The prognostic significance of tumour-stroma ratio in oestrogen receptor-positive breast cancer

We are grateful to Breast Cancer Campaign for funding our collection of male breast carcinomas and for supporting DLH and SP. SAS was funded by the Wolfson Foundation and a Wellcome Trust Vacation Scholarship. HHT was funded by Cancer Research UK. We convey special thanks to members of the Leeds Breast Team for input and support at various stages of this project.Peer reviewedPublisher PD

Tumour sampling method can significantly influence gene expression profiles derived from neoadjuvant window studies

Patient-matched transcriptomic studies using tumour samples before and after treatment allow inter-patient heterogeneity to be controlled, but tend not to include an untreated comparison. Here, Illumina BeadArray technology was used to measure dynamic changes in gene expression from thirty-seven paired diagnostic core and surgically excised breast cancer biopsies obtained from women receiving no treatment prior to surgery, to determine the impact of sampling method and tumour heterogeneity. Despite a lack of treatment and perhaps surprisingly, consistent changes in gene expression were identified during the diagnosis-surgery interval (48 up, 2 down; Siggenes FDR 0.05) in a manner independent of both subtype and sampling-interval length. Instead, tumour sampling method was seen to directly impact gene expression, with similar effects additionally identified in six published breast cancer datasets. In contrast with previous findings, our data does not support the concept of a significant wounding or immune response following biopsy in the absence of treatment and instead implicates a hypoxic response following the surgical biopsy. Whilst sampling-related gene expression changes are evident in treated samples, they are secondary to those associated with response to treatment. Nonetheless, sampling method remains a potential confounding factor for neoadjuvant study design

Comment on: The prognostic significance of tumour-stroma ratio in oestrogen receptor-positive breast cancer

Immunology and molecular genetics of gynecological cancer

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival (m/z 180.9436 and 241.0118) and metastasis-free survival (m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13361-016-1544-4) contains supplementary material, which is available to authorized users

Host Plant Species Differentiation in a Polyphagous Moth: Olfaction is Enough

International audiencePolyphagous herbivorous insects need to discriminate suitable from unsuitable host plants in complex plant communities. While studies on the olfactory system of monophagous herbivores have revealed close adaptations to their host plant's characteristic volatiles, such adaptive fine-tuning is not possible when a large diversity of plants is suitable. Instead, the available literature on polyphagous herbivore preferences suggests a higher level of plasticity, and a bias towards previously experienced plant species. It is therefore necessary to take into account the diversity of plant odors that polyphagous herbivores encounter in the wild in order to unravel the olfactory basis of their host plant choice behaviour. In this study we show that a polyphagous moth, Spodoptera littoralis, has the sensory ability to distinguish five host plant species using olfaction alone, this being a prerequisite to the ability to make a choice. We have used gas chromatography mass spectrometry (GC-MS) and gas chromatography electroantennographic detection (GC-EAD) in order to describe host plant odor profiles as perceived by S. littoralis. We find that each plant emits specific combinations and proportions of GC-EAD active volatiles, leading to statistically distinct profiles. In addition, at least four of these plants show GC-EAD active compound proportions that are conserved across individual plants, a characteristic that enables insects to act upon previous olfactory experiences during host plant choice. By identifying the volatiles involved in olfactory differentiation of alternative host plants by Spodoptera littoralis, we set the groundwork for deeper investigations of how olfactory perceptions translate into behaviour in polyphagous herbivores