Ilenia Migliaccio

Cell-free DNA (cfDNA) extracted from peripheral blood has emerged as a crucial biomarker source in oncology research. To enhance the detection of somatic copy number alterations (SCNAs) and circulating tumor DNA (ctDNA), we developed eSENSES, a 2 Mb breast cancer-targeted NGS panel. It includes 15,000 genome-wide SNPs, 500 focal SNPs in breast cancer driver regions, and exons from 81 commonly altered genes, alongside a custom computational approach. We assessed the performance of eSENSES using both synthetic and clinical samples showing that eSENSES can detect ctDNA levels below 1%, exhibiting high sensitivity and specificity at 2-3% ctDNA levels. In patients with metastatic breast cancer, ctDNA estimations correlated with disease progression. When compared with other technologies and state-of-the-art approaches, eSENSES demonstrated enhanced performance. eSENSES provides a reliable, powerful and cost-effective tool for monitoring disease progression and guiding therapeutic decisions in breast cancer patients.

The cyclin-dependent kinases 4 and 6 inhibitors are the mainstay of treatment for patients with hormone receptor-positive and HER2-negative breast cancer. The ability of these drugs to improve the outcome of patients both in the metastatic and the early setting has been largely demonstrated. However, resistance, either de novo or acquired, represents a major clinical challenge. In the past years, efforts have been made to identify biomarkers that might help in a better selection of patients or to unravel the mechanisms leading to resistance in order to develop new therapeutic strategies to overcome it. Alterations of cell cycle-related genes and proteins are among the best characterized markers of resistance, and pathways impacting the cell cycle, including nuclear and growth factor receptors signaling, have been thoroughly investigated. Despite this, to date, cyclin-dependent kinases 4 and 6 inhibitors are administered based only on the hormone receptor and HER2 status of the tumor, and patients progressing on therapy are managed with currently available treatments. Here we summarize present knowledge on the cyclin-dependent kinases 4 and 6 inhibitors’ mechanisms of action, efficacy data, and mechanisms of resistance.

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.

Background: Colorectal cancer (CRC) is the fourth most commonly diagnosed and third most deadly cancer worldwide. Surgery is the main treatment option for early disease; however, a relevant proportion of CRC patients relapse. Here, variations among preoperative and postoperative serum metabolomic fingerprint of CRC patients were studied, and possible associations between metabolic variations and cancer relapse were explored. Methods: A total of 41 patients with stage I-III CRC, planned for radical resection, were enrolled. Serum samples, collected preoperatively (t0) and 4–6 weeks after surgery before the start of any treatment (t1), were analyzed via NMR spectroscopy. NMR data were analyzed using multivariate and univariate statistical approaches. Results: Serum metabolomic fingerprints show differential clustering between t0 and t1 (82–85% accuracy). Pyruvate, HDL-related parameters, acetone, and 3-hydroxybutyrate appear to be the major players in this discrimination. Eight out of the 41 CRC patients enrolled developed cancer relapse. Postoperative, relapsed patients show an increase of pyruvate and HDL-related parameters, and a decrease of Apo-A1 Apo-B100 ratio and VLDL-related parameters. Conclusions: Surgery significantly alters the metabolomic fingerprint of CRC patients. Some metabolic changes seem to be associated with the development of cancer relapse. These data, if validated in a larger cohort, open new possibilities for risk stratification in patients with early-stage CRC.

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.

CDK4/6 inhibitors (CDK4/6i) and endocrine therapy are the standard treatment for patients with hormone receptor-positive and HER2 negative (HR+/HER2−) metastatic breast cancer. Patients might show intrinsic and acquired resistance, which leads to treatment failure and progression. Circulating biomarkers have the potential advantages of recognizing patients who might not respond to treatment, monitoring treatment effects and identifying markers of acquired resistance during tumor progression with a simple withdrawal of peripheral blood. Genomic alterations on circulating tumor DNA and serum thymidine kinase activity, but also circulating tumor cells, epigenetic or exosome markers are currently being tested as markers of CDK4/6i treatment response, even though none of these have been integrated into clinical practice. In this review, we discuss the recent advancements in the development of circulating biomarkers of CDK4/6i response in patients with HR+/HER2−breast cancer.

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).

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.