Risk Assessment for Venous Thromboembolism in Chemotherapy-Treated Ambulatory Cancer Patients: A Machine Learning Approach

OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score). DESIGN: Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set. RESULTS: Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs. CONCLUSIONS: Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors

Preclinical HER-2 Vaccines: From Rodent to Human HER-2

open3noEffective prevention of human cancer with vaccines against viruses, such as HBV and HPV, raises the question whether also non-virus related tumors could be prevented with immunological means. Studies in HER-2-transgenic mice showed that powerful anti-HER-2 vaccines, could almost completely prevent the onset of mammary carcinoma. Protective immune responses were orchestrated by T cells and their cytokines, and effected by antibodies against HER-2 gene product p185. Analogous findings were reported in a variety of other cancer immunoprevention systems, thus leading to the definition of oncoantigens, optimal target antigens that are causally involved in carcinogenesis and cancer progression. Prophylactic HER-2 vaccines were also effective in preventing metastasis outgrowth, indicating that concepts and approaches developed for cancer immunoprevention could prove fruitful in cancer immunotherapy as well. The availability of cancer-prone mice carrying a human HER-2 transgene is now fostering the design of novel vaccines against human p185. A further bridge toward human cancer was recently provided by novel immunodeficient models, like Rag2-/-;Il2rg-/- mice, which are permissive for metastatic spread of human HER-2C cancer cells and can be engrafted with a functional human immune system, allowing for the first time the study of vaccines against oncoantigens to elicit human immune responses against human cancer cells in vivo.openPier-Luigi Lollini;Carla De Giovanni;Patrizia NanniPier-Luigi Lollini;Carla De Giovanni;Patrizia Nann

The Promise of Preventive Cancer Vaccines

Years of unsuccessful attempts at fighting established tumors with vaccines have taught us all that they are only able to truly impact patient survival when used in a preventive setting, as would normally be the case for traditional vaccines against infectious diseases. While true primary cancer prevention is still but a long-term goal, secondary and tertiary prevention are already in the clinic and providing encouraging results. A combination of immunopreventive cancer strategies and recently approved checkpoint inhibitors is a further promise of forthcoming successful cancer disease control, but prevention will require a considerable reduction of currently reported toxicities. These considerations summed with the increased understanding of tumor antigens allow space for an optimistic view of the future

2011: the immune hallmarks of cancer

Ten years after the publication of the position paper “The hallmarks of cancer” (Hanahan and Weinberg Cell 100:57–70, 2000), it has become increasingly clear that mutated cells on their way to giving rise to a tumor have also to learn how to thrive in a chronically inflamed microenvironment, evade immune recognition, and suppress immune reactivity. Genetic and molecular definition of these three immune hallmarks of cancer offers the opportunity to learn how to deploy specific countermeasures to reverse the situation in favor of the immune system and, eventually, the patient. This new information could be channeled to address what seem to be the three major hallmarks for the immune control of cancer progression: effective procedures to activate immune reactivity; characterization of not-disposable oncoantigens; and counteraction of immune suppression

Ensuring sample quality for biomarker discovery studies - Use of ict tools to trace biosample life-cycle

The growing demand of personalized medicine marked the transition from an empirical medicine to a molecular one, aimed at predicting safer and more effective medical treatment for every patient, while minimizing adverse effects. This passage has emphasized the importance of biomarker discovery studies, and has led sample availability to assume a crucial role in biomedical research. Accordingly, a great interest in Biological Bank science has grown concomitantly. In biobanks, biological material and its accompanying data are collected, handled and stored in accordance with standard operating procedures (SOPs) and existing legislation. Sample quality is ensured by adherence to SOPs and sample whole life-cycle can be recorded by innovative tracking systems employing information technology (IT) tools for monitoring storage conditions and characterization of vast amount of data. All the above will ensure proper sample exchangeability among research facilities and will represent the starting point of all future personalized medicine-based clinical trials

Bioprofiling TS/A Murine Mammary Cancer for a Functional Precision Experimental Model

