Liquid biopsy based on cell-free DNA (cfDNA) enables non-invasive dynamic assessment of disease status in patients with cancer, both in the early and advanced settings. The analysis of DNA-methylation (DNAm) from cfDNA samples holds great promise due to the intrinsic characteristics of DNAm being more prevalent, pervasive, and cell- and tumor-type specific than genomics, for which established cfDNA assays already exist. Herein, we report on recent advances on experimental strategies for the analysis of DNAm in cfDNA samples. We describe the main steps of DNAm-based analysis workflows, including pre-analytics of cfDNA samples, DNA treatment, assays for DNAm evaluation, and methods for data analysis. We report on protocols, biomolecular techniques, and computational strategies enabling DNAm evaluation in the context of cfDNA analysis, along with practical considerations on input sample requirements and costs. We provide an overview on existing studies exploiting cell-free DNAm biomarkers for the detection and monitoring of cancer in early and advanced settings, for the evaluation of drug resistance, and for the identification of the cell-of-origin of tumors. Finally, we report on DNAm-based tests approved for clinical use and summarize their performance in the context of liquid biopsy.

New single-cell isolation technologies are facilitating studies on the transcriptomics of individual cells. Bio-Rad ddSEQ is a droplet-based microfluidic system that, when coupled with downstream Illumina library preparation and sequencing, enables the monitoring of thousands of genes per cell. Sequenced reads show unique features that do not permit the use of freely available tools to perform single cell demultiplexing. We present ddSeeker, a tool to perform initial processing and quality metrics of reads generated through Bio-Rad ddSEQ/Illumina experiments. Its application to the Illumina test dataset demonstrates that ddSeeker performs better than Illumina BaseSpace software, enabling a higher recovery of valid reads. We also show its utility in the analysis of an in-house dataset including two read sets characterized by low and high sequencing quality. ddSeeker and its source code are available at https://github.com/cgplab/ddSeeker . ddSeeker is a freely available tool to perform initial processing and quality metrics of reads generated through Bio-Rad ddSEQ/Illumina single cell transcriptomic experiments.

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

Currently, there is limited data regarding the effectiveness of standard subsequent line therapies such as endocrine therapy, chemotherapy, or targeted agents after progression on CDK4/6 inhibitor-based regimens. This paper describes time-to-treatment failure beyond progression on palbociclib or palbociclib+endocrine therapy in patients enrolled in the phase II, multicenter TREnd trial. Our results indicate that there is limited benefit from post-palbociclib treatment, regardless of the type of therapy received. A small population of long responders were identified who demonstrated ongoing benefit from a subsequent line of endocrine therapy after progression to palbociclib-based regimens. A translational research program is ongoing on this population of outliers.

Differentially DNA methylated regions (DMRs) inform on the role of epigenetic changes in cancer. We present Rocker-meth, a new computational method exploiting a heterogeneous hidden Markov model to detect DMRs across multiple experimental platforms. Through an extensive comparative study, we first demonstrate Rocker-meth excellent performance on synthetic data. Its application to more than 6,000 methylation profiles across 14 tumor types provides a comprehensive catalog of tumor type-specific and shared DMRs, and agnostically identifies cancer-related partially methylated domains (PMD). In depth integrative analysis including orthogonal omics shows the enhanced ability of Rocker-meth in recapitulating known associations, further uncovering the pan-cancer relationship between DNA hypermethylation and transcription factor deregulation depending on the baseline chromatin state. Finally, we demonstrate the utility of the catalog for the study of colorectal cancer single-cell DNA-methylation data.

We aim to elucidate the prognostic value of PIK3CA mutations and copy number (CN) gain (PIK3CA-mut/gain) in hormone receptor-positive and HER2-negative (HR + /HER2−) breast cancer (BC). We analyzed primary HR + /HER2− BC from three publicly available datasets comprising over 2000 samples and assessed the associations with tumoral and clinical characteristics and outcome. Clinical benefit (CB) in alpelisib-treated patients from two studies including 46 patients was analyzed. About 8–10% of HR + /HER2− primary BC had PIK3CA-mut/gain. In two of the datasets analyzed, among patients with PIK3CA mutant tumors, those with mut/gain had significantly worse outcome compared to those with CN neutral (PIK3CA-mut/neut) and PIK3CA-mut/gain remained an independent prognostic factor. CB of alpelisib-treated patients with PIK3CA-mut/gain and PIK3CA-mut/neut tumors was comparable. PIK3CA CN might help clarifying the prognostic and predictive role of PIK3CA mutations. Further studies are warranted.