The incidence of cutaneous malignant melanoma has increased dramatically in Caucasians the last few decades, an increase that is partly explained by altered sun exposure habits. For the individual patient, with a localized disease, the tumor thickness of the excised lesion is the most important prognostic factor. However, there is a need to identify characteristics that can place patients in certain risk groups.

In this study, the protein expression of multiple proteins in malignant melanoma tumors was studied, with the aim of identifying potential new candidate biomarkers. Representative samples from melanoma tissues were assembled in a tissue microarray format and protein expression was detected using immunohistochemistry. Multiple cohorts were used and for a subset of proteins the expression was also analyzed in melanocytes in normal skin and in benign nevi. The immunohistochemical staining was evaluated manually and for part of the proteins also with an automated algorithm.

The protein expression of STX7 was described for the first time in tumors of the melanocytic lineage. Stronger expression of STX7 and SOX10 was seen in superficial spreading melanomas compared with nodular malignant melanomas. An inverse relationship between STX7 expression and T-stage was seen and between SOX10 expression and T-stage and Ki-67, respectively. In a population-based cohort the expression of MITF was analyzed and found to be associated with prognosis. Twenty-one potential biomarkers were analyzed using bioinformatics tools and a protein signature was identified which had a prognostic value independent of T-stage. The protein driving this signature was RBM3, a protein not previously described in malignant melanoma. Other markers included in the signature were MITF, SOX10 and Ki-67.

In conclusion, the protein expression of numerous potential biomarkers was extensively studied and a new prognostic protein panel was identified which can be of value for risk stratification.

Background: Microphthalmia associated transcription factor (MITF) protein has a central role in the differentiation and survival of melanocytes. The aim of the study was to investigate whether MITF can be employed as a prognostic marker in patients operated on for cutaneous malignant melanoma.

Methods: A cohort study design based on information collected from population-based registers. For included patients tissue microarrays and immunohistochemistry were employed to study the protein expression of MITF in the primary malignant melanoma tumors by estimating the fraction of positive tumor cells and the staining intensity.

Results: The vast majority of tumors expressed MITF in >25% of the tumor cells with a strong staining intensity and looking at these factors individually these patients had a better prognosis. When cell fraction and intensity were combined a high-risk group dying of malignant melanoma was identified as those with 25% -75% of tumor cells staining with weak intensity and those with <25% of tumor cells staining with strong intensity. However, the majority of the deaths occurred in the lower risk groups.

Conclusions: Although a high-risk group for death in malignant melanoma was identified we conclude that MITF is not useful as a prognostic marker because of the distribution of that particular expression in the population.

Impact: Our results indicate a bi-phasic pattern of MITF expression and although not useful as a prognostic marker these results are in line with other experimental studies and are relevant to explore further.

Human cytomegalovirus (CVM) has been detected by immunohistochemistry (IHC) in brain tumours; however, whether CMV antigen is seen in melanomas has not yet been elucidated. Applying IHC, melanoma tissue was assessed for the expression of pp65, a tegument protein of CMV. Two cohorts were available, cohort-I and II, the latter included also related metastasis. In addition to IHC, in situ hybridisation (ISH) was carried out to assess whether CMV related genetic sequences were detectable in a subset of cases. Seventy per cent of the 142 cases in cohort-I and 50% of the 37 cases in cohort-II displayed immunoreactivity (IR). In both cohorts, the IHC outcome correlated with T-stage (Cohort I: Spearman 0.22, p = 0.01, Cohort II: Fisher exact text 0.04). In 30 of cohort-II cases, when IHC staining was carried out on both the primary tumour and the corresponding metastasis, no change in IR was noted in 53%; in 20%, the IR was lower and in 27% higher in the metastasis when compared with the primary tumour. These results were significant (Fisher exact test 0.03). Applying ISH technique on four tumour cases with detectable pp65 protein, CMV related genetic sequence was not detected. Here, we demonstrate, congruent with observations published for brain tumours, that the protein pp65 is indeed observed in substantial number of melanoma cases with IHC; however, no signal was detected with ISH technique. These findings are in line with previously reported studies, demonstrating that the role of CMV in tumours is still debatable.

