The skin, as the outermost barrier, harbors a unique microbial consortium. While the skin microbiota plays a crucial role in maintaining homeostasis, disruptions in host-microbe interactions have been associated with chronic inflammatory skin conditions such as atopic dermatitis and psoriasis vulgaris. However, the specifics of individual host-microbe interactions, particularly their anti-inflammatory effects that would serve as seeds for therapeutic agents, remain largely unexplored. Furthermore, how the skin environment that is colonized by microbiota affects the bacterial metabolic activity is undetermined. In this article, we introduce that Staphylococcus cohnii can suppress skin inflammation via promotion of glucocorticoid synthesis in the skin and the proteomic approach used for gene expression analysis of bacteria colonized on the skin. Additionally, we will present the latest findings on the stratum corneum, the outermost layer of the skin, where skin microbiota colonize. By using various methods including proteomic analysis, we expect to elucidate beneficial host-microbe interactions and develop new treatments using skin microbiota.

Journal of Proteome Data and Methods (JPDM) publishes data papers, but many researchers find it difficult to understand the difference between data papers and regular research papers and their purpose. This paper thus discusses three topics: (1) a summary of how data publication became mandatory, (2) what the purpose and contents of a data paper should be, and (3) specific points to keep in mind when writing a data paper for JPDM. The first topic focuses on the Human Genome Project and other large-scale research projects and the evolution of data publication guidelines, rather than technical aspects such as the spread of the Internet. In the next subject, examples of data reuse and how other data journals are positioning their data papers will be presented. The last subject will be based on reviewers’ comments on papers actually submitted to JPDM, citing specific sections.

Rare cancers encounter significant delays in the development of diagnostic and therapeutic strategies due to their inherently low incidence. The limited availability of clinical specimens and patient-derived cancer model further constrains opportunities for translational research. In this review, I discuss the challenges posed by small case numbers to proteomic analyses of rare cancers and explore strategies to address them, including the utilization of archival formalin-fixed paraffin-embedded (FFPE) specimens and the establishment of living biobanks. I also present patient-derived cancer models, such as sarcoma cell lines and xenografts established in my laboratory, and emphasize the importance of resource sharing to advance research. Furthermore, I propose the concept of “reverse innovation,” whereby methodologies and frameworks developed through rare cancer research may be applied to studies of molecularly stratified subtypes of more common cancers. Confronting the challenges inherent in disease rarity represents a forward-looking initiative that anticipates future directions in oncology. Promoting rare cancer research, through the development of integrated biobanking systems for clinical specimens and the systematic generation of cancer models, is expected to provide critical insights into disease mechanisms and foster the discovery of novel therapeutic options to improve survival and quality of life for patients with rare cancers.