Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis.

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

Real-time analysis of the cancer genome and fragmentome from plasma and urine cell-free DNA using nanopore sequencing.

Cell-free DNA (cfDNA) can be isolated and sequenced from blood and/or urine of cancer patients. Conventional short-read sequencing lacks deployability and speed and can be biased for short cfDNA fragments. Here, we demonstrate that with Oxford Nanopore Technologies (ONT) sequencing we can achieve delivery of genomic and fragmentomic data from liquid biopsies. Copy number aberrations and cfDNA fragmentation patterns can be determined in less than 24 h from sample collection. The tumor-derived cfDNA fraction calculated from plasma of lung cancer patients and urine of bladder cancer patients was highly correlated (R = 0.98) with the tumor fraction calculated from short-read sequencing of the same samples. cfDNA size profile, fragmentation patterns, fragment-end composition, and nucleosome profiling near transcription start sites in plasma and urine exhibited the typical cfDNA features. Additionally, a high proportion of long tumor-derived cfDNA fragments (> 300 bp) are recovered in plasma and urine using ONT sequencing. ONT sequencing is a cost-effective, fast, and deployable approach for obtaining genomic and fragmentomic results from liquid biopsies, allowing the analysis of previously understudied cfDNA populations.

The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection.

BACKGROUND: Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection. RESULTS: We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81. CONCLUSIONS: The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.

Tumor-educated platelet blood tests for Non-Small Cell Lung Cancer detection and management.

Liquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Discrimination Between Pre- and Postcapillary Pulmonary Hypertension Using Platelet RNA.

Background Appropriate treatment of pulmonary hypertension (PH) is critically dependent on accurate discrimination between pre- and postcapillary PH. However, clinical discrimination is challenging and frequently requires a right heart catheterization. Existing risk scores to detect postcapillary PH have suboptimal discriminatory strength. We have previously shown that platelet-derived RNA profiles may have diagnostic value for PH detection. Here, we hypothesize that platelet-derived RNAs can be employed to select unique biomarker panels for the discrimination between pre- and postcapillary PH. Methods and Results Blood platelet RNA from whole blood was isolated and sequenced from 50 patients with precapillary PH (with different PH subtypes) as well as 50 patients with postcapillary PH. RNA panels were calculated by ANOVA statistics, and classifications were performed using a support vector machine algorithm, supported by particle swarm optimization. We identified in total 4279 different RNAs in blood platelets from patients with pre- and postcapillary PH. A particle swarm optimization-selected RNA panel of 1618 distinctive RNAs with differential levels together with a trained support vector machine algorithm accurately discriminated patients with precapillary PH from patients with postcapillary PH with 100% sensitivity, 60% specificity, 80% accuracy, and 0.95 (95% CI, 0.86-1.00) area under the curve in the independent validation series (n=20). Conclusions This proof-of-concept study demonstrates that particle swarm optimization/support vector machine-enhanced classification of platelet RNA panels may be able to discriminate precapillary PH from postcapillary PH. This research provides a foundation for the development of a blood test with a high negative predictive value that would improve early diagnosis of precapillary PH and prevents unnecessary invasive testing in patients with postcapillary PH.

Platelet RNA sequencing for cancer screening in patients with unprovoked venous thromboembolism: a prospective cohort study.

BACKGROUND: Platelet RNA sequencing has been shown to accurately detect cancer in previous studies. OBJECTIVES: To compare the diagnostic accuracy of platelet RNA sequencing with standard-of-care limited cancer screening in patients with unprovoked venous thromboembolism (VTE). METHODS: Patients aged ≥40 years with unprovoked VTE were recruited at 13 centers and followed for 12 months for cancer. Participants underwent standard-of-care limited cancer screening, and platelet RNA sequencing analysis was performed centrally at study end for cases and selected controls. Sensitivity and specificity were calculated, using the predefined primary positivity threshold of 0.54 for platelet RNA sequencing aiming at 86% test sensitivity, and an additional predefined threshold of 0.89 aiming at 99% test specificity. RESULTS: A total of 476 participants were enrolled, of whom 25 (5.3%) were diagnosed with cancer during 12-month follow-up. For each cancer patient, 3 cancer-free patients were randomly selected for the analysis. The sensitivity of limited screening was 72% (95% CI, 52-86) at a specificity of 91% (95% CI, 82-95). The area under the receiver operator characteristic for platelet RNA sequencing was 0.54 (95% CI, 0.41-0.66). At the primary positivity threshold, all patients had a positive test, for a sensitivity estimated at 100% (95% CI, 87-99) and a specificity of 8% (95% CI, 3.7-16.4). At the secondary threshold, sensitivity was 68% (95% CI, 48-83; p value compared with limited screening 0.71) at a specificity of 36% (95% CI, 26-47). CONCLUSION: Platelet RNA sequencing had poor diagnostic accuracy for detecting occult cancer in patients with unprovoked VTE with the current algorithm.

