Feasibility of recruitment to an oral dysplasia trial in the United Kingdom

Background: Oral epithelial dysplasia (OED) has a malignant potential. Therapeutic options for OED remain both limited and without good evidence. Despite surgery being the most common method of treating OED, recurrence and potentially significant morbidity remain problematic. Consequently, there has been much interest in non-surgical treatments for OED. Cyclo-oxygenase (COX) up-regulation is known to occur in the dysplasia-carcinoma sequence and evidence now exists that COX-2 is a prognostic marker of malignant transformation in OED. COX-inhibitors are therefore considered a potential therapeutic strategy for treating this condition. We aimed to provide both proof of principal evidence supporting the effect of topical COX inhibition, and determine the feasibility of recruitment to an OED chemoprevention trial in the UK. Methods: Recruitment of 40 patients with oral leukoplakia to 4 study arms was planned. The total daily dose of Aspirin would increase in each group and be used in the period between initial diagnostic and follow-up biopsies. Results: During the 15-month recruitment period, 15/50 screened patients were eligible for recruitment, and 13 (87%) consented. Only 1 had OED diagnosed on biopsy. 16 patients were intolerant of, or already taking Aspirin and 16 patients required no biopsy. Initial recruitment was slow, as detection relied on clinicians identifying potentially eligible patients. Pre-screening new patient letters and directly contacting patients listed for biopsies improved screening of potentially eligible patients. However, as the incidence of OED was so low, it had little impact on trial recruitment. The trial was terminated, as recruitment was unlikely to be achieved in a single centre. Conclusion: This feasibility trial has demonstrated the low incidence of OED in the UK and the difficulties in conducting a study because of this. With an incidence of around 1.5/100,000/year and a high proportion of those patients already taking or intolerant of Aspirin, a large multi-centred trial would be required to fulfil the recruitment for this study. The ability of topical non-steroidal anti-inflammatory drugs to modify COX and prostaglandin expression remains an important but unanswered question. Collaboration with centres in other parts of the world with higher incidences of the disease may be required to ensure adequate recruitment. ISRCTN: 31503555

Prognostic Significance of Negative Lymph Node Long Axis in Esophageal Cancer: Results From the Randomized Controlled UK MRC OE02 Trial

OBJECTIVE: To analyze the relationship between negative lymph node (LNneg) size as a possible surrogate marker of the host antitumor immune response and overall survival (OS) in esophageal cancer (EC) patients. BACKGROUND: Lymph node (LN) status is a well-established prognostic factor in EC patients. An increased number of LNnegs is related to better survival in EC. Follicular hyperplasia in LNneg is associated with better survival in cancer-bearing mice and might explain increased LN size. METHODS: The long axis of 304 LNnegs was measured in hematoxylin-eosin stained sections from resection specimens of 367 OE02 trial patients (188 treated with surgery alone (S), 179 with neoadjuvant chemotherapy plus surgery (C+S)) as a surrogate of LN size. The relationship between LNneg size, LNneg microarchitecture, clinicopathological variables, and OS was analyzed. RESULTS: Large LNneg size was related to lower pN category (P = 0.01) and lower frequency of lymphatic invasion (P = 0.02) in S patients only. Irrespective of treatment, (y)pN0 patients with large LNneg had the best OS. (y)pN1 patients had the poorest OS irrespective of LNneg size (P < 0.001). Large LNneg contained less lymphocytes (P = 0.02) and had a higher germinal centers/lymphocyte ratio (P = 0.05). CONCLUSIONS: This is the first study to investigate LNneg size in EC patients randomized to neoadjuvant chemotherapy followed by surgery or surgery alone. Our pilot study suggests that LNneg size is a surrogate marker of the host antitumor immune response and a potentially clinically useful new prognostic biomarker for (y)pN0 EC patients. Future studies need to confirm our results and explore underlying biological mechanisms

Chronic allograft nephropathy

Chronic allograft nephropathy (CAN) is the leading cause of renal allograft loss in paediatric renal transplant recipients. CAN is the result of immunological and nonimmunological injury, including acute rejection episodes, hypoperfusion, ischaemia reperfusion, calcineurin toxicity, infection and recurrent disease. The development of CAN is often insidious and may be preceded by subclinical rejection in a well-functioning allograft. Classification of CAN is histological using the Banff classification of renal allograft pathology with classic findings of interstitial fibrosis, tubular atrophy, glomerulosclerosis, fibrointimal hyperplasia and arteriolar hyalinosis. Although improvement in immunosuppression has led to greater 1-year graft survival rates, chronic graft loss remains relatively unchanged and opportunistic infectious complications remain a problem. Protocol biopsy monitoring is not current practice in paediatric transplantation for CAN monitoring but may have a place if new treatment options become available. Newer immunosuppression regimens, closer monitoring of the renal allograft and management of subclinical rejection may lead to reduced immune injury leading to CAN in the paediatric population but must be weighed against the risk of increased immunosuppression and calcineurin inhibitor nephrotoxicity

Pharmacokinetics of Tacrolimus in Kidney Transplant Recipients: Twice Daily Versus Once Daily Dosing

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72008/1/j.1600-6143.2004.00383.x.pd

Automated detection and delineation of lymph nodes in haematoxylin & eosin stained digitised slides.

