MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples.

DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.

CHD8 suppression impacts on histone H3 lysine 36 trimethylation and alters RNA alternative splicing.

Disruptive mutations in the chromodomain helicase DNA-binding protein 8 gene (CHD8) have been recurrently associated with autism spectrum disorders (ASDs). Here we investigated how chromatin reacts to CHD8 suppression by analyzing a panel of histone modifications in induced pluripotent stem cell-derived neural progenitors. CHD8 suppression led to significant reduction (47.82%) in histone H3K36me3 peaks at gene bodies, particularly impacting on transcriptional elongation chromatin states. H3K36me3 reduction specifically affects highly expressed, CHD8-bound genes and correlates with altered alternative splicing patterns of 462 genes implicated in 'regulation of RNA splicing' and 'mRNA catabolic process'. Mass spectrometry analysis uncovered a novel interaction between CHD8 and the splicing regulator heterogeneous nuclear ribonucleoprotein L (hnRNPL), providing the first mechanistic insights to explain the CHD8 suppression-derived splicing phenotype, partly implicating SETD2, a H3K36me3 methyltransferase. In summary, our results point toward broad molecular consequences of CHD8 suppression, entailing altered histone deposition/maintenance and RNA processing regulation as important regulatory processes in ASD.

Genomic correlates of clinical outcome in advanced prostate cancer.

Heterogeneity in the genomic landscape of metastatic prostate cancer has become apparent through several comprehensive profiling efforts, but little is known about the impact of this heterogeneity on clinical outcome. Here, we report comprehensive genomic and transcriptomic analysis of 429 patients with metastatic castration-resistant prostate cancer (mCRPC) linked with longitudinal clinical outcomes, integrating findings from whole-exome, transcriptome, and histologic analysis. For 128 patients treated with a first-line next-generation androgen receptor signaling inhibitor (ARSI; abiraterone or enzalutamide), we examined the association of 18 recurrent DNA- and RNA-based genomic alterations, including androgen receptor (AR) variant expression, AR transcriptional output, and neuroendocrine expression signatures, with clinical outcomes. Of these, only RB1 alteration was significantly associated with poor survival, whereas alterations in RB1, AR, and TP53 were associated with shorter time on treatment with an ARSI. This large analysis integrating mCRPC genomics with histology and clinical outcomes identifies RB1 genomic alteration as a potent predictor of poor outcome, and is a community resource for further interrogation of clinical and molecular associations.

Circulating tumor cells and palbociclib treatment in patients with ER-positive, HER2-negative advanced breast cancer: results from a translational sub-study of the TREnd trial.

BACKGROUND: Circulating tumor cells (CTCs) are prognostic in patients with advanced breast cancer (ABC). However, no data exist about their use in patients treated with palbociclib. We analyzed the prognostic role of CTC counts in patients enrolled in the cTREnd study, a pre-planned translational sub-study of TREnd (NCT02549430), that randomized patients with ABC to palbociclib alone or palbociclib plus the endocrine therapy received in the prior line of treatment. Moreover, we evaluated RB1 gene expression on CTCs and explored its prognostic role within the cTREnd subpopulation. METHODS: Forty-six patients with ER-positive, HER2-negative ABC were analyzed. Blood samples were collected before starting palbociclib treatment (timepoint T0), after the first cycle of treatment (timepoint T1), and at disease progression (timepoint T2). CTCs were isolated and counted by CellSearch® System using the CellSearch™Epithelial Cell kit. Progression-free survival (PFS), clinical benefit (CB) during study treatment, and time to treatment failure (TTF) after study treatment were correlated with CTC counts. Samples with ≥ 5 CTCs were sorted by DEPArray system® (DA). RB1 and GAPDH gene expression levels were measured by ddPCR. RESULTS: All 46 patients were suitable for CTCs analysis. CTC count at T0 did not show significant prognostic value in terms of PFS and CB. Patients with at least one detectable CTC at T1 (n = 26) had a worse PFS than those with 0 CTCs (n = 16) (p = 0.02). At T1, patients with an increase of at least three CTCs showed reduced PFS compared to those with no increase (mPFS = 3 versus 9 months, (p = 0.004). Finally, patients with ≥ 5 CTCs at T2 (n = 6/23) who received chemotherapy as post-study treatment had a shorter TTF (p = 0.02). Gene expression data for RB1 were obtained from 19 patients. CTCs showed heterogeneous RB1 expression. Patients with detectable expression of RB1 at any timepoint showed better, but not statistically significant, outcomes than those with undetectable levels. CONCLUSIONS: CTC count seems to be a promising modality in monitoring palbociclib response. Moreover, CTC count at the time of progression could predict clinical outcome post-palbociclib. RB1 expression analysis on CTCs is feasible and may provide additional prognostic information. Results should be interpreted with caution given the small studied sample size.

