This Research Topic compiles six articles that investigate the molecular profiles and prognostic indicators across a spectrum of malignancies, ranging from prevalent carcinomas to rare sarcomas. The shared objective across these studies is to translate molecular and clinical data into actionable tools for patient stratification and targeted intervention.

In the context of biomarker discovery for common solid tumors, several contributions identified specific genetic and proteomic signatures linked to patient outcomes and the tumor immune microenvironment. Jiang et al. developed a 5-gene prognostic model based on disulfidptosis-related genes in colon cancer, demonstrating its utility in predicting overall survival and reflecting immune infiltration characteristics. For non-small cell lung cancer, Podemska et al. reported that MRPL23 overexpression serves as an independent prognostic factor for shorter overall survival, particularly within the squamous cell carcinoma subtype. Similarly, Jiang et al. established E2F2 as a risk factor in serous ovarian cancer, linking its elevated expression to poor prognosis, specific immune cell recruitment, and altered drug sensitivity.

Beyond common epithelial tumors, this Research Topic addresses the molecular characterization of rare and complex malignancies. Wei et al. provided a comprehensive mass spectrometry-based proteomic analysis of low-grade undifferentiated spindle cell sarcoma (USCS). By identifying differentially expressed proteins such as PHRF1 and DIDO1, their work offers baseline data for potential therapeutic targets in a disease that currently lacks specific predictive markers. Expanding on the complexity of rare clinical presentations, Xu et al. detailed a case involving the coexistence of low-grade pulmonary mucinous epithelioid carcinoma and metastatic adrenal sarcomatoid carcinoma, highlighting the critical role of the BRAF p.V600E mutation in tracking metastatic progression and guiding personalized targeted therapy.

Finally, the integration of clinical parameters into predictive models is addressed by Bai et al., who constructed a multiple linear regression model to predict the preoperative peritoneal cancer index in patients with pseudomyxoma peritonei. This approach utilizes standard preoperative variables to estimate surgical disease burden.

Together, these studies illustrate the ongoing transition from broad histopathological classification to precise molecular and clinical profiling, providing specific data points to optimize risk assessment and individualized treatment strategies.

XY: Writing – original draft, Writing – review and editing.

The author(s) declared that financial support was not received for this work and/or its publication.

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that generative AI was not used in the creation of this manuscript.

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Keywords

malignant tumors, molecular profiling, precision oncology, prognostic biomarkers, rare malignancies, tumor immune microenvironment

Citation

Yang X (2026) Editorial: Clinical molecular biological characteristics of malignant tumors. Front. Mol. Biosci. 13:1824594. doi: 10.3389/fmolb.2026.1824594

Received

06 March 2026

Accepted

10 March 2026

Published

14 April 2026

Volume

13 - 2026

Edited and reviewed by

Matteo Becatti, University of Firenze, Italy

Updates

Copyright

© 2026 Yang.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xi Yang, yangxi19900601@126.com

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.