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Abstract Objectives Being met with empathy increases information sharing, treatment coherence, and helps patients to recover faster. However, we do not know how the content of the conversation about disease progression, new treatments, or other issues concerning serious illness affects patients' perceptions of the physician's empathy, and thus, the quality of the conversation. This study aimed to test the hypothesis that patients will rate their physician lower following a “bad news” consultation using the consultation and relational empathy (CARE) measure. Methods A total of 186 outpatients from the Department of Oncology were recruited for this study. After meeting with a patient, the physician filled out a form, placing the patient in either the “bad news” group, or the “neutral/good news” group along with information about the patient and the consultation. The patient was given the CARE measure after the visit. Results The patients who had received bad news rated their physicians a significantly lower score on the CARE measure, even though the effect size was small, than those who had neutral/good news. On average, bad news consultations were 11 min longer. Conclusions Physicians need to be aware of the patients' need to be known and understood, in addition to having skills to attend to emotional cues and concerns, since the current study's finding could be a sign either of the content being projected onto the physician or that the physician is focused on the message rather than on the patient.

Abstract Background In childhood (CCS) and testicular cancer (TCS) survivors, low-grade inflammation may represent a link between testosterone deficiency (hypogonadism) and risk of metabolic syndrome. We aimed to study levels of inflammatory markers in CCS and TCS and the association with hypogonadism and future cardio-metabolic risk factors. Methods Serum levels of inflammatory markers and testosterone were analyzed in CCS (n = 90), and TCS (n = 64, median time from diagnosis: 20 and 2.0 years, respectively), and in controls (n = 44). Differences in levels between patients and controls were calculated using univariate analysis of variance. T-test and logistic regression were applied to compare levels of cardio-metabolic risk factors and odds ratio (OR) of hypogonadism and metabolic syndrome in low and high inflammatory marker groups after 4–12 years of follow up. Adjustment for age, smoking, and active cancer was made. Results TCS and CCS, as compared to controls, had 1.44 (95%CI 1.06–1.96) and 1.25 (95 CI 1.02–1.53) times higher levels of IL-8, respectively. High IL-6 levels were associated with hypogonadism at baseline (OR 2.83, 95%CI 1.25–6.43) and the association was stronger for high IL-6 combined with low IL-10 levels (OR 3.10, 95%CI 1.37–7.01). High IL-6 levels were also associated with higher BMI, waist circumference, insulin, and HbA1c at follow up. High TNF-α was associated with higher diastolic blood pressure. No individual inflammatory marker was significantly associated with risk of metabolic syndrome at follow up. High IL-6 combined with low IL-10 levels were associated with risk of metabolic syndrome (OR 3.83, 95%CI 1.07–13.75), however not statistically significantly after adjustment. Conclusion TCS and CCS present with low-grade inflammation. High IL-6 levels were associated with hypogonadism and cardio-metabolic risk factors. Low IL-10 levels might reinforce the IL-6 mediated risk of developing metabolic syndrome.

Abstract The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in‐depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.

Abstract The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass‐spectrometry‐based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein‐coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.