Tumor Necrosis Factor α Influences Phenotypic Plasticity and Promotes Epigenetic Changes in Human Basal Forebrain Cholinergic Neuroblasts.

TNFα is the main proinflammatory cytokine implicated in the pathogenesis of neurodegenerative disorders, but it also modulates physiological functions in both the developing and adult brain. In this study, we investigated a potential direct role of TNFα in determining phenotypic changes of a recently established cellular model of human basal forebrain cholinergic neuroblasts isolated from the nucleus basalis of Meynert (hfNBMs). Exposing hfNBMs to TNFα reduced the expression of immature markers, such as nestin and ß-tubulin III, and inhibited primary cilium formation. On the contrary, TNFα increased the expression of TNFα receptor TNFR2 and the mature neuron marker MAP2, also promoting neurite elongation. Moreover, TNFα affected nerve growth factor receptor expression. We also found that TNFα induced the expression of DNA-methylation enzymes and, accordingly, downregulated genes involved in neuronal development through epigenetic mechanisms, as demonstrated by methylome analysis. In summary, TNFα showed a dual role on hfNBMs phenotypic plasticity, exerting a negative influence on neurogenesis despite a positive effect on differentiation, through mechanisms that remain to be elucidated. Our results help to clarify the complexity of TNFα effects in human neurons and suggest that manipulation of TNFα signaling could provide a potential therapeutic approach against neurodegenerative disorders.

Clinical outcomes after palbociclib with or without endocrine therapy in postmenopausal women with hormone receptor positive and HER2-negative metastatic breast cancer enrolled in the TREnd trial.

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.

Tumor purity quantification by clonal DNA methylation signatures.

Motivation: Controlling for tumor purity in molecular analyses is essential to allow for reliable genomic aberration calls, for inter-sample comparison and to monitor heterogeneity of cancer cell populations. In genome wide screening studies, the assessment of tumor purity is typically performed by means of computational methods that exploit somatic copy number aberrations. Results: We present a strategy, called Purity Assessment from clonal MEthylation Sites (PAMES), which uses the methylation level of a few dozen, highly clonal, tumor type specific CpG sites to estimate the purity of tumor samples, without the need of a matched benign control. We trained and validated our method in more than 6000 samples from different datasets. Purity estimates by PAMES were highly concordant with other state-of-the-art tools and its evaluation in a cancer cell line dataset highlights its reliability to accurately estimate tumor admixtures. We extended the capability of PAMES to the analysis of CpG islands instead of the more platform-specific CpG sites and demonstrated its accuracy in a set of advanced tumors profiled by high throughput DNA methylation sequencing. These analyses show that PAMES is a valuable tool to assess the purity of tumor samples in the settings of clinical research and diagnostics. Availability and implementation: https://github.com/cgplab/PAMES. Contact: matteo.benelli@uslcentro.toscana.it or f.demichelis@unitn.it. Supplementary information: Supplementary data are available at Bioinformatics online.

ddSeeker: a tool for processing Bio-Rad ddSEQ single cell RNA-seq data.

BACKGROUND: 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. RESULTS: 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 . CONCLUSIONS: 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.

A gene expression signature of Retinoblastoma loss-of-function predicts resistance to neoadjuvant chemotherapy in ER-positive/HER2-positive breast cancer patients.