The TS/A cell line was established in 1983 from a spontaneous mammary tumor arisen in an inbred BALB/c female mouse. Its features (heterogeneity, low immunogenicity and metastatic ability) rendered the TS/A cell line suitable as a preclinical model for studies on tumor-host interactions and for gene therapy approaches. The integrated biological profile of TS/A resulting from the review of the literature could be a path towards the description of a precision experimental model of mammary cancer

IFN-γ and CD38 in Hyperprogressive Cancer Development

Immune checkpoint inhibitors (ICIs) improve the survival of patients with multiple types of cancer. However, low response rates and atypical responses limit their success in clinical applications. The paradoxical acceleration of tumor growth after treatment, defined as hyperprogressive disease (HPD), is the most difficult problem facing clinicians and patients alike. The mechanisms that underlie hyperprogression (HP) are still unclear and controversial, although different factors are associated with the phenomenon. In this review, we propose two factors that have not yet been demonstrated to be directly associated with HP, but upon which it is important to focus attention. IFN-γ is a key cytokine in antitumor response and its levels increase during ICI therapy, whereas CD38 is an alternative immune checkpoint that is involved in immunosuppressive responses. As both factors are associated with resistance to ICI therapy, we have discussed their possible involvement in HPD with the conclusion that IFN-γ may contribute to HP onset through the activation of the inflammasome pathway, immunosuppressive enzyme IDO1 and activation-induced cell death (AICD) in effector T cells, while the role of CD38 in HP may be associated with the activation of adenosine receptors, hypoxia pathways and AICD-dependent T-cell depletion

Intratumoral delivery of recombinant vaccinia virus encoding for ErbB2/Neu inhibits the growth of salivary gland carcinoma cells

The antitumor activity induced by intratumoral vaccination with poxvirus expressing a tumor antigen was shown to be superior to that induced by subcutaneous vaccination. Salivary gland carcinomas overexpress ErbB2. Trastuzumab, a monoclonal antibody to ErbB2, was proposed for salivary gland tumors treatment. We explored the effectiveness of intratumoral vaccination with the recombinant vaccinia virus ErbB2/Neu (rV-neuT) vaccine in hampering the growth of transplanted Neu-overexpressing BALB-neuT salivary gland cancer cells (SALTO) in BALB-neuT mice

Modeling the competition between lung metastases and the immune system using agents

<p>Abstract</p> <p>Background</p> <p>The Triplex cell vaccine is a cancer cellular vaccine that can prevent almost completely the mammary tumor onset in HER-2/neu transgenic mice. In a translational perspective, the activity of the Triplex vaccine was also investigated against lung metastases showing that the vaccine is an effective treatment also for the cure of metastases. A future human application of the Triplex vaccine should take into account several aspects of biological behavior of the involved entities to improve the efficacy of therapeutic treatment and to try to predict, for example, the outcomes of longer experiments in order to move faster towards clinical phase I trials. To help to address this problem, MetastaSim, a hybrid Agent Based - ODE model for the simulation of the vaccine-elicited immune system response against lung metastases in mice is presented. The model is used as in silico wet-lab. As a first application MetastaSim is used to find protocols capable of maximizing the total number of prevented metastases, minimizing the number of vaccine administrations.</p> <p>Results</p> <p>The model shows that it is possible to obtain "in silico" a 45% reduction in the number of vaccinations. The analysis of the results further suggests that any optimal protocol for preventing lung metastases formation should be composed by an initial massive vaccine dosage followed by few vaccine recalls.</p> <p>Conclusions</p> <p>Such a reduction may represent an important result from the point of view of translational medicine to humans, since a downsizing of the number of vaccinations is usually advisable in order to minimize undesirable effects. The suggested vaccination strategy also represents a notable outcome. Even if this strategy is commonly used for many infectious diseases such as tetanus and hepatitis-B, it can be in fact considered as a relevant result in the field of cancer-vaccines immunotherapy. These results can be then used and verified in future "in vivo" experiments, and their outcome can be used to further improve and refine the model.</p