Background: A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool. Patients and methods: This pre-specified substudy included 4077 participants in an independent validation set (cancer: n ¼ 2823; non-cancer: n ¼ 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured. Results: Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%). Conclusion:In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests. Clinical trial number: NCT02889978.

Purpose Tumor-infiltrating lymphocytes (TILs) have prognostic significance in many cancers, yet their roles in glioblastoma (GBM) have not been fully defined. We hypothesized TILs in GBM are associated with molecular alterations, histologies and survival. Experimental Design We used data from The Cancer Genome Atlas (TCGA) to investigate molecular, histologic and clinical correlates of TILs in GBMs. Lymphocytes were categorized as absent, present or abundant in histopathologic images from 171 TCGA GBMs. Associations were examined between lymphocytes and histologic features, mutations, copy number alterations, CpG island methylator phenotype, transcriptional class and survival. We validated histologic findings using CD3G gene expression. Results We found a positive correlation between TILs and GBMs with gemistocytes, sarcomatous cells, epithelioid cells and giant cells. Lymphocytes were enriched in the mesenchymal transcriptional class and strongly associated with mutations in NF1 and RB1. These mutations are frequent in the mesenchymal class and characteristic of gemistocytic, sarcomatous, epithelioid and giant cell histologies. Conversely, TILs were rare in GBMs with small cells and oligodendroglioma components. Lymphocytes were depleted in the classical transcriptional class and in EGFR-amplified and homozygous PTEN-deleted GBMs. These alterations are characteristic of GBMs with small cells and GBMs of the classical transcriptional class. No association with survival was demonstrated. Conclusions TILs were enriched in GBMs of the mesenchymal class, strongly associated with mutations in NF1 and RB1 and typical of histologies characterized by these mutations. Conversely, TILs were depleted in the classical class, EGFR-amplified and homozygous PTEN-deleted tumors and rare in histologies characterized by these alterations.