862 Background: Bladder cancer (BC) is a difficult and expensive cancer to treat, as lifelong care is needed. Anti-PD-1 therapies are used as a frontline treatment for BC. However, diverse response creates a need for novel methods to identify those patients that will benefit. We developed an algorithm (MIA-IO: Microscopy Image Analysis - Immunotherapy Outcome) to infer BC patient survival under anti-PD-1 immunotherapies with H&E-stained whole slide images (WSIs). Methods: A foundation model was trained on ~100k WSIs from various sources. Next, it was fine-tuned to create MIA-PDL-1, which infers PDL-1 status from H&E WSIs ( n = 1546). It was separately fine-tuned to identify tumor, stroma, necrosis and lymphocytes (training n = 2765 patches). An open-source model (CellViT) was used to identify neoplastic, inflammatory, connective, epithelial, and dead cells (training n = 190K cells). 617 features were derived from the segmentations to measure the spatial makeup of the tissues. Finally, a random survival forest (MIA-IO) was trained combining PDL-1 status, tissue/cell features, age and sex to estimate overall survival from treatment start. To develop MIA-IO, we used 331 WSIs from BC patient treated with several immunotherapies from internal trial and commercial sources (internal dataset) and 227 from a vendor as an external test set. We also evaluated MIA-IO using only patients treated with PD-1 therapies (i.e., Pembrolizumab and Nivolumab). Log-rank test was used to determine statistical significance of inferred high-risk (HR) and low-risk (LR) event times for each model. Results: The table shows survival probabilities for inferred HR and LR patient groups as stratified based on inferred death time. Survival of LR group was significantly higher than HR group for the all-immunotherapies model and for the PD-1 only therapy model in internal and external sets. Features holding greatest inference weight included texture of tumor regions and immune distributions. Cell and tissue features were found to carry the greatest estimation weight, such as texture of the tumor regions and immune distributions. Conclusions: Routine H&E biopsies may contain information prognostic of therapeutic response to immunotherapies and further study with more samples is warranted. This method is and faster than immunohistochemistry, spares additional tissue use, and may be used to select those patients that would benefit from PD-1 therapy. Survival probabilities based on algorithm stratification. Internal A Internal PD-1 External A External PD-1 Patients Train / Test ( n ) 264 / 67 157 / 39 - / 227 - / 182 MIA-IO LR / MIA-IO HR ( n ) 38 / 29 18 / 21 33 / 194 154 / 28 Overall Survival probability (LR / HR) 6-month 0.81 / 0.5 0.95 / 0.63 0.82 / 0.78 0.84 / 0.68 12-month 0.81 / 0.37 0.95 / 0.39 0.78 / 0.58 0.64 / 0.4 24-month 0.59 / 0.3 0.75 / 0.29 0.62 / 0.37 0.45 / 0.23 Log-rank test p -value 0.008 0.004 0.050 0.0182 A All patients, PD-1 PD-1 only treated cohort.
ED02-02 MicroRNAs (miRNAs) are an abundant class of endogenous small non-coding RNAs that function as negative gene regulators. We present data from integrative genomic analysis of the miRNome in human epithelial ovarian cancer including miRNA microarray, array-based comparative genomic hybridization, cDNA microarray, and tissue array. miRNA expression was markedly downregulated with malignant transformation and tumor progression. A high proportion of genomic loci containing miRNA genes exhibited DNA copy number alterations in ovarian cancer (37.1%). Copy number alterations observed in >15% tumors were considered significant. We identified 41 miRNA genes with gene copy number changes that were shared among human ovarian cancer, breast cancer and melanoma (26 with gains and 15 with losses) as well as miRNA genes with copy number changes that were unique to each tumor type. miRNA gene copy changes correlate with miRNA gene expression in ovarian cancer. Thus, genomic copy number loss may account for downregulation of ~15% of miRNA genes. Additionally, epigenetic silencing may account for downregulation of at least ~36% of miRNA genes. miRNA downregulation contributes to genome-wide transcriptional deregulation. Eight miRNAs located in chromosome 14 miRNA cluster ( Dlk1-Gtl2 domain) were downregulated in advanced relative to early stage EOC; two of them, mir-495 and mir-410, are potential tumor suppressor genes and were predicted to target a large part of protein-coding genes that are upregulated in the same cancers. Additional miRNAs were found to be significantly associated with clinical outcome in late stage EOC.
Supplementary Figure 1 from MicroRNA Microarray Identifies <i>Let-7i</i> as a Novel Biomarker and Therapeutic Target in Human Epithelial Ovarian Cancer
Supplementary Figure 1 Legend from Cancer Cell Lines as Genetic Models of Their Parent Histology: Analyses Based on Array Comparative Genomic Hybridization
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