Whole-transcriptome sequencing and machine learning detect molecular signatures of endometrial cancer in non-invasive vaginal swabs

Synopsis

The first peer-reviewed PinkDx paper. Women undergoing hysterectomy were enrolled in the exploratory PNK001 study and provided vaginal swabs, ectocervical swabs, endocervical cytobrushes and endometrial tissue; sequencing data came from 27 PNK001 participants and 46 Cooperative Human Tissue Network samples. Classifiers trained on expressed genes and variant counts distinguished 5 benign from 15 malignant cases in cytobrush, ectocervical and vaginal swab samples with average cross-validation AUCs of 0.6 to 0.96, and tissue-trained classifiers reached AUCs of 0.97 and 0.98 on an independent test set. Kennedy is twelfth of fourteen authors.

In the career genome

• PinkDxChapter 13 · Strand A · Founder

  PinkDx, Inc.

  PinkDx

  Co-founder and Chief Scientific Officer

  APR 2024 – PRESENT
• PinkDxChapter 14 · Strand B · Research

  PinkDx, Inc.

  Reading endometrial cancer from a vaginal swab

  Co-founder and Chief Scientific Officer, PinkDx

  JUL 2024 – PRESENT