Examining patient-reported late toxicity and its association with quality of life and unmet need for symptom management among nasopharyngeal cancer survivors: a cross-sectional survey

IntroductionAlongside the improved survival of nasopharyngeal cancer (NPC), late radiation toxicities are alarmingly hampering survivors’ quality of life. A patient-reported symptom burden survey is lacking to address the unmet need for symptom management among local NPC survivors.MethodsA single-center cross-sectional survey was conducted on 211 NPC survivors who had completed radiation therapy for three to 120 months. We employed the Chinese version M. D. Anderson Symptom Inventory - Head & Neck Module (MDASI-HN-C), Functional Assessment of Cancer Therapy - Head & Neck (FACT-HN-C), and a question extracted from the Cancer Survivors’ Unmet Needs Measure (CaSUN).ResultsTwo hundred valid responses were collected. Participants suffered from at least four moderate to severe symptoms (mean = 4.84, SD = 4.99). The top five severe symptoms were dry mouth, mucus problems, difficulty swallowing or chewing, teeth or gum problems, and memory problems. MDASI-HN-C subscales were negatively correlated with the physical, emotional, functional, and HN-specific domains of the FACT-HN-C. The unmet need for symptom management was positively associated with symptom burden, either general symptoms (Adjusted odds ratio [ORadj] = 1.566, 95% CI = 1.282 – 1.914, p < 0.001) or top-5 symptoms (ORadj = 1.379, 95% CI = 1.185 – 1.604, p < 0.001), while negatively associated with post-RT time (ORadj = 0.981, 95% CI [0.972, 0.991], p < 0.001).ConclusionVirtually all NPC survivors suffer from late toxicities, which interplay with survivors’ perceptions intricately to affect their unmet needs for symptom management. Personalized supportive care strategies with regular assessments and stratifications are warranted

Identification of a humanized mouse model for functional testing of immune-mediated biomaterial foreign body response.

Biomedical devices comprise a major component of modern medicine, however immune-mediated fibrosis and rejection can limit their function over time. Here, we describe a humanized mouse model that recapitulates fibrosis following biomaterial implantation. Cellular and cytokine responses to multiple biomaterials were evaluated across different implant sites. Human innate immune macrophages were verified as essential to biomaterial rejection in this model and were capable of cross-talk with mouse fibroblasts for collagen matrix deposition. Cytokine and cytokine receptor array analysis confirmed core signaling in the fibrotic cascade. Foreign body giant cell formation, often unobserved in mice, was also prominent. Last, high-resolution microscopy coupled with multiplexed antibody capture digital profiling analysis supplied spatial resolution of rejection responses. This model enables the study of human immune cell-mediated fibrosis and interactions with implanted biomaterials and devices

Development of a standardized histopathology scoring system using machine learning algorithms for intervertebral disc degeneration in the mouse model—An ORS spine section initiative

Mice have been increasingly used as preclinical model to elucidate mechanisms and test therapeutics for treating intervertebral disc degeneration (IDD). Several intervertebral disc (IVD) histological scoring systems have been proposed, but none exists that reliably quantitate mouse disc pathologies. Here, we report a new robust quantitative mouse IVD histopathological scoring system developed by building consensus from the spine community analyses of previous scoring systems and features noted on different mouse models of IDD. The new scoring system analyzes 14 key histopathological features from nucleus pulposus (NP), annulus fibrosus (AF), endplate (EP), and AF/NP/EP interface regions. Each feature is categorized and scored; hence, the weight for quantifying the disc histopathology is equally distributed and not driven by only a few features. We tested the new histopathological scoring criteria using images of lumbar and coccygeal discs from different IDD models of both sexes, including genetic, needle-punctured, static compressive models, and natural aging mice spanning neonatal to old age stages. Moreover, disc sections from common histological preparation techniques and stains including H&E, SafraninO/Fast green, and FAST were analyzed to enable better cross-study comparisons. Fleiss\u27s multi-rater agreement test shows significant agreement by both experienced and novice multiple raters for all 14 features on several mouse models and sections prepared using various histological techniques. The sensitivity and specificity of the new scoring system was validated using artificial intelligence and supervised and unsupervised machine learning algorithms, including artificial neural networks, k-means clustering, and principal component analysis. Finally, we applied the new scoring system on established disc degeneration models and demonstrated high sensitivity and specificity of histopathological scoring changes. Overall, the new histopathological scoring system offers the ability to quantify histological changes in mouse models of disc degeneration and regeneration with high sensitivity and specificity

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Natural and anthropogenic changes to mangrove distributions in the Pioneer River Estuary (QLD, Australia)

We analyzed a time series of aerial photographs and Landsat satellite imagery of the Pioneer River Estuary (near Mackay, Queensland, Australia) to document both natural and anthropogenic changes in the area of mangroves available to filter river runoff between 1948 and 2002. Over 54 years, there was a net loss of 137 ha (22%) of tidal mangroves during four successive periods that were characterized by different driving mechanisms: (1) little net change (1948– 1962); (2) net gain from rapid mangrove expansion (1962–1972); (3) net loss from clearing and tidal isolation (1972–1991); and (4) net loss from a severe species-specific dieback affecting over 50% of remaining mangrove cover (1991–2002). Manual digitization of aerial photographs was accurate for mapping changes in the boundaries of mangrove distributions, but this technique underestimated the total loss due to dieback. Regions of mangrove dieback were identified and mapped more accurately and efficiently after applying the Normalized Difference Vegetation Index (NDVI) to Landsat Thematic Mapper satellite imagery, and then monitoring changes to the index over time. These remote sensing techniques to map and monitor mangrove changes are important for identifying habitat degradation, both spatially and temporally, in order to prioritize restoration for management of estuarine and adjacent marine ecosystems

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

A common variant near TGFBR3 is associated with primary open angle glaucoma

Primary open angle glaucoma (POAG), a major cause of blindness worldwide, is a complex disease with a significant genetic contribution. We performed Exome Array (Illumina) analysis on 3504 POAG cases and 9746 controls with replication of the most significant findings in 9173 POAG cases and 26 780 controls across 18 collections of Asian, African and European descent. Apart from confirming strong evidence of association at CDKN2B-AS1 (rs2157719 [G], odds ratio [OR] = 0.71, P = 2.81 × 10−33), we observed one SNP showing significant association to POAG (CDC7–TGFBR3 rs1192415, ORG-allele = 1.13, Pmeta = 1.60 × 10−8). This particular SNP has previously been shown to be strongly associated with optic disc area and vertical cup-to-disc ratio, which are regarded as glaucoma-related quantitative traits. Our study now extends this by directly implicating it in POAG disease pathogenesis