Background: Standardized care pathway (SCP) was introduced by the Swedish health authorities to eliminate unwanted delay in the diagnostics of cancer patients; for melanoma, SCP started in 2016. The aim of this study was to investigate the impact of SCP on reporting time for invasive melanomas.

Materials and methods: Information on reporting time was collected on all samples handled according to the SCP and on all invasive melanomas diagnosed in 2016–2018 at the Department of Clinical Pathology, Akademiska University Hospital, Uppsala, Sweden.

Results: During the study period, 205 samples were handled according to the SCP, resulting in 53 cases (26%) diagnosed with invasive melanomas. A total of 301 invasive melanomas from 286 patients were diagnosed during the study period; 67 (22%) were submitted as SCP, 36 (12%) as a general priority case, and 198 (66%) as non-priority. The reporting time for the SCP cases was 8 days, for general priority cases 6 days, and for non-priority cases it was 24 days. The reporting time increased from 18 to 31 days for the non-priority cases and from 15 to 25 days for all cases with invasive melanomas during the study period.

Conclusion: This study demonstrates prolonged reporting times for invasive melanomas since the implementation of SCP. This is probably caused by the crowd-out effect of the SCP samples, limited personnel resources, and inaccuracy of the clinical diagnosis. SCP might therefore be a suboptimal method to shorten reporting times for invasive melanomas.

The thickness of a primary malignant melanoma tumor is the most important prognostic indicator for a patient with primary cutaneous malignant melanoma. To optimize the management and treatment of melanoma patients there is an unmet need to identify characteristics that can further stratify melanoma patients into high or low risk for progressive disease. Despite numerous studies no single marker has yet been shown to add significant prognostic information. An algorithmic approach, combining data from several markers provides an attractive model to identify patients of increased risk of dying from malignant melanoma. The primary aim of the present study was to analyze the correlation between clinical outcome and protein expression patterns of multiple proteins in malignant melanoma tumors using immunohistochemistry and tissue microarrays. Candidate proteins were identified based on a selective and differential expression pattern in melanoma tumors and tested in a cohort of 143 melanoma patients. Protein expression was analyzed using both manual scoring and automated image analysis-based algorithms. We found no single marker of prognosis that was independent of tumor thickness. When combining potential prognostic markers we could define a prognostic index, based on RBM3, MITF, SOX10 and Ki-67, that was independent of tumor thickness in multivariate analysis. Our findings suggest that a good prognosis signature can be identified in melanoma patients with tumors showing a low fraction of Ki-67 positive tumor cells and a high fraction of RBM3 positive tumor cells combined with low intensity levels of SOX10 and MITF.

BACKGROUND: Patients with metastazing malignant melanoma have a poor outcome and determination of thickness of the primary tumor remains as the most important prognostic predictor. The aim of this study was to use an antibody-based proteomics strategy to search for new molecular markers associated with melanoma progression. Two proteins, TRP-1 and galectin-1, were identified as proteins with enhanced expression in cells from the melanocytic lineage. PATIENTS AND METHODS: Protein profiling of TRP-1 and galectin-1 together with proliferation marker Ki-67 and melanocyte marker Melan-A was performed in normal tissues from 144 individuals and in 216 different tumors using tissue microarrays and immunohistochemistry. The protein expression pattern was further analyzed in a defined cohort of 157 patients diagnosed with invasive cutaneous malignant melanoma. RESULTS: Both TRP-1 and galectin-1 were highly expressed in normal melanocytes and melanoma. The expression of TRP-1 was inversely correlated with tumor stage (p=0.002, (R=-0.28)). Neither TRP-1 or galectin-1 was associated with overall or disease free survival (p>0.14, p>0.46 respectively). Ki-67 was associated with tumor stage and survival (p<0.001). CONCLUSION: TRP-1 and galectin-1 protein expression patterns were determined in normal and cancer tissues and both proteins were expressed in the majority of the malignant melanomas. There was no correlation between TRP-1 or galectin-1 expression and survival.

Background: Cancer immunity is based on the interaction of a multitude of cells in the spatial context of the tumour tissue. Clinically relevant immune signatures are therefore anticipated to fundamentally improve the accuracy in predicting disease progression.