Detection and localization of early- and late-stage cancers using platelet RNA.

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I-IV cancer patients and in half of 352 stage I-III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.

Distinct Platelet Ribonucleic Acid Signatures in Patients with Pulmonary Hypertension.

Rationale: Pulmonary hypertension encompasses progressive disorders leading to right ventricular dysfunction and early death. Late detection is an important cause of poor clinical outcomes. However, biomarkers that accurately predict the presence of pulmonary hypertension are currently lacking. Objectives: In this study, we provide evidence that blood platelets contain a distinctive ribonucleic acid (RNA) profile that may be exploited for the detection of pulmonary hypertension. Methods: Blood platelet RNA was isolated prospectively from 177 prevalent patients with different subtypes of pulmonary hypertension as well as 195 control subjects clinically not suspected of pulmonary hypertension. Sequencing libraries were created using SMARTer (Switching Mechanism at 5' end of RNA Template) copy desoxyribonucleic acid amplification and sequenced on the Illumina High Throughput Sequencing platform. RNA-sequencing reads were mapped to the human reference genome, and intron-spanning spliced RNA reads were selected. Differential spliced RNA panels were calculated by analysis of variance statistics. A particle swarm optimization-enhanced classification algorithm was built employing a development (n = 213 samples) and independent validation series (n = 159 samples). Results: We detected a total of 4,014 different RNAs in blood platelets from patients with pulmonary hypertension (n = 177) and asymptomatic control subjects (n = 195). Gene ontology analysis revealed enhanced RNA concentrations for genes related to RNA processing, translation, and mitochondrial function. A particle swarm optimization-selected RNA panel of 408 distinctive differentially spliced RNAs mediated detection of pulmonary hypertension with 93% sensitivity, 62% specificity, 77% accuracy, 0.89 (95% confidence interval, 0.83-0.93) area under the curve, and a negative predictive value of 91% in the independent validation series. The prediction score was independent of age, sex, smoking, pulmonary hypertension subtype, and the use of pulmonary hypertension-specific medication or anticoagulants. Conclusions: A platelet RNA panel may accurately discriminate patients with pulmonary hypertension from asymptomatic control subjects. In the light of current diagnostic delays, this study is the starting point for further development and evaluation of a platelet RNA-based blood test to ultimately improve early diagnosis and clinical outcomes in patients with pulmonary hypertension.

The Effect of Preanalytical and Physiological Variables on Cell-Free DNA Fragmentation.

BACKGROUND: Assays that account for the biological properties and fragmentation of cell-free DNA (cfDNA) can improve the performance of liquid biopsy. However, preanalytic and physiological differences between individuals on fragmentomic analysis are poorly defined. METHODS: We analyzed the impact of collection tube, plasma processing time, and physiology on the size distribution of cfDNA, their genome-wide representation, and sequence diversity at the cfDNA fragment ends using shallow whole-genome sequencing. RESULTS: Neither different stabilizing collection tubes nor processing times affected the cfDNA fragment sizes, but could impact the genome-wide fragmentation patterns and fragment-end sequences of cfDNA. In addition, beyond differences depending on the gender, the physiological conditions tested between 63 individuals (age, body mass index, use of medication, and chronic conditions) minimally influenced the outcome of fragmentomic methods. CONCLUSIONS: Fragmentomic approaches have potential for implementation in the clinic, pending clear traceability of analytical and physiological factors.

Tumor-Educated Platelet RNA for the Detection and (Pseudo)progression Monitoring of Glioblastoma.

Tumor-educated platelets (TEPs) are potential biomarkers for cancer diagnostics. We employ TEP-derived RNA panels, determined by swarm intelligence, to detect and monitor glioblastoma. We assessed specificity by comparing the spliced RNA profile of TEPs from glioblastoma patients with multiple sclerosis and brain metastasis patients (validation series, n = 157; accuracy, 80%; AUC, 0.81 [95% CI, 0.74-0.89; p < 0.001]). Second, analysis of patients with glioblastoma versus asymptomatic healthy controls in an independent validation series (n = 347) provided a detection accuracy of 95% and AUC of 0.97 (95% CI, 0.95-0.99; p < 0.001). Finally, we developed the digitalSWARM algorithm to improve monitoring of glioblastoma progression and demonstrate that the TEP tumor scores of individual glioblastoma patients represent tumor behavior and could be used to distinguish false positive progression from true progression (validation series, n = 20; accuracy, 85%; AUC, 0.86 [95% CI, 0.70-1.00; p < 0.012]). In conclusion, TEPs have potential as a minimally invasive biosource for blood-based diagnostics and monitoring of glioblastoma patients.