PURPOSE: HER2-positive (HER2+) breast cancers show heterogeneous response to chemotherapy, with the ER-positive (ER+) subgroup deriving less benefit. Loss of retinoblastoma tumor suppressor gene (RB1) function has been suggested as a cardinal feature of breast cancers that are more sensitive to chemotherapy and conversely resistant to CDK4/6 inhibitors. We performed a retrospective analysis exploring RBsig, a gene signature of RB loss, as a potential predictive marker of response to neoadjuvant chemotherapy in ER+/HER2+ breast cancer patients. METHODS: We selected clinical trials of neoadjuvant chemotherapy ± anti-HER2 therapy in HER2+ breast cancer patients with available information on gene expression data, hormone receptor status, and pathological complete response (pCR) rates. RBsig expression was computed in silico and correlated with pCR. RESULTS: Ten studies fulfilled the inclusion criteria and were included in the analysis (514 patients). Overall, of 211 ER+/HER2+ breast cancer patients, 49 achieved pCR (23%). The pCR rate following chemotherapy ± anti-HER2 drugs in patients with RBsig low expression was significantly lower compared to patients with RBsig high expression (16% vs. 30%, respectively; Fisher's exact test p = 0.015). The area under the ROC curve (AUC) was 0.62 (p = 0.005). In the 303 ER-negative (ER-)/HER2+ patients treated with chemotherapy ± anti-HER2 drugs, the pCR rate was 43%. No correlation was found between RBsig expression and pCR rate in this group. CONCLUSIONS: Low expression of RBsig identifies a subset of ER+/HER2+ patients with low pCR rates following neoadjuvant chemotherapy ± anti-HER2 therapy. These patients may potentially be spared chemotherapy in favor of anti-HER2, endocrine therapy, and CDK 4/6 inhibitor combinations.

A novel founder MYO15A frameshift duplication is the major cause of genetic hearing loss in Oman.

The increased risk for autosomal recessive disorders is one of the most well-known medical implications of consanguinity. In the Sultanate of Oman, a country characterized by one of the highest rates of consanguineous marriages worldwide, prevalence of genetic hearing loss (GHL) is estimated to be 6/10 000. Families of GHL patients have higher consanguinity rates than the general Omani population, indicating a major role for recessive forms. Mutations in GJB2, the most commonly mutated GHL gene, have been sporadically described. We collected 97 DNA samples of GHL probands, affected/unaffected siblings and parents from 26 Omani consanguineous families. Analyzing a first family by whole-exome sequencing, we identified a novel homozygous frameshift duplication (c.1171_1177dupGCCATCT) in MYO15A, the gene linked to the deafness locus DFNB3. This duplication was then found in a total of 8/26 (28%) families, within a 849 kb founder haplotype. Reconstruction of haplotype structure at MYO15A surrounding genomic regions indicated that the founder haplotype branched out in the past two to three centuries from a haplotype present worldwide. The MYO15A duplication emerges as the major cause of GHL in Oman. These findings have major implications for the design of GHL diagnosis and prevention policies in Oman.

CEBPA-double-mutated acute myeloid leukemia displays a unique phenotypic profile: a reliable screening method and insight into biological features.

Mutations in CCAAT/enhancer binding protein α (CEBPA) occur in 5-10% of cases of acute myeloid leukemia. CEBPA-double-mutated cases usually bear biallelic N- and C-terminal mutations and are associated with a favorable clinical outcome. Identification of CEBPA mutants is challenging because of the variety of mutations, intrinsic characteristics of the gene and technical issues. Several screening methods (fragment-length analysis, gene expression array) have been proposed especially for large-scale clinical use; although efficient, they are limited by specific concerns. We investigated the phenotypic profile of blast and maturing bone marrow cell compartments at diagnosis in 251 cases of acute myeloid leukemia. In this cohort, 16 (6.4%) patients had two CEBPA mutations, whereas ten (4.0%) had a single mutation. First, we highlighted that the CEBPA-double-mutated subset displays recurrent phenotypic abnormalities in all cell compartments. By mutational analysis after cell sorting, we demonstrated that this common phenotypic signature depends on CEBPA-double-mutated multi-lineage involvement. From a multidimensional study of phenotypic data, we developed a classifier including ten core and widely available parameters. The selected markers on blasts (CD34, CD117, CD7, CD15, CD65), neutrophil (SSC, CD64), monocytic (CD14, CD64) and erythroid (CD117) compartments were able to cluster CEBPA-double-mutated cases. In a validation set of 259 AML cases from three independent centers, our classifier showed excellent performance with 100% specificity and 100% sensitivity. We have, therefore, established a reliable screening method, based upon multidimensional analysis of widely available phenotypic parameters. This method provides early results and is suitable for large-scale detection of CEBPA-double-mutated status, allowing gene sequencing to be focused in selected cases.