Treatment of patients with oesophageal and gastric cancer (OeGC) is guided by disease stage, patient performance status and preferences. Lymph node (LN) status is one of the strongest prognostic factors for OeGC patients. However, survival varies between patients with the same disease stage and LN status. We recently showed that LN size from patients with OeGC might also have prognostic value, thus making delineations of LNs essential for size estimation and the extraction of other imaging biomarkers. We hypothesized that a machine learning workflow is able to: (1) find digital H&E stained slides containing LNs, (2) create a scoring system providing degrees of certainty for the results, and (3) delineate LNs in those images. To train and validate the pipeline, we used 1695 H&E slides from the OE02 trial. The dataset was divided into training (80%) and validation (20%). The model was tested on an external dataset of 826 H&E slides from the OE05 trial. U-Net architecture was used to generate prediction maps from which predefined features were extracted. These features were subsequently used to train an XGBoost model to determine if a region truly contained a LN. With our innovative method, the balanced accuracies of the LN detection were 0.93 on the validation dataset (0.83 on the test dataset) compared to 0.81 (0.81) on the validation (test) datasets when using the standard method of thresholding U-Net predictions to arrive at a binary mask. Our method allowed for the creation of an "uncertain" category, and partly limited false-positive predictions on the external dataset. The mean Dice score was 0.73 (0.60) per-image and 0.66 (0.48) per-LN for the validation (test) datasets. Our pipeline detects images with LNs more accurately than conventional methods, and high-throughput delineation of LNs can facilitate future LN content analyses of large datasets

Automated detection and delineation of lymph nodes in haematoxylin & eosin stained digitised slides

Treatment of patients with oesophageal and gastric cancer (OeGC) is guided by disease stage, patient performance status and preferences. Lymph node (LN) status is one of the strongest prognostic factors for OeGC patients. However, survival varies between patients with the same disease stage and LN status. We recently showed that LN size from patients with OeGC might also have prognostic value, thus making delineations of LNs essential for size estimation and the extraction of other imaging biomarkers. We hypothesized that a machine learning workflow is able to: (1) find digital H&E stained slides containing LNs, (2) create a scoring system providing degrees of certainty for the results, and (3) delineate LNs in those images. To train and validate the pipeline, we used 1695 H&E slides from the OE02 trial. The dataset was divided into training (80%) and validation (20%). The model was tested on an external dataset of 826 H&E slides from the OE05 trial. U-Net architecture was used to generate prediction maps from which predefined features were extracted. These features were subsequently used to train an XGBoost model to determine if a region truly contained a LN. With our innovative method, the balanced accuracies of the LN detection were 0.93 on the validation dataset (0.83 on the test dataset) compared to 0.81 (0.81) on the validation (test) datasets when using the standard method of thresholding U-Net predictions to arrive at a binary mask. Our method allowed for the creation of an “uncertain” category, and partly limited false-positive predictions on the external dataset. The mean Dice score was 0.73 (0.60) per-image and 0.66 (0.48) per-LN for the validation (test) datasets. Our pipeline detects images with LNs more accurately than conventional methods, and high-throughput delineation of LNs can facilitate future LN content analyses of large datasets

The regulation of miRNAs by reconstituted high-density lipoproteins in diabetes-impaired angiogenesis

Diabetic vascular complications are associated with impaired ischaemia-driven angiogenesis. We recently found that reconstituted high-density lipoproteins (rHDL) rescue diabetes-impaired angiogenesis. microRNAs (miRNAs) regulate angiogenesis and are transported within HDL to sites of injury/repair. The role of miRNAs in the rescue of diabetes-impaired angiogenesis by rHDL is unknown. Using a miRNA array, we found that rHDL inhibits hsa-miR-181c-5p expression in vitro and using a hsa-miR-181c-5p mimic and antimiR identify a novel anti-angiogenic role for miR-181c-5p. miRNA expression was tracked over time post-hindlimb ischaemic induction in diabetic mice. Early post-ischaemia when angiogenesis is important, rHDL suppressed hindlimb mmu-miR-181c-5p. mmu-miR-181c-5p was not detected in the plasma or within HDL, suggesting rHDL specifically targets mmu-miR-181c-5p at the ischaemic site. Three known angiogenic miRNAs (mmu-miR-223-3p, mmu-miR-27b-3p, mmu-miR-92a-3p) were elevated in the HDL fraction of diabetic rHDL-infused mice early post-ischaemia. This was accompanied by a decrease in plasma levels. Only mmu-miR-223-3p levels were elevated in the hindlimb 3 days post-ischaemia, indicating that rHDL regulates mmu-miR-223-3p in a time-dependent and site-specific manner. The early regulation of miRNAs, particularly miR-181c-5p, may underpin the rescue of diabetes-impaired angiogenesis by rHDL and has implications for the treatment of diabetes-related vascular complications