Automatic analysis of nuclear features reveals a non-tumoral predictor of tumor grade in bladder cancer.

BACKGROUND & OBJECTIVES: Tumor grade determines prognosis in urothelial carcinoma. The classification of low and high grade is based on nuclear morphological features that include nuclear size, hyperchromasia and pleomorphism. These features are subjectively assessed by the pathologists and are not numerically measured, which leads to high rates of interobserver variability. The purpose of this study is to assess the value of a computer-based image analysis tool for identifying predictors of tumor grade in bladder cancer. METHODS: Four hundred images of urothelial tumors were graded by five pathologists and two expert genitourinary pathologists using a scale of 1 (lowest grade) to 5 (highest grade). A computer algorithm was used to automatically segment the nuclei and to provide morphometric parameters for each nucleus, which were used to establish the grading algorithm. Grading algorithm was compared to pathologists' agreement. RESULTS: Comparison of the grading scores of the five pathologists with the expert genitourinary pathologists score showed agreement rates between 88.5% and 97.5%.The agreement rate between the two expert genitourinary pathologists was 99.5%. The quantified algorithm based conventional parameters that determine the grade (nuclear size, pleomorphism and hyperchromasia) showed > 85% agreement with the expert genitourinary pathologists. Surprisingly, the parameter that was most associated with tumor grade was the 10th percentile of the nuclear area, and high grade was associated with lower 10th percentile nuclei, caused by the presence of more inflammatory cells in the high-grade tumors. CONCLUSION: Quantitative nuclear features could be applied to determine urothelial carcinoma grade and explore new biologically explainable parameters with better correlation to grade than those currently used.

Short Training Significantly Improves Ganglion Cell Detection Using an Algorithm-Assisted Approach.

CONTEXT.­: Medical education in pathology relies on the accumulation of experience gained through inspection of numerous samples from each entity. Acquiring sufficient teaching material for rare diseases, such as Hirschsprung disease (HSCR), may be difficult, especially in smaller institutes. The current study makes use of a previously developed decision support system using a decision support algorithm meant to aid pathologists in the diagnosis of HSCR. OBJECTIVE.­: To assess the effect of a short training session on algorithm-assisted HSCR diagnosis. DESIGN.­: Five pathologists reviewed a data set of 568 image sets (1704 images in total) selected from 50 cases by the decision support algorithm and were tasked with scoring the images for the presence or absence of ganglion cells. The task was repeated a total of 3 times. Each pathologist had to complete a short educational presentation between the second and third iterations. RESULTS.­: The training resulted in a significantly increased rate of correct diagnoses (true positive/negative) and a decreased need for referrals for expert consultation. No statistically significant changes in the rate of false positives/negatives were detected. CONCLUSIONS.­: A very short (<10 minutes) training session can greatly improve the pathologist's performance in the algorithm-assisted diagnosis of HSCR. The same approach may be feasible in training for the diagnosis of other rare diseases.

Transient cell-in-cell formation underlies tumor relapse and resistance to immunotherapy.

Despite the remarkable successes of cancer immunotherapies, the majority of patients will experience only partial response followed by relapse of resistant tumors. While treatment resistance has frequently been attributed to clonal selection and immunoediting, comparisons of paired primary and relapsed tumors in melanoma and breast cancers indicate that they share the majority of clones. Here, we demonstrate in both mouse models and clinical human samples that tumor cells evade immunotherapy by generating unique transient cell-in-cell structures, which are resistant to killing by T cells and chemotherapies. While the outer cells in this cell-in-cell formation are often killed by reactive T cells, the inner cells remain intact and disseminate into single tumor cells once T cells are no longer present. This formation is mediated predominantly by IFNγ-activated T cells, which subsequently induce phosphorylation of the transcription factors signal transducer and activator of transcription 3 (STAT3) and early growth response-1 (EGR-1) in tumor cells. Indeed, inhibiting these factors prior to immunotherapy significantly improves its therapeutic efficacy. Overall, this work highlights a currently insurmountable limitation of immunotherapy and reveals a previously unknown resistance mechanism which enables tumor cells to survive immune-mediated killing without altering their immunogenicity.

Cancer immunotherapies use the body's own immune system to fight off cancer. But, despite some remarkable success stories, many patients only see a temporary improvement before the immunotherapy stops being effective and the tumours regrow. It is unclear why this occurs, but it may have to do with how the immune system attacks cancer cells. Immunotherapies aim to activate a special group of cells known as killer T-cells, which are responsible for the immune response to tumours. These cells can identify cancer cells and inject toxic granules through their membranes, killing them. However, killer T-cells are not always effective. This is because cancer cells are naturally good at avoiding detection, and during treatment, their genes can mutate, giving them new ways to evade the immune system. Interestingly, when scientists analysed the genes of tumour cells before and after immunotherapy, they found that many of the genes that code for proteins recognized by T-cells do not change significantly. This suggests that tumours' resistance to immune attack may be physical, rather than genetic. To investigate this hypothesis, Gutwillig et al. developed several mouse tumour models that stop responding to immunotherapy after initial treatment. Examining cells from these tumours revealed that when the immune system attacks, they reorganise by getting inside one another. This allows some cancer cells to hide under many layers of cell membrane. At this point killer T-cells can identify and inject the outer cell with toxic granules, but it cannot reach the cells inside. This ability of cancer cells to hide within one another relies on them recognising when the immune system is attacking. This happens because the cancer cells can detect certain signals released by the killer T-cells, allowing them to hide. Gutwillig et al. identified some of these signals, and showed that blocking them stopped cancer cells from hiding inside each other, making immunotherapy more effective. This new explanation for how cancer cells escape the immune system could guide future research and lead to new cancer treatments, or approaches to boost existing treatments. Understanding the process in more detail could allow scientists to prevent it from happening, by revealing which signals to block, and when, for best results.