H3M2: detection of runs of homozygosity from whole-exome sequencing data.

MOTIVATION: Runs of homozygosity (ROH) are sizable chromosomal stretches of homozygous genotypes, ranging in length from tens of kilobases to megabases. ROHs can be relevant for population and medical genetics, playing a role in predisposition to both rare and common disorders. ROHs are commonly detected by single nucleotide polymorphism (SNP) microarrays, but attempts have been made to use whole-exome sequencing (WES) data. Currently available methods developed for the analysis of uniformly spaced SNP-array maps do not fit easily to the analysis of the sparse and non-uniform distribution of the WES target design. RESULTS: To meet the need of an approach specifically tailored to WES data, we developed [Formula: see text], an original algorithm based on heterogeneous hidden Markov model that incorporates inter-marker distances to detect ROH from WES data. We evaluated the performance of [Formula: see text] to correctly identify ROHs on synthetic chromosomes and examined its accuracy in detecting ROHs of different length (short, medium and long) from real 1000 genomes project data. [Formula: see text] turned out to be more accurate than GERMLINE and PLINK, two state-of-the-art algorithms, especially in the detection of short and medium ROHs. AVAILABILITY AND IMPLEMENTATION: [Formula: see text] is a collection of bash, R and Fortran scripts and codes and is freely available at https://sourceforge.net/projects/h3m2/. CONTACT: albertomagi@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutational Analysis of Circulating Tumor DNA in Patients With Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer Receiving Palbociclib: Results From the TREnd Trial.

PURPOSE: To identify prognostic circulating biomarkers to cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i), we performed a mutational analysis on circulating tumor DNA (ctDNA) samples from patients included in the TREnd trial, which randomly assigned patients to receive the CDK4/6i palbociclib alone or with the endocrine treatment (ET) to which they had progressed. METHODS: Forty-six patients were enrolled in this substudy. Plasma was collected before treatment (T0), after the first cycle of therapy (T1), and at the time of progression (T2). ctDNA hybridization and capture were performed using the Illumina TruSight Tumor 170 Kit. Acquired mutations were confirmed by digital polymerase chain reaction. Progression-free survival analysis was estimated using the Kaplan-Meier method and compared with the log-rank test. RESULTS: The most frequently mutated genes at T0 were ESR1 (23%), PIK3CA (17%), AR, FGFR2, and TP53 (10%). Mutations in ESR1 at T0 conferred higher risk of progression in the entire population (P = .02) and in patients treated with palbociclib + ET (P = .04). ESR1 mutation effect remained significant after correction for clinical variables (P = .03). PIK3CA mutations at T0 were not prognostic, but higher risk of progression was observed when a broader analysis of PI3K pathway was performed (P = .04). At T2, we observed the emergence of nine new mutations in seven genes. CONCLUSION: Mutations in ESR1 and in PI3K pathway genes at T0 were associated with worse prognosis in palbociclib-treated patients. We describe the emergence of newly acquired mutations in palbociclib-treated patients, which might potentially affect subsequent treatment.

Noninvasive Detection of Neuroendocrine Prostate Cancer through Targeted Cell-free DNA Methylation.

