Sex-based protein differences in lung cancer could reshape treatment approaches

Cancer does not treat men and women the same way. Lung adenocarcinoma strikes women more often. Squamous cell carcinoma of the lung favors men. For years, researchers have wondered why—what is happening inside the cells that produces these divergent patterns? A team at Sanford Burnham Prebys Medical Discovery Institute has begun to answer that question by looking not at genes, but at proteins.

On July 15, 2026, the researchers published their findings in BMJ Oncology, revealing that biological sex shapes the protein landscape of tumors in ways that could fundamentally alter how doctors treat cancer. Among eight cancer types they examined, lung adenocarcinoma stood out most starkly: 901 proteins showed different abundance levels between male and female patients. The discovery suggests that sex is not merely a demographic variable in cancer—it is a biological force that rewires the tumor's molecular machinery.

The work builds on two decades of infrastructure that made such a finding possible. After the Human Genome Project concluded, the National Institutes of Health launched The Cancer Genome Atlas in 2006, sequencing the genomes and gene expression of tens of thousands of cancer samples across 33 cancer types. Five years later came the Clinical Proteomic Tumor Analysis Consortium, which connected the dots between genetic sequences, gene expression patterns, and the actual proteins present in tumors. For the first time, researchers had a public resource to ask questions about the cancer proteome—the full complement of proteins that drive tumor behavior.

Chenghao Zhu, a research assistant professor at the institute, and his colleagues took advantage of this resource by analyzing protein sequencing data from 934 cancer patients. Their approach was methodical: they compared proteins in tumor tissue to proteins in adjacent normal tissue from the same patients, using the healthy cells as a control. This comparison revealed the magnitude of sex-based differences. Lung adenocarcinoma emerged as the most striking case, but kidney renal clear cell carcinoma, pancreatic ductal adenocarcinoma, liver hepatocellular carcinoma, and glioblastoma all showed moderate sex-based protein variation. Colon adenocarcinoma and head and neck squamous cell carcinoma showed no significant differences.

The question then became whether these protein differences actually mattered for cancer biology. The team cross-referenced their findings with data from the Dependency Map Consortium, which identifies genes required for cell survival in different cancer types. When researchers used CRISPR gene editing to knock out genes that showed sex-differential protein abundance in lung adenocarcinoma cell lines, the result was telling: the cells with those genes removed showed worse survival. This suggested the protein differences were not incidental—they were central to how the cancer cells functioned.

Paul Boutros, director of the Cancer Center at Sanford Burnham Prebys, framed the implications plainly: proteins are the primary targets of cancer drugs and the biomarkers doctors use to monitor disease. Understanding how sex shapes the proteome could enable treatment strategies tailored not just to cancer type, but to the individual patient's sex and tumor characteristics. The research team plans to expand this work, analyzing newer data from the Clinical Proteomic Tumor Analysis Consortium and studying how proteins change in response to treatment—a crucial step toward understanding why some patients develop resistance to therapy while others respond well.

The findings represent a shift in how the field thinks about precision medicine. For decades, cancer research has focused on genetic mutations and gene expression. Proteins, however, are where the action happens. They are what actually drives cell behavior, what drugs bind to, what determines whether a tumor grows or shrinks. By revealing that sex fundamentally alters the protein composition of at least some cancers, this work suggests that truly personalized cancer treatment may require accounting for biology that goes far deeper than the tumor's genetic code.