Highly specific vaginal microbiome signature for gynecological cancersOriginal paper
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.
Read MoreWhat was studied?
Researchers pooled vaginal 16S rRNA sequencing data from 529 women across 10 public bioprojects: 348 with gynecologic cancer (cervical, ovarian, or endometrial) and 181 cancer-free controls. The goal was to define a vaginal microbiome signature for gynecologic cancer and test it as a diagnostic biomarker.
How was it studied?
Raw sequence data were processed with VSEARCH and compared using Chao1, Shannon, and Simpson alpha-diversity indices and Bray-Curtis beta-diversity. LEfSe identified differentially abundant taxa, Spearman correlation built a co-abundance network, and a random forest model based on genus-level abundance was trained and validated, including leave-one-dataset-out testing.
What did they find?
Cancer patients had significantly higher vaginal alpha-diversity and distinctly separated beta-diversity from controls, unrelated to menopausal status. Firmicutes and Lactobacillus were depleted, while Bacteroidetes, Proteobacteria, Prevotella, Streptococcus, and Anaerococcus were enriched. Of 111 differentially abundant ASVs, 77 were enriched in cancer patients. A 56-genus random forest model reached 84.96% accuracy (AUC), with leave-one-dataset-out validation averaging 0.70.
Why it matters
According to PubMed, this cross-study analysis suggests a reproducible vaginal dysbiosis signature, marked by Lactobacillus loss and pathobiont enrichment, that may support non-invasive early screening for gynecologic cancers. [DOI](https://doi.org/10.1515/biol-2022-0850)