Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing datasets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ~18,000 human tumors with overall survival outcomes across 39 malignancies. Using this resource, we identified a FOXM1 regulatory network as a major predictor of adverse outcomes, and found that expression of favorably prognostic genes, including KLRB1, largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and discover biomarkers and therapeutic targets.

Circulating tumor DNA (ctDNA) represents a promising biomarker for noninvasive assessment of cancer burden, but existing methods have insufficient sensitivity or patient coverage for broad clinical applicability. Here we introduce CAncer Personalized Profiling by deep Sequencing (CAPP-Seq), an economical and ultrasensitive method for quantifying ctDNA. We implemented CAPP-Seq for non-small cell lung cancer (NSCLC) with a design covering multiple classes of somatic alterations that identified mutations in >95% of tumors. We detected ctDNA in 100% of stage II–IV and 50% of stage I NSCLC patients, with 96% specificity for mutant allele fractions down to ~0.02%. Levels of ctDNA significantly correlated with tumor volume, distinguished between residual disease and treatment-related imaging changes, and provided earlier response assessment than radiographic approaches. Finally, we explored biopsy-free tumor screening and genotyping with CAPP-Seq. We envision that CAPP-Seq could be routinely applied clinically to detect and monitor diverse malignancies, thus facilitating personalized cancer therapy.

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by ~3 fold, and synergize when combined to yield ~15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to clinical non-small cell lung cancer (NSCLC) samples, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and 96% specificity and detection of ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

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Key Points• DLBCL can be detected in the blood by immunoglobulin high-throughput sequencing (Ig-HTS) with high specificity.• Although DLBCL can be detected in leukocytes or plasma by Ig-HTS, plasma has greater sensitivity and more accurately reflects disease.Recent studies have shown limited utility of routine surveillance imaging for diffuse large B-cell lymphoma (DLBCL) patients achieving remission. Detection of molecular disease by immunoglobulin high-throughput sequencing (Ig-HTS) from peripheral blood provides an alternate strategy for surveillance. We prospectively evaluated the utility of Ig-HTS within 311 blood and 105 tumor samples from 75 patients with DLBCL, comparing Ig-HTS from the cellular (circulating leukocytes) and acellular (plasma cell-free DNA) compartments of peripheral blood to clinical outcomes and 18 fluoro-deoxyglucose positron emission tomography combined with computed tomography (PET/CT; n 5 173). Clonotypic immunoglobulin rearrangements were detected in 83% of patients with adequate tumor samples to enable subsequent monitoring in peripheral blood. Molecular disease measured from plasma, compared with circulating leukocytes, was more abundant and better correlated with radiographic disease burden. Before treatment, molecular disease was detected in the plasma of 82% of patients compared with 71% in circulating cells (P 5 .68). However, molecular disease was detected significantly more frequently in the plasma at time of relapse (100% vs 30%; P 5 .001). Detection of molecular disease in the plasma often preceded PET/CT detection of relapse in patients initially achieving remission. During surveillance time points before relapse, plasma Ig-HTS demonstrated improved specificity (100% vs 56%, P < .0001) and similar sensitivity (31% vs 55%, P 5 .4) compared with PET/CT. Given its high specificity, Ig-HTS from plasma has potential clinical utility for surveillance after complete remission. (Blood. 2015;125(24):3679-3687)