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

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

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

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intratumural heterogeneity in head and neck squamous cell carcinoma

Background: As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.Methods: In a pilot cohort of 9 treatment-naïve HNSCC patients, DNA from two intra-tumoural sites (core and margin) was whole-exome sequenced. A 9-gene panel was designed to perform targeted sequencing on pre-treatment plasma cell-free DNA and selected post-treatment samples.Results: Rates of genomic ITH among the 9 patients was high. COSMIC variants from 19 TCGA HNSCC genes demonstrated an 86.9% heterogeneity rate (present in one tumour sub-site only). Across all patients, cell-free DNA (ctDNA) identified 12.9% (range 7.5-19.8%) of tumour-specific variants, of which 55.6% were specific to a single tumour sub-site only. CtDNA identified 79.0% (range: 55.6-90.9%) of high-frequency variants (tumour VAF>5%). Analysis of ctDNA in serial post-treatment blood samples in patients who suffered recurrence demonstrated dynamic changes in both tumour-specific and acquired variants that predicted recurrence ahead of clinical detection.Conclusion: We demonstrate that a ctDNA liquid biopsy identified spatial genomic ITH in HNSCC and reliably detected high-frequency driver mutations. Serial sampling allowed post-treatment surveillance and early identification of treatment failure

Effect of pathologic tumor response and nodal status on survival in the medical research council adjuvant gastric infusional chemotherapy trial

Purpose: The Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) trial established perioperative epirubicin, cisplatin, and fluorouracil chemotherapy as a standard of care for patients with resectable esophagogastric cancer. However, identification of patients at risk for relapse remains challenging. We evaluated whether pathologic response and lymph node status after neoadjuvant chemotherapy are prognostic in patients treated in the MAGIC trial. Materials and Methods: Pathologic regression was assessed in resection specimens by two independent pathologists using the Mandard tumor regression grading system (TRG). Differences in overall survival (OS) according to TRG were assessed using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses using the Cox proportional hazards method established the relationships among TRG, clinical-pathologic variables, and OS. Results: Three hundred thirty resection specimens were analyzed. In chemotherapy-treated patients with a TRG of 1 or 2, median OS was not reached, whereas for patients with a TRG of 3, 4, or 5, median OS was 20.47 months. On univariate analysis, high TRG and lymph node metastases were negatively related to survival (Mandard TRG 3, 4, or 5: hazard ratio [HR], 1.94; 95% CI, 1.11 to 3.39; P = .0209; lymph node metastases: HR, 3.63; 95% CI, 1.88 to 7.0; P < .001). On multivariate analysis, only lymph node status was independently predictive of OS (HR, 3.36; 95% CI, 1.70 to 6.63; P < .001). Conclusion: Lymph node metastases and not pathologic response to chemotherapy was the only independent predictor of survival after chemotherapy plus resection in the MAGIC trial. Prospective evaluation of whether omitting postoperative chemotherapy and/or switching to a noncross-resistant regimen in patients with lymph node-positive disease whose tumor did not respond to preoperative epirubicin, cisplatin, and fluorouracil may be appropriate