Methods: Through a multiplex in situ analysis we evaluated 15 immune cell classes in 1481 tumour samples. Single-cell and bulk RNAseq data sets were used for functional analysis and validation of prognostic and predictive associations.

Findings: By combining the prognostic information of anti-tumoural CD8+ lymphocytes and tumour supportive CD68+CD163+ macrophages in colorectal cancer we generated a signature of immune activation (SIA). The prognostic impact of SIA was independent of conventional parameters and comparable with the state-of-art immune score. The SIA was also associated with patient survival in oesophageal adenocarcinoma, bladder cancer, lung adenocarcinoma and melanoma, but not in endometrial, ovarian and squamous cell lung carcinoma. We identified CD68+CD163+ macrophages as the major producers of complement C1q, which could serve as a surrogate marker of this macrophage subset. Consequently, the RNA-based version of SIA (ratio of CD8A to C1QA) was predictive for survival in independent RNAseq data sets from these six cancer types. Finally, the CD8A/C1QA mRNA ratio was also predictive for the response to checkpoint inhibitor therapy.

Interpretation: Our findings extend current concepts to procure prognostic information from the tumour immune microenvironment and provide an immune activation signature with high clinical potential in common human cancer types.

Aims: Immunohistochemistry is a routine practice in clinical cancer diagnostics and also an established technology for tissue-based research regarding biomarker discovery efforts. Tedious manual assessment of immunohistochemically stained tissue needs to be fully automated to take full advantage of the potential for high throughput analyses enabled by tissue microarrays and digital pathology. Such automated tools also need to be reproducible for different experimental conditions and biomarker targets. In this study we present a novel supervised melanoma specific pattern recognition approach that is fully automated and quantitative. Methods and Results: Melanoma samples were immunostained for the melanocyte specific target, Melan-A. Images representing immunostained melanoma tissue were then digitally processed to segment regions of interest, highlighting Melan-A positive and negative areas. Color deconvolution was applied to each region of interest to separate the channel containing the immunohistochemistry signal from the hematoxylin counterstaining channel. A support vector machine melanoma classification model was learned from a discovery melanoma patient cohort (n = 264) and subsequently validated on an independent cohort of melanoma patient tissue sample images (n = 157). Conclusion: Here we propose a novel method that takes advantage of utilizing an immuhistochemical marker highlighting melanocytes to fully automate the learning of a general melanoma cell classification model. The presented method can be applied on any protein of interest and thus provides a tool for quantification of immunohistochemistry-based protein expression in melanoma.

Background and aims. Fecal calprotectin (FC) is used as a marker for intestinal inflammation in inflammatory bowel disease (IBD) but there is no reliable marker for collagenous colitis (CC). We have previously demonstrated that the mucosal inflammation in CC is characterized by eosinophil activation, which is restored during budesonide treatment, but there is no enhanced neutrophil activity. The aim of this study was to evaluate the use of fecal eosinophil cationic protein (F-ECP) and eosinophil protein X (F-EPX) compared with the neutrophil-derived myeloperoxidase (F-MPO) and FC in patients treated for active CC. Methods. Patients with active CC (n = 12) were studied before and after 3, 7, 28 and 56 days of budesonide treatment. Clinical symptoms and stool frequency were recorded, fecal samples were collected, and F-ECP, F-EPX, F-MPO and FC were measured at each occasion. Results. All but one patient achieved remission. On inclusion 92%, 67%, 67% and 75% of the patients had elevated F-ECP, F-EPX, F-MPO and FC levels, respectively. All markers decreased during the treatment, particularly F-ECP and F-EPX, which decreased after only 3 days. At the end of the study 100%, 92%, 83% and 75% of the patients had normal F-ECP, F-EPX, F-MPO and FC values, respectively. Conclusion. F-ECP demonstrated the best discriminating capacity in detecting active CC. A normalized F-ECP and F-EPX may further be studied as a marker for successful treatment. During budesonide treatment there is a rapid fall in F-ECP and F-EPX, accompanied by clinical improvement, indicating an essential role for the eosinophil participating in the pathophysiology of CC.