clair Shores, MI 48081, USA., Kernen K; Michigan Institute of Urology, St. Clair Shores, MI 48081, USA., Tinawi-Aljundi R; Michigan Institute of Urology, St. Clair Shores, MI 48081, USA., Putzi M; Urology Austin, Austin, TX 78705, USA., Kassis AI; Immunis.AI, Royal Oak, MI 48067, USA.; Harvard Medical School, Harvard University, Boston, MA 02115, USA., Kantoff PW; Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.; Convergent Therapeutics Inc., Cambridge, MA 02138, USA. |
| Abstrakt: |
The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independent training ( n = 713) and validation ( n = 305) sets. Whole transcriptome RNA sequencing was performed on isolated phagocytic CD14+ and non-phagocytic CD2+ cells and their gene expression levels were used to develop predictive models that correlate to adverse pathologic features. The immune-transcriptomic model with the highest performance for predicting adverse pathology, based on a subtraction of the log-transformed expression signals of the two cell types, displayed an area under the curve (AUC) of the receiver operating characteristic of 0.70. The addition of biomarkers in combination with traditional clinical risk factors (age, serum prostate-specific antigen (PSA), PSA density, race, digital rectal examination (DRE), and family history) enhanced the AUC to 0.91 and 0.83 for the training and validation sets, respectively. The markers identified by this approach uncovered specific pathway associations relevant to (prostate) cancer biology. Increased phagocytic activity in conjunction with cancer-associated (mis-)regulation is also represented by these markers. Differential gene expression of circulating immune cells gives insight into the cellular immune response to early tumor development and immune surveillance. |
