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

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

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

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

Characterization of a genetic mouse model of lung cancer: a promise to identify Non-Small Cell Lung Cancer therapeutic targets and biomarkers.

Background: Non-small cell lung cancer (NSCLC) accounts for 81% of all cases of lung cancer and they are often fatal because 60% of the patients are diagnosed at an advanced stage. Besides the need for earlier diagnosis, there is a high need for additional effective therapies. In this work, we investigated the feasibility of a lung cancer progression mouse model, mimicking features of human aggressive NSCLC, as biological reservoir for potential therapeutic targets and biomarkers. Results: We performed RNA-seq profiling on total RNA extracted from lungs of a 30 week-old K-rasLA1/p53R172H\u394g and wild type (WT) mice to detect fusion genes and gene/exon-level differential expression associated to the increase of tumor mass. Fusion events were not detected in K-rasLA1/p53R172H\u394g tumors. Differential expression at exon-level detected 33 genes with differential exon usage. Among them nine, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of more than 500 NSCLC RNA-seq transcriptomes. None of the genes showed a significant correlation between exon-level expression and disease prognosis. Differential expression at gene-level allowed the identification of 1513 genes with a significant increase in expression associated to tumor mass increase. 74 genes, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of two transcriptomics datasets of human NSCLC samples, encompassing more than 900 samples. SPP1 was the only molecule whose over-expression resulted statistically related to poor outcome regarding both survival and metastasis formation. Two other molecules showed over-expression associated to poor outcome due to metastasis formation: GM-CSF and ADORA3. GM-CSF is a secreted protein, and we confirmed its expression in the supernatant of a cell line derived by a K-rasLA1/p53R172H\u394g mouse tumor. ADORA3 is instead involved in the induction of p53-mediated apoptosis in lung cancer cell lines. Since in our model p53 is inactivated, ADORA3 does not negatively affect tumor growth but remains expressed on tumor cells. Thus, it could represent an interesting target for the development of antibody-targeted therapy on a subset of NSCLC, which are p53 null and ADORA3 positive. Conclusions: Our study provided a complete transcription overview of the K-rasLA1/p53R172H\u394g mouse NSCLC model. This approach allowed the detection of ADORA3 as a potential target for antibody-based therapy in p53 mutated tumors

Vaccines against human HER2 prevent mammary carcinoma in mice transgenic for human HER2

INTRODUCTION: The availability of mice transgenic for the human HER2 gene (huHER2) and prone to the development of HER2-driven mammary carcinogenesis (referred to as FVB-huHER2 mice) prompted us to study active immunopreventive strategies targeting the human HER2 molecule in a tolerant host. METHODS: FVB-huHER2 were vaccinated with either IL-12-adjuvanted human HER2-positive cancer cells or DNA vaccine carrying chimeric human-rat HER2 sequences. Onset and number of mammary tumors were recorded to evaluate vaccine potency. Mice sera were collected and passively transferred to xenograft-bearing mice to assess their antitumor efficacy. RESULTS: Both cell and DNA vaccines significantly delayed tumor onset, leading to about 65% tumor-free mice at 70 weeks, whereas mock-vaccinated FVB-huHER2 controls developed mammary tumors at a median age of 45 weeks. In the DNA vaccinated group, 65% of mice were still tumor-free at about 90 weeks of age. The number of mammary tumors per mouse was also significantly reduced in vaccinated mice. Vaccines broke the immunological tolerance to the huHER2 transgene, inducing both humoral and cytokine responses. The DNA vaccine mainly induced a high and sustained level of anti-huHER2 antibodies, the cell vaccine also elicited interferon (IFN)-gamma production. Sera of DNA-vaccinated mice transferred to xenograft-carrying mice significantly inhibited the growth of human HER2-positive cancer cells. CONCLUSIONS: Anti-huHER2 antibodies elicited in the tolerant host exert antitumoral activity