An integrative omics perspective for the analysis of chemical signals in ecological interactions.

All living organisms emit, detect, and respond to chemical stimuli, thus creating an almost limitless number of interactions by means of chemical signals. Technological and intellectual advances in the last two decades have enabled chemical signals analyses at several molecular levels, including gene expression, molecular diversity, and receptor affinity. These advances have also deepened our understanding of nature to encompass interactions at multiple organism levels across different taxa. This tutorial review describes the most recent analytical developments in 'omics' technologies (i.e., genomics, transcriptomics, proteomics, and metabolomics) and provide recent examples of its application in studies of chemical signals. We highlight how studies have integrated an enormous amount of information generated from different omics disciplines into one publicly available platform. In addition, we stress the importance of considering different signal modalities and an evolutionary perspective to establish a comprehensive understanding of chemical communication.

Multivariate prognostic factors analysis for second-line chemotherapy in advanced biliary tract cancer.

BACKGROUND: The role of second-line chemotherapy (CT) is not established in advanced biliary tract cancer (aBTC). We investigated the outcome of aBTC patients treated with second-line CT and devised a prognostic model. METHODS: Baseline clinical and laboratory data of 300 consecutive aBTC patients were collected and association with overall survival (OS) was investigated by multivariable Cox models. RESULTS: The following parameters resulted independently associated with longer OS: Eastern Cooperative Oncology Group performance status of 0 (P<0.001; hazard ratio (HR), 0.348; 95% confidence interval (CI) 0.215-0.562), CA19.9 lower than median (P=0.013; HR, 0.574; 95% CI 0.370-0.891), progression-free survival after first-line CT ≥ 6 months (P=0.027; HR, 0.633; 95% CI 0.422-0.949) and previous surgery on primary tumour (P=0.027; HR, 0.609; 95% CI 0.392-0.945). We grouped the 249 patients with complete data available into three categories according to the number of fulfilled risk factors: median OS times for good-risk (zero to one factors), intermediate-risk (two factors) and poor-risk (three to four factors) groups were 13.1, 6.6 and 3.7 months, respectively (P<0.001). CONCLUSIONS: Easily available clinical and laboratory factors predict prognosis of aBTC patients undergoing second-line CT. This model allows individual patient-risk stratification and may help in treatment decision and trial design.

Synthetic lethality to overcome cancer drug resistance.

A large body of evidence point out that the onset of synthetic lethality may provide a useful tool for amplifying the efficacy of drugs in anticancer regimens, to uncover interdependence between genes and to identify predictive factors that would be extremely useful to guide in the selection of more effective targeted drugs and drug combinations for each patient. Here, we provide an overview on the exploitation of synthetic lethality to overcome drug resistance to conventional chemotherapy in several types of solid tumors. We report recent findings on cellular markers and gene mutations which are specifically essential for the viability of cancer cells and for resistance to chemotherapeutics. In addition, new molecularly targeted strategies to overcome drug resistance are suggested.