Castration-resistant prostate cancer (CRPC) is a heterogeneous disease associated with phenotypic subtypes that drive therapy response and outcome differences. Histologic transformation to castration-resistant neuroendocrine prostate cancer (CRPC-NE) is associated with distinct epigenetic alterations, including changes in DNA methylation. The current diagnosis of CRPC-NE is challenging and relies on metastatic biopsy. We developed a targeted DNA methylation assay to detect CRPC-NE using plasma cell-free DNA (cfDNA). The assay quantifies tumor content and provides a phenotype evidence score that captures diverse CRPC phenotypes, leveraging regions to inform transcriptional state. We tested the design in independent clinical cohorts (n = 222 plasma samples) and qualified it achieving an AUC > 0.93 for detecting pathology-confirmed CRPC-NE (n = 136). Methylation-defined cfDNA tumor content was associated with clinical outcomes in two prospective phase II clinical trials geared towards aggressive variant CRPC and CRPC-NE. These data support the application of targeted DNA methylation for CRPC-NE detection and patient stratification. SIGNIFICANCE: Neuroendocrine prostate cancer is an aggressive subtype of treatment-resistant prostate cancer. Early detection is important, but the diagnosis currently relies on metastatic biopsy. We describe the development and validation of a plasma cell-free DNA targeted methylation panel that can quantify tumor fraction and identify patients with neuroendocrine prostate cancer noninvasively. This article is featured in Selected Articles from This Issue, p. 384.

Acetyl-CoA carboxylase 1 controls a lipid droplet-peroxisome axis and is a vulnerability of endocrine-resistant ER+ breast cancer.

Targeting aromatase deprives ER+ breast cancers of estrogens and is an effective therapeutic approach for these tumors. However, drug resistance is an unmet clinical need. Lipidomic analysis of long-term estrogen-deprived (LTED) ER+ breast cancer cells, a model of aromatase inhibitor resistance, revealed enhanced intracellular lipid storage. Functional metabolic analysis showed that lipid droplets together with peroxisomes, which we showed to be enriched and active in the LTED cells, controlled redox homeostasis and conferred metabolic adaptability to the resistant tumors. This reprogramming was controlled by acetyl-CoA-carboxylase-1 (ACC1), whose targeting selectively impaired LTED survival. However, the addition of branched- and very long-chain fatty acids reverted ACC1 inhibition, a process that was mediated by peroxisome function and redox homeostasis. The therapeutic relevance of these findings was validated in aromatase inhibitor-treated patient-derived samples. Last, targeting ACC1 reduced tumor growth of resistant patient-derived xenografts, thus identifying a targetable hub to combat the acquisition of estrogen independence in ER+ breast cancers.

Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript.

MOTIVATION: The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emergence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of genomic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few computational approaches have been developed for the detection of chimeric transcripts. Although all of these computational methods show good sensitivity, much work remains to reduce the huge number of false-positive calls that arises from this analysis. RESULTS: We proposed a novel computational framework, named chimEric tranScript detection algorithm (EricScript), for the identification of gene fusion products in paired-end RNA-seq data. Our simulation study on synthetic data demonstrates that EricScript enables to achieve higher sensitivity and specificity than existing methods with noticeably lower running times. We also applied our method to publicly available RNA-seq tumour datasets, and we showed its capability in rediscovering known gene fusions.

Read count approach for DNA copy number variants detection.

MOTIVATION: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data. RESULTS: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform.

Detecting common copy number variants in high-throughput sequencing data by using JointSLM algorithm.

The discovery of genomic structural variants (SVs), such as copy number variants (CNVs), is essential to understand genetic variation of human populations and complex diseases. Over recent years, the advent of new high-throughput sequencing (HTS) platforms has opened many opportunities for SVs discovery, and a very promising approach consists in measuring the depth of coverage (DOC) of reads aligned to the human reference genome. At present, few computational methods have been developed for the analysis of DOC data and all of these methods allow to analyse only one sample at time. For these reasons, we developed a novel algorithm (JointSLM) that allows to detect common CNVs among individuals by analysing DOC data from multiple samples simultaneously. We test JointSLM performance on synthetic and real data and we show its unprecedented resolution that enables the detection of recurrent CNV regions as small as 500 bp in size. When we apply JointSLM to analyse chromosome one of eight genomes with different ancestry, we identify 3000 regions with recurrent CNVs of different frequency and size: hierarchical clustering on these regions segregates the eight individuals in two groups that reflect their ancestry, demonstrating the potential utility of JointSLM for population genetics studies.

