As science culture gravitates toward a more holistic inclusion of both males and females in research design, the outlining of sex differences and their respective intersections with disease physiology and pathophysiology should see reciprocal expansion. Melanoma skin cancer, for example, has observed a female advantage in incidence, mortality, and overall survival since the early 1970s. The exact biological mechanism of this trend, however, is unclear and further complicated by a layering of clinical variables such as skin phototype, age, and body mass index. In this perspective, we highlight epidemiological evidence of sex differences in melanoma and summarize the landscape of their potential origin. Among several biological hallmarks, we make a note of sex‐specific immune profiles—along with divergent hormonal regulation, social practices, DNA damage and oxidative stress responses, body composition, genetic variants, and X‐chromosome expression—as probable drivers of disparity in melanoma initiation and progression. This review further focuses the conversation of sex as an influencing factor in melanoma development and its potential implication for disease management and treatment strategies.

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

Extracellular vesicles (EVs) are membrane‐bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept. Summary: Extracellular vesicles (EVs) have enormous potential as biomarkers of diseases, as they can carry signatures of the cells they are derived from and the pathogenesis process. Biofluids, such as blood plasma, are highly complex and contain many components with physicochemical properties similar to those of EVs, making it challenging to obtain pure EV fractions. Challenges in obtaining pure preparations represent a main hurdle for studying EVs, and their components are potential biomarkers. This article explores the concept of studying EV proteins within complex samples, discussing opportunities and needs to move this field forward.

Background: The natural day-night cycle synchronizes our circadian rhythms, but modern work practices like night shifts disrupt this pattern, leading to increased exposure to nighttime light. This exposure is linked to various health issues. While some studies have explored the effects of night shifts on human circadian rhythms, there is limited research on the consequences of long-term exposure to shift-work light conditions. Rodents can provide valuable insights into these effects. This study aimed to examine how short- or long-term exposure to rotating shifts and chronic jetlag affects the core circadian oscillators in the liver and skin of mammals. Methods: C57BL/6J male mice were subjected to simulated shift-work light conditions, including short-term or long-term rotating shifts and chronic jet-lag conditions. Liver and skin samples were collected every four hours over a 24-hour period on the second day of constant darkness. RNA was extracted and qRT-PCR analysis was conducted to measure the circadian gene expression in liver and skin tissues. Circadian rhythm analysis using CircaCompare compared the control group to mice exposed to shift-work light conditions. Results: The liver's circadian clock is significantly altered in mice under long-term rotating shift conditions, with a lesser but still noticeable impact in mice experiencing chronic jetlag. However, short-term rotating shift conditions do not significantly affect the liver's circadian clock. Conversely, all three simulated shift conditions affect the skin's circadian clock, indicating that the skin clock is more sensitive to shift-work light conditions than the liver clock. Compared to the liver, the skin's circadian clock is greatly affected by long-term rotating shift conditions. Conclusions: The study findings indicate more pronounced disturbances in the canonical clock genes of the skin compared to the liver under simulated shift-work light conditions. These results suggest that the skin clock is more vulnerable to the effects of shift-work.

Background: The natural day-night cycle synchronizes our circadian rhythms, but modern work practices like night shifts disrupt this pattern, leading to increased exposure to nighttime light. This exposure is linked to various health issues. While some studies have explored the effects of night shifts on human circadian rhythms, there is limited research on the consequences of long-term exposure to shift-work light conditions. Rodents can provide valuable insights into these effects. This study aimed to examine how short- or long-term exposure to rotating shifts and chronic jetlag affects the core circadian oscillators in the liver and skin of mammals. Methods: C57BL/6J male mice were subjected to simulated shift-work light conditions, including short-term or long-term rotating shifts and chronic jet-lag conditions. Liver and skin samples were collected every four hours over a 24-hour period on the second day of constant darkness. RNA was extracted and qRT-PCR analysis was conducted to measure the circadian gene expression in liver and skin tissues. Circadian rhythm analysis using CircaCompare compared the control group to mice exposed to shift-work light conditions. Results: The liver's circadian clock is significantly altered in mice under long-term rotating shift conditions, with a lesser but still noticeable impact in mice experiencing chronic jetlag. However, short-term rotating shift conditions do not significantly affect the liver's circadian clock. Conversely, all three simulated shift conditions affect the skin's circadian clock, indicating that the skin clock is more sensitive to shift-work light conditions than the liver clock. Compared to the liver, the skin's circadian clock is greatly affected by long-term rotating shift conditions. Conclusions: The study findings indicate more pronounced disturbances in the canonical clock genes of the skin compared to the liver under simulated shift-work light conditions. These results suggest that the skin clock is more vulnerable to the effects of shift-work.