Cutaneous T-Cell Lymphomas (CTCL) are rare, but potentially devastating malignancies, whose pathogenesis remains poorly elucidated. Unfortunately, currently it is not possible to predict based on the available criteria in which patients the cancer will progress and which patients will experience an indolent disease course. Furthermore, at early stages this malignancy often masquerades as psoriasis, chronic eczema or other benign inflammatory dermatoses. As a result, it takes on average 6 y to diagnose this lymphoma since its initial presentation. In this study, we performed transcription expression profiling using TruSeq targeted RNA gene expression on 181 fresh and formalin-fixed and paraffin-embedded (FFPE) skin samples from CTCL patients and patients affected by benign inflammatory dermatoses that often mimic CTCL clinically and on histology (e.g., psoriasis, chronic eczema, etc.) We also analyzed multiple longitudinal biopsies that were obtained from the same patients over time. Our results underscore significant molecular heterogeneity with respect to gene expression between different patients and even within the same patients over time. Our study also confirmed and genes as being differentially expressed between CTCL and benign skin biopsies. In addition, we found that differential expression for a subset of these markers (e.g., and) may be useful in prognosticating this disease. This research, combined with other molecular analyses, prepares the foundation for the development of personalized molecular approach toward diagnosis and management of CTCL.

Deregulation of STAT signaling has been implicated in the pathogenesis for a variety of cancers, including CTCL. Constitutive activation of STAT5 and STAT3 was observed in early and late stages of CTCL, respectively. In early stages, IL-2, IL-7 and IL-15 signaling via JAK1 and JAK3 kinases is believed to be responsible for activating STAT5, while in advanced stages development of IL-21 autocrine signaling is thought to be important for STAT3 activation. Recent molecular evidence further suggests that upregulation of STAT5 in early disease stages results in increased expression of oncogenic miR-155 microRNA that subsequently targets STAT4 expression on mRNA level. STAT4 signaling is known to be critical for T helper (Th) 1 phenotype differentiation and its loss results in a switch from Th1 to Th2 phenotype in malignant T cells. During this switch the expression of STAT6 is often upregulated in CTCL. In advanced stages, activation of STAT3 and STAT5 may become completely cytokine-independent and be driven only via constitutively active JAK1 and JAK3 kinases. Further research into the molecular pathogenesis of JAK/STAT signaling in this cancer may enable us to develop effective therapies for our patients.

Purpose While many Mycosis Fungoides (MF) patients presenting with stage I disease enjoy an indolent disease course and normal life expectancy, about 15-20% of them progress to higher stages, and most ultimately succumb to their disease. Currently, it's not possible to predict which patients will progress and which patients will have a stable disease. Previously, we conducted microarray analyses with RT-PCR validation of gene expression in biopsy specimens from 60 stage I-IV CTCL patients, identified three distinct clusters based upon transcription profile and correlated our molecular findings with 6 years of clinical follow up. Experimental Design We test by RT-PCR within our prediction model the expression of ∼240 genes that were previously reported to play an important role in CTCL carcinogenesis. We further extend the clinical follow up of our patients to 11 years. We compare the expression of selected genes between MF/Sézary Sydrome and benign inflammatory dermatoses that often mimic this cancer. Results Our findings demonstrate that 52 out of the ∼240 genes can be classified into cluster 1-3 expression patterns and such expression is consistent with their suggested biological roles. Moreover, we determined that 17 genes (CCL18, CCL26, FYB, T3JAM, MMP12, LEF1, LCK, ITK, GNLY, IL2RA, IL-26, IL-22, CCR4, GTSF1, SYCP1, STAT5A, TOX) are able to both identify patients who are at risk of progression and also distinguish MF/SS from benign mimickers. Conclusions This study, combined with other gene expression analyses, prepares the foundation for the development of personalized molecular approach towards diagnosis and treatment of CTCL.

The current results provide a comprehensive analysis of CTCL burden in Canada and highlight several important areas of geographic case clustering. These findings argue that industrial exposures may play an important role in promoting CTCL pathogenesis. Cancer 2017;123:3550-67. © 2017 American Cancer Society.

BackgroundCurrent wound assessment practices are lacking on several measures. For example, the most common method for measuring wound size is using a ruler, which has been demonstrated to be crude and inaccurate. An increase in periwound temperature is a classic sign of infection but skin temperature is not always measured during wound assessments. To address this, we have developed a smartphone application that enables non-contact wound surface area and temperature measurements. Here we evaluate the inter-rater reliability and accuracy of this novel point-of-care wound assessment tool.Methods and findingsThe wounds of 87 patients were measured using the Swift Wound app and a ruler. The skin surface temperature of 37 patients was also measured using an infrared FLIR™ camera integrated with the Swift Wound app and using the clinically accepted reference thermometer Exergen DermaTemp 1001. Accuracy measurements were determined by assessing differences in surface area measurements of 15 plastic wounds between a digital planimeter of known accuracy and the Swift Wound app. To evaluate the impact of training on the reproducibility of the Swift Wound app measurements, three novice raters with no wound care training, measured the length, width and area of 12 plastic model wounds using the app. High inter-rater reliabilities (ICC = 0.97–1.00) and high accuracies were obtained using the Swift Wound app across raters of different levels of training in wound care. The ruler method also yielded reliable wound measurements (ICC = 0.92–0.97), albeit lower than that of the Swift Wound app. Furthermore, there was no statistical difference between the temperature differences measured using the infrared camera and the clinically tested reference thermometer.ConclusionsThe Swift Wound app provides highly reliable and accurate wound measurements. The FLIR™ infrared camera integrated into the Swift Wound app provides skin temperature readings equivalent to the clinically tested reference thermometer. Thus, the Swift Wound app has the advantage of being a non-contact, easy-to-use wound measurement tool that allows clinicians to image, measure, and track wound size and temperature from one visit to the next. In addition, this tool may also be used by patients and their caregivers for home monitoring.