Risk assessment of disease recurrence in early breast cancer: A serum metabolomic study focused on elderly patients.

BACKGROUND: We previously showed that metabolomics predicts relapse in early breast cancer (eBC) patients, unselected by age. This study aims to identify a "metabolic signature" that differentiates eBC from advanced breast cancer (aBC) patients, and to investigate its potential prognostic role in an elderly population. METHODS: Serum samples from elderly breast cancer (BC) patients enrolled in 3 onco-geriatric trials, were retrospectively analyzed via proton nuclear magnetic resonance (1H NMR) spectroscopy. Three nuclear magnetic resonance (NMR) spectra were acquired for each serum sample: NOESY1D, CPMG, Diffusion-edited. Random Forest (RF) models to predict BC relapse were built on NMR spectra, and resulting RF risk scores were evaluated by Kaplan-Meier curves. RESULTS: Serum samples from 140 eBC patients and 27 aBC were retrieved. In the eBC cohort, median age was 76 years; 77% of patients had luminal, 10% HER2-positive and 13% triple negative (TN) BC. Forty-two percent of patients had tumors >2 cm, 43% had positive axillary nodes. Using NOESY1D spectra, the RF classifier discriminated free-from-recurrence eBC from aBC with sensitivity, specificity and accuracy of 81%, 67% and 70% respectively. We tested the NOESY1D spectra of each eBC patient on the RF models already calculated. We found that patients classified as "high risk" had higher risk of disease recurrence (hazard ratio (HR) 3.42, 95% confidence interval (CI) 1.58-7.37) than patients at low-risk. CONCLUSIONS: This analysis suggests that a "metabolic signature", identified employing NMR fingerprinting, is able to predict the risk of disease recurrence in elderly patients with eBC independently from standard clinicopathological features.

Serum thymidine kinase activity in patients with HR-positive/HER2-negative advanced breast cancer treated with ribociclib plus letrozole: Results from the prospective BioItaLEE trial.

BACKGROUND: Thymidine kinase 1 (TK1) is an enzyme downstream of the CDK4/6 pathway, with a critical role in DNA synthesis; serum TK1 activity (sTKa) is a novel liquid biopsy biomarker of tumour cell proliferation. METHODS: The phase IIIb, BioItaLEE trial (NCT03439046) collected sera from postmenopausal patients with hormone receptor-positive (HR+), HER2-negative (HER2-) advanced breast cancer (ABC) treated with first-line ribociclib plus letrozole at baseline, day 15 of cycle 1 (C1D15), day 1 of cycle 2 (C2D1), and at first imaging. Associations between sTKa assessed at different time points or sTKa dynamic patterns, and progression-free survival (PFS) were evaluated using multivariate Cox models. RESULTS: Overall, 287 patients were enroled. Median follow-up was 26.9 months. High sTKa (>median) at baseline was associated with higher risk of progression (hazard ratio [HR], 2.21; 95% confidence interval [95% CI], 1.45, 3.37; P = 0.0002); similar results were observed for patients with high sTKa levels at C1D15 and C2D1. Early sTKa dynamic patterns were strongly predictive of PFS. The pattern with high sTKa levels at C2D1 following initial decrease at C1D15 was associated with higher risk of progression versus the pattern with low sTKa levels at both time points (HR, 2.89; 95% CI, 1.57, 5.31; P = 0.0006), while the pattern with high sTKa levels at C1D15 was associated with the shortest PFS (HR, 5.65; CI: 2.84, 11.2; P < 0.0001). Baseline and dynamic sTKa changes provided independent information. CONCLUSIONS: sTKa appears to be a new promising prognostic and pharmacodynamic biomarker in patients with HR+/HER2- ABC treated with ribociclib plus letrozole as first-line therapy.