Project description:DNA methylation in colorectal cancer diagnosis. The Illumina GoldenGate Methylation Cancer Panel I was used to select a set of candidates markers informative of colorectal cancer diagnosis from 807 cancer-related genes. In the discovery phase, tumor tissue and paired adjacent normal mucosa from 92 colorectal patients were analyzed.
Project description:Purpose: Using the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial samples, we identified cell-free DNA (cfDNA) biomarker candidate genes bearing the epigenetic mark 5-hydroxymethylcytosine (5hmC) that detect occult colorectal cancer (CRC) up to 36 mo prior to clinical diagnosis. Methods: PLCO study subjects were matched by age, race, and sex as cases (n = 201, diagnosed with CRC within 36 mo of blood collection) and controls (n = 402, no cancer diagnosis on follow-up, average 16.3 years after entering the study). Archived plasma samples (300 µL per study subject) were obtained from the National Cancer Institute (NCI), and we employed the sensitive 5hmC-Seal chemical labeling approach on 3 - 8 ng of extracted cfDNA. Following next-generation sequencing (NGS) and genome-wide mapping of 5hmC, we then conducted association studies and machine-learning modeling to analyze the genome-wide 5hmC profiles within training and validation groups that were randomly selected at a 2:1 ratio. Results: Robust genome-wide 5hmC profiles were successfully obtained from these decades-old samples. Association analyses using the Cox proportional hazards models suggested several epigenetic pathways relevant to CRC development distinguishing cases from controls. A weighted Cox model, comprised of 32-associated gene bodies, showed predictive detection value for CRC as early as 24-36 mo prior to overt tumor diagnosis. Furthermore, a trend for increased predictive power was observed for blood samples collected closer to CRC diagnosis. Notably, the 5hmC-based predictive model showed comparable performance regardless of sex and self-reported race/ethnicity, and significantly outperformed risk factors such as age and obesity assessed as BMI (body mass index). Conclusion: An assay and machine learning modeling of 5hmC epigenetic signals on cfDNA revealed candidate biomarkers and a scoring algorithm with the potential to predict CRC occurrence despite the absence of clinical symptoms or the availability of effective predictors. Developing a minimally-invasive clinical assay that detects 5hmC-modified biomarkers holds promise for improving early CRC detection and ultimately patient outcomes. Future investigations to expand this strategy to prospectively collected samples are warranted.
Project description:DNA methylation in colorectal cancer diagnosis. The Illumina GoldenGate Methylation Cancer Panel I was used to select a set of candidates markers informative of colorectal cancer diagnosis from 807 cancer-related genes. In the discovery phase, tumor tissue and paired adjacent normal mucosa from 92 colorectal patients were analyzed. Bisulphite converted DNA from 92 colorectal tumor samples and paired adjacent normal mucosa were hybridised to the Illumina GoldenGate Methylation Cancer Panel I. Additionally, replicates were hybridised for five tumor tissue and their corresponding normal mucosa for reproducibility purposes, totalling 194 samples. Three samples (SAMPLEs 49, 51, and 162) and 50 loci did not reach the quality criteria required regarding the signal-to-noise ratio and were therefore excluded from further analysis. One additional non-tumoral sample (SAMPLE 15) was removed because it exhibited a methylation pattern quiet different from that shown by the rest of normal specimens, which could be indicative of hybridization errors. These Samples and loci are included in the raw data matrix to allow other investigators to use them if different criteria are applied. They have been also included in the Sample tables with missing values in order to preserve the structure of the data across records/files (See 'data processing' section for more details).
Project description:The present study explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide potential biomarkers for their use in non-invasive screening strategies for the early detection of lung cancer (LC). EBC was collected from 192 individuals (49 control volunteers, 49 risk factor-smoking volunteers, 46 chronic obstructive pulmonary disease patients and 48 LC patients). Using LC-MS/MS a total of 348 different proteins with a different pattern among the four groups were identified in EBC samples. Despite the great variability observed among individuals, significantly more proteins were identified in the EBC from LC patients compared to other groups. Furthermore, the average number of proteins identified per sample was significantly higher in LC patients and Receiver Operating Characteristic curve analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histone isoforms, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples and levels of KRT6A, KRT6B and KRT6C isoforms were significantly higher in samples from LC patients. Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC. Thus, this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer.
Project description:We have used Illumina Infinium HumanMethylation450 BeadChip array profiling to profile paediatric high grade gliomas within the HERBY clinical trial. The HERBY trial was a phase-II open-label, randomised, multicentre trial evaluating bevacizumab in patients with newly-diagnosed non-brainstem HGG between the ages of 3-18yrs. The 450K methylation array was used to separate brain tumour samples on the basis of their methylation profiles which represent the cell of origin the time and place in which tumours arise. Methylation arrays provide data for an integrated molecular diagnosis of brain tumours and define specific molecular subgroups and subtypes of high grade gliomas carrying distinct driver mutations and patterns of somatic alterations.
Project description:Proteome characterization of the neoadjuvant clinical trial PROMIX.
https://www.clinicaltrials.gov/ct2/show/NCT00957125
Patients received six rounds of chemotherapy with epirubicin and docetaxel, and if PR or PD after the second course, bevacizumab.
Project description:CAMILLA is a basket trial (NCT03539822) evaluating cabozantinib plus the ICI durvalumab in chemorefractory gastrointestinal cancer. Herein, are the phase II colorectal cohort results. 29 patients were evaluable. 100% had confirmed pMMR/MSS tumors. Primary endpoint was met with ORR of 27.6% (95% CI 12.7-47.2%). Secondary endpoints of 4-month PFS rate was 44.83% (95% CI 26.5-64.3%); and median OS was 9.1 months (95% CI 5.8-20.2). Grade≥3 TRAE occurred in 39%. In post-hoc analysis of patients with RAS wild type tumors, ORR was 50% and median PFS and OS were 6.3 and 21.5 months respectively. Exploratory spatial transcriptomic profiling of pretreatment tumors showed upregulation of VEGF and MET signaling, increased extracellular matrix activity and pre-existing anti-tumor immune responses coexisting with immune suppressive features like T cell migration barriers in responders versus non-responders. Cabozantinib plus durvalumab demonstrated anti-tumor activity, manageable toxicity, and have led to the activation of the phase III STELLAR-303 trial.