An Exercise-Induced Metabolic Shield in Distant Organs Blocks Cancer Progression and Metastatic Dissemination.

Exercise prevents cancer incidence and recurrence, yet the underlying mechanism behind this relationship remains mostly unknown. Here we report that exercise induces the metabolic reprogramming of internal organs that increases nutrient demand and protects against metastatic colonization by limiting nutrient availability to the tumor, generating an exercise-induced metabolic shield. Proteomic and ex vivo metabolic capacity analyses of murine internal organs revealed that exercise induces catabolic processes, glucose uptake, mitochondrial activity, and GLUT expression. Proteomic analysis of routinely active human subject plasma demonstrated increased carbohydrate utilization following exercise. Epidemiologic data from a 20-year prospective study of a large human cohort of initially cancer-free participants revealed that exercise prior to cancer initiation had a modest impact on cancer incidence in low metastatic stages but significantly reduced the likelihood of highly metastatic cancer. In three models of melanoma in mice, exercise prior to cancer injection significantly protected against metastases in distant organs. The protective effects of exercise were dependent on mTOR activity, and inhibition of the mTOR pathway with rapamycin treatment ex vivo reversed the exercise-induced metabolic shield. Under limited glucose conditions, active stroma consumed significantly more glucose at the expense of the tumor. Collectively, these data suggest a clash between the metabolic plasticity of cancer and exercise-induced metabolic reprogramming of the stroma, raising an opportunity to block metastasis by challenging the metabolic needs of the tumor. SIGNIFICANCE: Exercise protects against cancer progression and metastasis by inducing a high nutrient demand in internal organs, indicating that reducing nutrient availability to tumor cells represents a potential strategy to prevent metastasis. See related commentary by Zerhouni and Piskounova, p. 4124.

Diffuse Facial Hyperpigmentation as a Presenting Sign of Lupus Erythematosus: Three Cases and Review of the Literature.

Lupus erythematosus (LE) is an autoimmune disorder commonly affecting the skin; cutaneous lesions may indicate systemic involvement, warranting further evaluation. Photosensitivity, which may result in hyperpigmentation, is a well-known feature of the disease. In contrast, the prevalence of primary hyperpigmentation as a presenting sign of LE is not well established. Here, we compare 3 unique cases of diffuse facial hyperpigmentation as the primary manifestation of LE (cutaneous or systemic) and review previously reported cases. Our data highlight the need for considering LE in the differential diagnosis of facial hyperpigmentation and substantiate the importance of this unique lupus variant in early diagnosis and patient evaluation.

Classification of node-positive melanomas into prognostic subgroups using keratin, immune, and melanogenesis expression patterns.

Cutaneous melanoma tumors are heterogeneous and show diverse responses to treatment. Identification of robust molecular biomarkers for classifying melanoma tumors into clinically distinct and homogenous subtypes is crucial for improving the diagnosis and treatment of the disease. In this study, we present a classification of melanoma tumors into four subtypes with different survival profiles based on three distinct gene expression signatures: keratin, immune, and melanogenesis. The melanogenesis expression pattern includes several genes that are characteristic of the melanosome organelle and correlates with worse survival, suggesting the involvement of melanosomes in melanoma aggression. We experimentally validated the secretion of melanosomes into surrounding tissues by melanoma tumors, which potentially affects the lethality of metastasis. We propose a simple molecular decision tree classifier for predicting a tumor's subtype based on representative genes from the three identified signatures. Key predictor genes were experimentally validated on melanoma samples taken from patients with varying survival outcomes. Our three-pattern approach for classifying melanoma tumors can contribute to advancing the understanding of melanoma variability and promote accurate diagnosis, prognostication, and treatment.

Adipocytes sensitize melanoma cells to environmental TGF-ß cues by repressing the expression of miR-211.

Transforming growth factor-ß (TGF-ß) superfamily members are critical signals in tissue homeostasis and pathogenesis. Melanoma grows in the epidermis and invades the dermis before metastasizing. This disease progression is accompanied by increased sensitivity to microenvironmental TGF-ß. Here, we found that skin fat cells (adipocytes) promoted metastatic initiation by sensitizing melanoma cells to TGF-ß. Analysis of melanoma clinical samples revealed that adipocytes, usually located in the deeper hypodermis layer, were present in the upper dermis layer within proximity to in situ melanoma cells, an observation that correlated with disease aggressiveness. In a coculture system, adipocytes secreted the cytokines IL-6 and TNF-α, which induced a proliferative-to-invasive phenotypic switch in melanoma cells by repressing the expression of the microRNA miR-211. In a xenograft model, miR-211 exhibited a dual role in melanoma progression, promoting cell proliferation while inhibiting metastatic spread. Bioinformatics and molecular analyses indicated that miR-211 directly targeted and repressed the translation of TGFBR1 mRNA, which encodes the type I TGF-ß receptor. Hence, through this axis of cytokine-mediated repression of miR-211, adipocytes increased the abundance of the TGF-ß receptor in melanoma cells, thereby enhancing cellular responsiveness to TGF-ß ligands. The induction of TGF-ß signaling, in turn, resulted in a proliferative-to-invasive phenotypic switch in cultured melanoma cells. Pharmacological inhibition of TGF-ß prevented these effects. Our findings further reveal a molecular link between fat cells and metastatic progression in melanoma that might be therapeutically targeted in patients.