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To quantify the degree of color match achieved during microvascular facial reconstruction, and to describe a novel technique for improving reconstructive skin color match. We hypothesize that split-thickness skin grafts (STSG) placed atop de-epithelialized free tissue produces better facial skin color match than free tissue with intact epithelium.Cross sectional photographic study of reconstructed facial skin color match.Sixty-eight adults, who underwent head and neck reconstructive surgery, were divided into six categories based on cutaneous reconstructive technique: cervicofacial flap, radial forearm free flap (RFFF), fibula free flap, anterolateral thigh free flap (ALT), STSG over adiopofascial flap (STAFF), and STSG over myogenous flap (STMF). Averaged color samplings of the reconstructed defect and adjacent normal skin were taken from digital photographs. The color difference was calculated using the delta-E calculation. Blinded expert observers also rated the degree of color match. Nonparametric cohort contrast and correlation statistical analyses were performed.The mean delta-E's and 10-point Likert ratings for the ALT, fibula, RFFF, STAFF, STMF, and cervicofacial flaps were 11.6, 10.0, 7.7, 6.3, 8.8, and 4.7, and 5.1, 6.4, 2.4, 3.2, 2.7, and 1.1, respectively. Likert scale inter-rater correlation was strong, with coefficient = 0.80.On average, STSG over de-epithelialized myogenous and adipofascial free tissue transfers produced a better color match than the skin paddles of donor sites, with the exception of the radial forearm donor site. Delta-E values obtained from photos correlated well with expert ratings of color match. This reliable technique for quantifying color match may be used in future studies.3 Laryngoscope, 132:1753-1759, 2022.

Tumor heterogeneity is a major challenge for oncology drug discovery and development. Understanding of the spatial tumor landscape is key to identifying new targets and impactful model systems. Here, we test the utility of spatial transcriptomics (ST) for oncology discovery by profiling 40 tissue sections and 80,024 capture spots across a diverse set of tissue types, sample formats, and RNA capture chemistries. We verify the accuracy and fidelity of ST by leveraging matched pathology analysis, which provides a ground truth for tissue section composition. We then use spatial data to demonstrate the capture of key tumor depth features, identifying hypoxia, necrosis, vasculature, and extracellular matrix variation. We also leverage spatial context to identify relative cell-type locations showing the anti-correlation of tumor and immune cells in syngeneic cancer models. Lastly, we demonstrate target identification approaches in clinical pancreatic adenocarcinoma samples, highlighting tumor intrinsic biomarkers and paracrine signaling.

pPD-1 is expressed on antigen-stimulated T cells and induces a downstream signaling pathway that works by negative feedback to inhibit T cell proliferation, cytokine release, and cytotoxicity. PD-1 antibodies increase tumor cell killing peripherally and have a role in advanced melanoma treatment. We describe a case of an 84 year old female with stage 4 metastatic melanoma in a trial of the PD-1 inhibitor pembrolizumab who developed multiple keratoacanthomas after several months of treatment. While keratoacanthomas have been reported in patients taking BRAF inhibitors, no such reports exist for those on pembrolizumab, making this the first case report to point out this association for further investigative studies./ppemJ Drugs Dermatol. 2017;16(5):513-515./em/p.

Importance Microcystic adnexal carcinoma (MAC) occurs primarily in older adults of white race/ethnicity on sun-exposed skin of the head and neck. There are no formal guiding principles based on expert review of the evidence to assist clinicians in providing the highest-quality care for patients. Objective To develop recommendations for the care of adults with MAC. Evidence review A systematic review of the literature (1990 to June 2018) was performed using MEDLINE, Embase, Web of Science, and the Cochrane Library. The keywords searched were microcystic adnexal carcinoma, sclerosing sweat gland carcinoma, sclerosing sweat duct carcinoma, syringomatous carcinoma, malignant syringoma, sweat gland carcinoma with syringomatous features, locally aggressive adnexal carcinoma, and combined adnexal tumor. A multidisciplinary expert committee critically evaluated the literature to create recommendations for clinical practice. Statistical analysis was used to estimate optimal surgical margins. Findings In total, 55 studies met our inclusion criteria. The mean age of 1968 patients across the studies was 61.8 years; 54.1% were women. Recommendations were generated for diagnosis, treatment, and follow-up of MAC. There are 5 key findings of the expert committee based on the available evidence: (1) A suspect skin lesion requires a deep biopsy that includes subcutis. (2) MAC confined to the skin is best treated by surgery that examines the surrounding and deep edges of the tissue removed (Mohs micrographic surgery or complete circumferential peripheral and deep margin assessment). (3) Radiotherapy can be considered as an adjuvant for MAC at high risk for recurrence, surgically unresectable tumors, or patients who cannot have surgery for medical reasons. (4) Patients should be seen by a physician familiar with MAC every 6 to 12 months for the first 5 years after treatment. Patient education on photoprotection, periodic skin self-examination, postoperative healing, and the possible normal changes in local sensation (eg, initial hyperalgesia) should be considered. (5) There is limited evidence to guide the treatment of metastasis in MAC due to its rarity. Limitations of our findings are that the medical literature on MAC comprises only retrospective reviews and descriptions of individual patients and there are no controlled studies to guide management. Conclusions and relevance The presented clinical practice guidelines provide an outline for the diagnosis and management of MAC. Future efforts using multi-institutional registries may improve our understanding of the natural history of the disease in patients with lymph node or nerve involvement, the role of radiotherapy, and the treatment of metastatic MAC with drug therapy.

Motivation: Gene expression profiling is an important tool for gaining insight into biology. Novel strategies are required to analyze the growing archives of microarray data and extract useful information from them. One area of interest is in the construction of gene association networks from collections of profiling data. Various approaches have been proposed to construct gene networks using profiling data, and these networks have been used in functional inference as well as in data visualization. Here, we investigated a non-parametric approach to translate profiling data into a gene network. We explored the characteristics and utility of the resulting network and investigated the use of network information in analysis of variance models and hypothesis testing. Results: Our work is composed of two parts: gene network construction and partitioning and hypothesis testing using sub-networks as groups. In the first part, multiple independently collected microarray datasets from the Gene Expression Omnibus data repository were analyzed to identify probe pairs that are positively co-regulated across the samples. A co-expression network was constructed based on a reciprocal ranking criteria and a false discovery rate analysis. We named this network Reference Gene Association (RGA) network. Then, the network was partitioned into densely connected sub-networks of probes using a multilevel graph partitioning algorithm. In the second part, we proposed a new, MANOVA-based approach that can take individual probe expression values as input and perform hypothesis testing at the sub-network level. We applied this MANOVA methodology to two published studies and our analysis indicated that the methodology is both effective and sensitive for identifying transcriptional sub-networks or pathways that are perturbed across treatments. Contact: Nathan.Siemers@bms.com or Ruiru.Ji@bms.com