Pappassimon1850

63 (99.8% CI 0.44 to 0.89); stratified log-rank 2-sided p-value less then 0.0001). The median OS was not reached for the nivolumab + ipilimumab group and was 25.95 months for the sunitinib group. The OS rates were 89.5% and 86.2% at 6 months, and 80.1% and 72.1% at 12 months in the nivolumab +ipilimumab and the sunitinib groups, respectively. K-M curves separated after approximately 3 months, favouring nivolumab + ipilimumab. This was not mirrored in the favourable-risk patients where no statistically significant difference was observed between nivolumab + ipilimumab and sunitinib in favourable-risk patients (HR 1.45 (descriptive 99.8% CI 0.51 to 4.12), p =0.2715).Centralisation of clinical pathology and with it better biobanking of veterinary samples could speed up the pace of cutting-edge research and its eventual translation into practice.In big data projects like SAVSNET and VetCompass lie the hope for a bigger veterinary evidence base, driving changes to consultations and treatments.A deeper understanding of the microbiome could help inform individualised treatment for animals and, in the use of faecal microbiota transplantation, a practical application of such knowledge already exists.Knowledge of canine genetics has advanced rapidly in recent years. Researchers say even deeper understanding is ahead, and that it could support a shift to more preventative veterinary care. But the involvement of a wide group of people will be vital in progressing towards that future.The future holds the promise of adding exciting new tools to the veterinary toolbox but,as Claire Read explains, there are still challenges to overcome.Overnight, the Covid-19 pandemic brought a need to use technology with which vets might not previously have grappled - most notably telemedicine. Here Daniella Dos Santos, president of the BVA throughout the first national lockdown, reflects on leading the profession through a sudden acceleration towards the future and questions what might come next.

Osteoarthritis (OA) structural status is imperfectly classified using radiographic assessment. Statistical shape modelling (SSM), a form of machine-learning, provides precise quantification of a characteristic 3D OA bone shape. We aimed to determine the benefits of this novel measure of OA status for assessing risks of clinically important outcomes.

The study used 4796 individuals from the Osteoarthritis Initiative cohort. SSM-derived femur bone shape (B-score) was measured from all 9433 baseline knee MRIs. We examined the relationship between B-score, radiographic Kellgren-Lawrence grade (KLG) and current and future pain and function as well as total knee replacement (TKR) up to 8 years.

B-score repeatability supported 40 discrete grades. KLG and B-score were both associated with risk of current and future pain, functional limitation and TKR; logistic regression curves were similar. However, each KLG included a wide range of B-scores. For example, for KLG3, risk of pain was 34.4 (95% CI 31.7 to 37.0)%,sment, analogous to the T-score in osteoporosis.

Clinical benefit from programmed cell death 1 receptor (PD-1) inhibitors relies on reinvigoration of endogenous antitumor immunity. Nonetheless, robust immunological markers, based on circulating immune cell subsets associated with therapeutic efficacy are yet to be validated.

We isolated peripheral blood mononuclear cell from three independent cohorts of melanoma and Merkel cell carcinoma patients treated with PD-1 inhibitor, at baseline and longitudinally after therapy. Using multiparameter flow cytometry and cell sorting, we isolated four subsets of CD8

T cells, based on PD-1 and TIGIT expression profiles. We performed phenotypic characterization, T cell receptor sequencing, targeted transcriptomic analysis and antitumor reactivity assays to thoroughly characterize each of these subsets.

We documented that the frequency of circulating PD-1

TIGIT

(DPOS) CD8

T-cells after 1 month of anti-PD-1 therapy was associated with clinical response and overall survival. This DPOS T-cell population was enriched in highly activated T-cells, tumor-specific and emerging T-cell clonotypes and T lymphocytes overexpressing CXCR5, a key marker of the CD8 cytotoxic follicular T cell population. Additionally, transcriptomic profiling defined a specific gene signature for this population as well as the overexpression of specific pathways associated with the therapeutic response.

Our results provide a convincing rationale for monitoring this PD-1

TIGIT

circulating population as an early cellular-based marker of therapeutic response to anti-PD-1 therapy.

Our results provide a convincing rationale for monitoring this PD-1+TIGIT+ circulating population as an early cellular-based marker of therapeutic response to anti-PD-1 therapy.

Combining radiotherapy (RT) with immuno-oncology (IO) therapy (IORT) may enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to provide prognosis, predict tumor response in a non-invasive fashion and improve patient selection for IORT. A biologically inspired CD8 T-cells-associated radiomics signature has been developed on previous cohorts. We evaluated here whether this CD8 radiomic signature is associated with lesion response, whether it may help to assess disease spatial heterogeneity for predicting outcomes of patients treated with IORT. learn more We also evaluated differences between irradiated and non-irradiated lesions.

Clinical data from patients with advanced solid tumors in six independent clinical studies of IORT were investigated. Immunotherapy consisted of 4 different drugs (antiprogrammed death-ligand 1 or anticytotoxic T-lymphocyte-associated protein 4 in monotherapy). Most patients received stereotactic RT to one lesion. Irradiated and non-irradiated lesions were delingical variables.

These results enhance the predictive value of the biologically inspired CD8 radiomics score and suggests that tumor heterogeneity should be systematically considered in patients treated with IORT. This CD8 radiomics signature may help select patients who are most likely to benefit from IORT.

These results enhance the predictive value of the biologically inspired CD8 radiomics score and suggests that tumor heterogeneity should be systematically considered in patients treated with IORT. This CD8 radiomics signature may help select patients who are most likely to benefit from IORT.