Insulin-like Growth Factor-1 Receptor (IGF-1R) expression on Circulating Tumor Cells (CTCs) and metastatic breast cancer outcome: results from the TransMYME trial

Purpose To evaluate the prognostic value of IGF-1R expression on circulating tumor cells (CTCs) in a prospective randomized clinical trial comparing chemotherapy plus metformin with chemotherapy alone in metastatic breast cancer (MBC) patients. Methods CTCs were collected at baseline and at the end of chemotherapy. An automated sample preparation and analysis system (CellSearch) were customized for detecting IGF-1R expression. The prognostic role of CTC count and IGF-1R was assessed for PFS and OS by univariate and multivariate analyses. Results Seventy-two out of 126 randomized patients were evaluated: 57% had >= 1 IGF-1R positive CTC and 37.5% >= 4 IGF-1R negative cells; 42% had CTC count >= 5/7.5 ml. At univariate analysis, the number of IGF-1R negative CTCs was strongly associated with risk of progression and death: HR 1.93 (P = 0.013) and 3.65 (P = 0.001), respectively; no association was detected between number of IGF-1R positive CTCs and PFS or OS (P = 0.322 and P = 0.840). The prognostic role of CTC count was confirmed: HR 1.69, P = 0.042 for PFS and HR 2.80 for OS, P = 0.002. By multivariate analysis, the prognostic role of the number of IGF-1R negative CTCs was maintained, while no residual prognostic role of CTC count or number of IGF-1R positive cells was found. Conclusion Loss of IGF-1R in CTCs is associated with a significantly worse outcome in MBC patients. This finding supports further evaluation for the role of IGF-1R on CTCs to improve patient stratification and to implement new targeted strategies. Clinical trial registration: Clinicaltrials.gov (NCT01885013); European Clinical Trials Database (EudraCT No.2009-014,662-26)

Single tube liquid biopsy for advanced non-small cell lung cancer

The need for a liquid biopsy in non-small cell lung cancer (NSCLC) patients is rapidly increasing. We studied the relation between overall survival (OS) and the presence of four cancer biomarkers from a single blood draw in advanced NSCLC patients: EpCAM(high) circulating tumor cells (CTC), EpCAM(low) CTC, tumor-derived extracellular vesicles (tdEV) and cell-free circulating tumor DNA (ctDNA). EpCAM(high) CTC were detected with CellSearch, tdEV in the CellSearch images and EpCAM(low) CTC with filtration after CellSearch. ctDNA was isolated from plasma and mutations present in the primary tumor were tracked with deep sequencing methods. In 97 patients, 21% had >= 2 EpCAM(high) CTC, 15% had >= 2 EpCAM(low) CTC, 27% had >= 18 tdEV and 19% had ctDNA with >= 10% mutant allele frequency. Either one of these four biomarkers could be detected in 45% of the patients and all biomarkers were present in 2%. In 11 out of 16 patients (69%) mutations were detected in the ctDNA. Two or more unfavorable biomarkers were associated with poor OS. The presence of EpCAM(high) CTC and elevated levels of tdEV and ctDNA was associated with a poor OS; however, the presence of EpCAM(low) CTC was not. This single tube approach enables simultaneous analysis of multiple biomarkers to explore their potential as a liquid biopsy

The clinical use of circulating tumor cells (CTCs) enumeration for staging of metastatic breast cancer (MBC): International expert consensus paper

BACKGROUND: The heterogeneity of metastatic breast cancer (MBC) necessitates novel biomarkers allowing stratification of patients for treatment selection and drug development. We propose to use the prognostic utility of circulating tumor cells (CTCs) for stratification of patients with stage IV disease. METHODS: In a retrospective, pooled analysis of individual patient data from 18 cohorts, including 2436 MBC patients, a CTC threshold of 5 cells per 7.5\u2009ml was used for stratification based on molecular subtypes, disease location, and prior treatments. Patients with 65 5 CTCs were classified as Stage IVaggressive, those with < 5 CTCs as Stage IVindolent. Survival was analyzed using Kaplan-Meier curves and the log rank test. RESULTS: For all patients, Stage IVindolent patients had longer median overall survival than those with Stage IVaggressive (36.3 months vs. 16.0 months, P\u2009<\u20090.0001) and similarly for de novo MBC patients (41.4 months Stage IVindolent vs. 18.7 months Stage IVaggressive, p\u2009<\u20090.0001). Moreover, patients with Stage IVindolent disease had significantly longer overall survival across all disease subtypes compared to the aggressive cohort: hormone receptor-positive (44 months vs. 17.3 months, P\u2009<\u20090.0001), HER2-positive (36.7 months vs. 20.4 months, P\u2009<\u20090.0001), and triple negative (23.8 months vs. 9.0 months, P\u2009<\u20090.0001). Similar results were obtained regardless of prior treatment or disease location. CONCLUSIONS: We confirm the identification of two subgroups of MBC, Stage IVindolent and Stage IVaggressive, independent of clinical and molecular variables. Thus, CTC count should be considered an important tool for staging of advanced disease and for disease stratification in prospective clinical trials

Articles Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data

Summary Background We aimed to assess the clinical validity of circulating tumour cell (CTC) quantifi cation for prognostication of patients with metastatic breast cancer by undertaking a pooled analysis of individual patient data

Mathematical models for HIV treatment : A schematic review

This review examines mathematical models related to the treatment of Human Immunodeficiency Virus (HIV) and Acquired Immunodeficiency Syndrome (AIDS). The analysis is based on two criteria: the physio-pathological one and the mathematical one. The former criterion checks the presence and possible differentiation of uninfected and infected T lymphocytes, of immune cells and of viruses. The latter criterion distinguishes among dynamic systems, optimal control, and differential game approaches. A schematic table collects the results of this analysis and allows the reader to find out at a glance both the physiopathological and the mathematical characteristics of each cited model

HIV Inside the Body: A Review of Mathematical Modeling.

none3This paper presents a review of works devoted to studies on Human Immunodeficiency Virus (HIV) and Acquired Immunodeficiency Syndrome (AIDS) dynamics through mathematical modeling. The analysis is performed over about a hundred papers from 1989 to the present day, distinguishing models according to the presence or absence of variables such as infected T-lymphocytes and immune effectors or precursors, and the presence or absence of differentiation in uninfected T cells, infected T cells and viruses. The review also cites the optimal control approaches to the topic and some recent formulations in terms of differential game theory, aimed at predicting the effects of different dosage schedules or drug combinations. For each group of works we describe the significant variables and underline their role in the dynamics. The survey also proposes a frequency table over the most commonly used parameters. Finally, building on the previous analysis, we resume the main features a mathematical model should have in order to describe faithfully the complex interactions between the immune system and HIV.restrictedBuratto, Alessandra; Cesaretto, Rudy; Zamarchi, RitaBuratto, Alessandra; Cesaretto, Rudy; Zamarchi, Rit

HIV vs. the Immune System: A Differential Game

A differential game is formulated in order to model the interaction between the immune system and the HIV virus. One player is represented by the immune system of a patient subject to a therapeutic treatment and the other player is the HIV virus. The aim of our study is to determine the optimal therapy that allows to prevent viral replication inside the body, so as to reduce the damage caused to the immune system, and allow greater survival and quality of life. We propose a model that considers all the most common classes of antiretroviral drugs taking into account different immune cells dynamics. We validate the model with numerical simulations, and determine optimal structured treatment interruption (STI) schedules for medications