Target Therapies in Lung Cancer

Targeting intracellular signaling molecules is an attractive approach for treatment of malignancies. In particular lung cancer has reached a plateau regarding overall survival, and target therapies could offer the possibility to improve patients' outcome beyond cytotoxic activity. The goal for target therapies is to identify agents that target tumor-specific molecules, thus sparing normal tissues; those molecules are called biomarkers, and their identification is recommended because it has a predictive value, for example, provides information on outcome with regard to a specific treatment. The increased specificity should lead to decreased toxicity and better activity. Herein we provide an update of the main target therapies in development or already available for the treatment of nonsmall cell lung cancer

Use of complementary and alternative medicine (CAM) in cancer patients. An italian multicenter survey

INTRODUCTION: Complementary and Alternative Medicine (CAM) include a wide range of products (herbs, vitamins, minerals, and probiotics) and medical practices, developed outside of the mainstream Western medicine. Patients with cancer are more likely to resort to CAM first or then in their disease history; the potential side effects as well as the costs of such practices are largely underestimated. PATIENTS AND METHOD: We conducted a descriptive survey in five Italian hospitals involving 468 patients with different malignancies. The survey consisted of a forty-two question questionnaire, patients were eligible if they were Italian-speaking and receiving an anticancer treatment at the time of the survey or had received an anticancer treatment no more than three years before participating in the survey. RESULTS: Of our patients, 48.9% said they use or have recently used CAM. The univariate analysis showed that female gender, high education, receiving treatment in a highly specialized institute and receiving chemotherapy are associated with CAM use; at the multivariate analysis high education (Odds Ratio, (OR): 1.96 95% Confidence Interval, CI, 1.27-3.05) and receiving treatment in a specialized cancer center (OR: 2.75 95% CI, 1.53-4.94) were confirmed as risk factors for CAM use. CONCLUSION: Roughly half of our patients receiving treatment for cancer use CAM. It is necessary that health professional explore the use of CAM with their cancer patients, educate them about potentially beneficial therapies in light of the limited available evidence of effectiveness, and work towards an integrated model of health-care provision

Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy.

Funder: Cancer Research UKSingle-cell RNA-seq reveals the role of pathogenic cell populations in development and progression of chronic diseases. In order to expand our knowledge on cellular heterogeneity, we have developed a single-nucleus RNA-seq2 method tailored for the comprehensive analysis of the nuclear transcriptome from frozen tissues, allowing the dissection of all cell types present in the liver, regardless of cell size or cellular fragility. We use this approach to characterize the transcriptional profile of individual hepatocytes with different levels of ploidy, and have discovered that ploidy states are associated with different metabolic potential, and gene expression in tetraploid mononucleated hepatocytes is conditioned by their position within the hepatic lobule. Our work reveals a remarkable crosstalk between gene dosage and spatial distribution of hepatocytes

Physician Attitudes and Perceptions of Complementary and Alternative Medicine (CAM): A Multicentre Italian Study

Purpose: Complementary and Alternative Medicine (CAM) interventions are widely used by patients with chronic disorders, including cancer, and may interact with cancer treatment. Physicians are often unaware of this, probably due to poor patient-physician communication on CAM. The purpose of this study was to evaluate physicians' knowledge, attitudes and practice patterns regarding CAM in a survey conducted in Italy. Methods: A questionnaire was administered to 438 physicians (11 Italian hospitals) who predominantly treat patients with chronic disease, to collect personal and professional data and information on attitudes toward CAM and its possible role in Conventional Medicine (CM). Results: Of the 438 participants, most were specialists in oncology (18%), internal medicine (17%), surgery (15%), and radiotherapy (11%). Most worked at university (44%) or research hospitals (31%). Forty-two percent of participants believed that CAM could have an integrative role within CM. Oncologists were the physicians who were best informed on CAM (58%). Physicians working at research institutes or university hospitals had a greater knowledge of CAM than those employed at general hospitals (p < 0.0001), and those who were also involved in research activity had a greater knowledge of CAM than those who were not (p < 0.003). Length of work experience was significantly related to CAM knowledge. Moreover, 55% of participants suggest CAM interventions to their patients and 44% discuss CAM with them. The best-known interventions were acupuncture, Aloe vera and high-dose vitamin C. Conclusion: CAM use by patients with chronic disease and/or cancer has become a topical issue for the scientific community and for physicians. Knowing the reasons that prompt these patients to use CAM and guiding them in their decisions would improve treatment and outcomes and also benefit healthcare systems. Our findings contribute to a greater understanding of CAM knowledge, attitudes, and practice among Italian physicians. Further research is needed to identify the more effective CAM treatments and to work toward an integrated healthcare model

Hepatocellular Carcinoma in HIV-infected Patients: Check Ealy, Treat Hard

Purpose. Hepatocellular carcinoma (HCC) is an increasingcause of mortality in HIV-infected patients inthe highly active antiretroviral therapy (HAART) era.The aims of this study were to describe HCC tumorcharacteristics and different therapeutic approaches, toevaluate patient survival time from HCC diagnosis, andto identify clinical prognostic predictors in patients withand without HIV infection.Patients and Methods. A multicenter observationalretrospective comparison of 104 HIV-infected patientsand 484 uninfected patients was performed in four Italiancenters. HCC was staged according to the BarcelonaClinic Liver Cancer (BCLC) criteria.Results. Tumor characteristics of patients with andwithout HIV were significantly different for age, EasternCooperative Oncology Group performance status(PS) score <1, and etiology of chronic liver disease. Despitethe similar potentially curative option rate and better BCLC stage at diagnosis, the median survivaltime was significantly shorter in HIV patients. HIVpatients were less frequently retreated at relapse.Independent predictors of survival were: BCLC stage,potentially effective HCC therapy, tumor dimension <3cm, HCC diagnosis under a screening program, HCC recurrence,and portal vein thrombosis. Restricting the analysisto HIV patients only, all positive prognostic factorswere confirmed together with HAART exposure.Conclusion. This study confirms a significantlyshorter survival time in HIV HCC patients. The lessaggressive retreatment at recurrence approach does notbalance the benefit of younger age and better BCLCstage and PS score of HIV patients. Thus, consideringthe prognosis of HIV HCC patients, effective screeningtechniques, programs, and specific managementguidelines are urgently needed

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells’ response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine