Molecular subtyping of breast cancer improves identification of both high and low risk patients.

BACKGROUND: Transcriptome analysis enables classification of breast tumors into molecular subtypes that correlate with prognosis and effect of therapy. We evaluated the clinical benefits of molecular subtyping compared to our current diagnostic practice. MATERIALS AND METHODS: Molecular subtyping was performed on a consecutive and unselected series of 524 tumors from women with primary breast cancer (n = 508). Tumors were classified by the 256 gene expression signature (CIT) and compared to conventional immunohistochemistry (IHC) procedures. RESULTS: More than 99% of tumors were eligible for molecular classification and final reports were available prior to the multidisciplinary conference. Using a prognostic standard mortality rate index (PSMRi) developed by the Danish Breast Cancer Group (DBCG) 39 patients were assigned with an intermediate risk and among these 16 (41%) were furthermore diagnosed by the multi-gene signature assigned with a luminal A tumor and consequently spared adjuvant chemotherapy. There was overall agreement between mRNA derived and IHC hormone receptor status, whereas IHC Ki67 protein proliferative index proved inaccurate, compared to the mRNA derived index. Forty-one patients with basal-like (basL) subtypes were screened for predisposing mutations regardless of clinical predisposition. Of those 17% carried pathogenic mutations. CONCLUSION: Transcriptome based subtyping of breast tumors evidently reduces the need for adjuvant chemotherapy and improves identification of women with predisposing mutations. The results imply that transcriptome profiling should become an integrated part of current breast cancer management.

VEGF-C sustains VEGFR2 activation under bevacizumab therapy and promotes glioblastoma maintenance.

Background: Glioblastoma ranks among the most lethal cancers, with current therapies offering only palliation. Paracrine vascular endothelial growth factor (VEGF) signaling has been targeted using anti-angiogenic agents, whereas autocrine VEGF/VEGF receptor 2 (VEGFR2) signaling is poorly understood. Bevacizumab resistance of VEGFR2-expressing glioblastoma cells prompted interrogation of autocrine VEGF-C/VEGFR2 signaling in glioblastoma. Methods: Autocrine VEGF-C/VEGFR2 signaling was functionally investigated using RNA interference and exogenous ligands in patient-derived xenograft lines and primary glioblastoma cell cultures in vitro and in vivo. VEGF-C expression and interaction with VEGFR2 in a matched pre- and post-bevacizumab treatment cohort were analyzed by immunohistochemistry and proximity ligation assay. Results: VEGF-C was expressed by patient-derived xenograft glioblastoma lines, primary cells, and matched surgical specimens before and after bevacizumab treatment. VEGF-C activated autocrine VEGFR2 signaling to promote cell survival, whereas targeting VEGF-C expression reprogrammed cellular transcription to attenuate survival and cell cycle progression. Supporting potential translational significance, targeting VEGF-C impaired tumor growth in vivo, with superiority to bevacizumab treatment. Conclusions: Our results demonstrate VEGF-C serves as both a paracrine and an autocrine pro-survival cytokine in glioblastoma, promoting tumor cell survival and tumorigenesis. VEGF-C permits sustained VEGFR2 activation and tumor growth, where its inhibition appears superior to bevacizumab therapy in improving tumor control.

Acute Haemarthrosis in the Haemophilia A Rat Generates a Local and Systemic Proinflammatory Response.

Background Replacement therapy with coagulation factor VIII (FVIII) concurrent with bleeds (on-demand) in haemophilia A (HA) patients has been hypothesized to increase the risk for antidrug antibodies (inhibitors). A danger signal environment, characterized by tissue damage and inflammation at the site of a bleed, is thought to contribute to the anti-FVIII response. The nature of this inflammatory reaction is, however, not fully known, and new insights will be valuable for both managing inhibitors and understanding arthropathy development. Objective To characterize the inflammatory response, locally and systemically, during the first 24 hours following a joint bleed in the HA rat. Methods HA rats received a needle-induced knee joint bleed (n = 83) or a sham procedure (n = 41). Blood samples were collected at selected time points from 0 to 24 hours post injury/sham. Synovial fluid, intra-articular knee tissue and popliteal lymph nodes were collected at 24 hours. Cytokine/chemokine concentrations and gene expression were measured. Results Gene expression analysis revealed a rapid inflammatory response in the injured knees, accompanied by significantly increased levels of specific gene products in the synovial fluid; IL-1ß, TNFα, KC/GRO, IL-6, Eotaxin, MCP-1, MCP-3, MIP-1α, MIP-2, RANTES, A2M and AGP. Plasma analysis demonstrated significantly increased systemic levels of KC/GRO and IL-6 in injured rats already after 5 to 6 hours. Conclusion A rapid proinflammatory response, locally and systemically, characteristic of innate immunity, was demonstrated. Results reveal a more comprehensive inflammatory picture than previously shown, with resemblance to human haemophilic arthropathy, and with unique correlation between gene expression level, synovial concentration and plasma concentration in individual rats.

Interpretation of appearance: the effect of facial features on first impressions and personality.

Appearance is known to influence social interactions, which in turn could potentially influence personality development. In this study we focus on discovering the relationship between self-reported personality traits, first impressions and facial characteristics. The results reveal that several personality traits can be read above chance from a face, and that facial features influence first impressions. Despite the former, our prediction model fails to reliably infer personality traits from either facial features or first impressions. First impressions, however, could be inferred more reliably from facial features. We have generated artificial, extreme faces visualising the characteristics having an effect on first impressions for several traits. Conclusively, we find a relationship between first impressions, some personality traits and facial features and consolidate that people on average assess a given face in a highly similar manner.