Circulating tumor DNA guided adjuvant chemotherapy in stage II colon cancer (MEDOCC-CrEATE):study protocol for a trial within a cohort study

BACKGROUND: Accurate detection of patients with minimal residual disease (MRD) after surgery for stage II colon cancer (CC) remains an urgent unmet clinical need to improve selection of patients who might benefit form adjuvant chemotherapy (ACT). Presence of circulating tumor DNA (ctDNA) is indicative for MRD and has high predictive value for recurrent disease. The MEDOCC-CrEATE trial investigates how many stage II CC patients with detectable ctDNA after surgery will accept ACT and whether ACT reduces the risk of recurrence in these patients. METHODS/DESIGN: MEDOCC-CrEATE follows the 'trial within cohorts' (TwiCs) design. Patients with colorectal cancer (CRC) are included in the Prospective Dutch ColoRectal Cancer cohort (PLCRC) and give informed consent for collection of clinical data, tissue and blood samples, and consent for future randomization. MEDOCC-CrEATE is a subcohort within PLCRC consisting of 1320 stage II CC patients without indication for ACT according to current guidelines, who are randomized 1:1 into an experimental and a control arm. In the experimental arm, post-surgery blood samples and tissue are analyzed for tissue-informed detection of plasma ctDNA, using the PGDx elio™ platform. Patients with detectable ctDNA will be offered ACT consisting of 8 cycles of capecitabine plus oxaliplatin while patients without detectable ctDNA and patients in the control group will standard follow-up according to guideline. The primary endpoint is the proportion of patients receiving ACT when ctDNA is detectable after resection. The main secondary outcome is 2-year recurrence rate (RR), but also includes 5-year RR, disease free survival, overall survival, time to recurrence, quality of life and cost-effectiveness. Data will be analyzed by intention to treat. DISCUSSION: The MEDOCC-CrEATE trial will provide insight into the willingness of stage II CC patients to be treated with ACT guided by ctDNA biomarker testing and whether ACT will prevent recurrences in a high-risk population. Use of the TwiCs design provides the opportunity to randomize patients before ctDNA measurement, avoiding ethical dilemmas of ctDNA status disclosure in the control group. TRIAL REGISTRATION: Netherlands Trial Register: NL6281/NTR6455 . Registered 18 May 2017, https://www.trialregister.nl/trial/6281

imPlatelet classifier: image-converted RNA biomarker profiles enable blood-based cancer diagnostics

Liquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia of Genes and Genomes was also implemented to improve accuracy. Images obtained from samples can then be compared against standard images for specific cancers to determine a diagnosis. We tested imPlatelet on a cohort of 401 non-small cell lung cancer patients, 62 sarcoma patients, and 28 ovarian cancer patients. imPlatelet provided excellent discrimination between lung cancer cases and healthy controls, with accuracy equal to 1 in the independent dataset. When discriminating between noncancer cases and sarcoma or ovarian cancer patients, accuracy equaled 0.91 or 0.95, respectively, in the independent datasets. According to our knowledge, this is the first study implementing an image-based deep-learning approach combined with biological knowledge to classify human samples. The performance of imPlatelet considerably exceeds previously published methods and our own alternative attempts of sample discrimination. We show that the deep-learning image-based classifier accurately identifies cancer, even when a limited number of samples are available.publishedVersio

Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.BACKGROUND: There are multiple existing and emerging therapeutic avenues for metastatic prostate cancer, with a common denominator, which is the need for predictive biomarkers. Circulating tumor DNA (ctDNA) has the potential to cost-efficiently accelerate precision medicine trials to improve clinical efficacy and diminish costs and toxicity. However, comprehensive ctDNA profiling in metastatic prostate cancer to date has been limited. METHODS: A combination of targeted and low-pass whole genome sequencing was performed on plasma cell-free DNA and matched white blood cell germline DNA in 364 blood samples from 217 metastatic prostate cancer patients. RESULTS: ctDNA was detected in 85.9% of baseline samples, correlated to line of therapy and was mirrored by circulating tumor cell enumeration of synchronous blood samples. Comprehensive profiling of the androgen receptor (AR) revealed a continuous increase in the fraction of patients with intra-AR structural variation, from 15.4% during first-line metastatic castration-resistant prostate cancer therapy to 45.2% in fourth line, indicating a continuous evolution of AR during the course of the disease. Patients displayed frequent alterations in DNA repair deficiency genes (18.0%). Additionally, the microsatellite instability phenotype was identified in 3.81% of eligible samples (≥ 0.1 ctDNA fraction). Sequencing of non-repetitive intronic and exonic regions of PTEN, RB1, and TP53 detected biallelic inactivation in 47.5%, 20.3%, and 44.1% of samples with ≥ 0.2 ctDNA fraction, respectively. Only one patient carried a clonal high-impact variant without a detectable second hit. Intronic high-impact structural variation was twice as common as exonic mutations in PTEN and RB1. Finally, 14.6% of patients presented false positive variants due to clonal hematopoiesis, commonly ignored in commercially available assays. CONCLUSIONS: ctDNA profiles appear to mirror the genomic landscape of metastatic prostate cancer tissue and may cost-efficiently provide somatic information in clinical trials designed to identify predictive biomarkers. However, intronic sequencing of the interrogated tumor suppressors challenges the ubiquitous focus on coding regions and is vital, together with profiling of synchronous white blood cells, to minimize erroneous assignments which in turn may confound results and impede true associations in clinical trials.The Belgian Foundation Against Cancer (grant number C/2014/227); Kom op tegen Kanker (Stand up to Cancer), the Flemish Cancer Society (grant number 00000000116000000206); Royal College of Surgeons/Cancer Research UK (C19198/A1533); The Cancer Research Funds of Radiumhemmet, through the PCM program at KI (grant number 163012); The Erling-Persson family foundation (grant number 4-2689-2016); the Swedish Research Council (grant number K2010-70X-20430-04-3), and the Swedish Cancer Foundation (grant number 09-0677)

White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

Contains fulltext : 216706.pdf (publisher's version ) (Open Access