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Poster/ePoster Sessions
01. Cervical cancer
#438 Molecular alterations predictive of outcome in early staged cervical cancer : a translational investigation from the SENTICOL III trial
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  1. Maryame El Gani1,
  2. Sabrina Ibadioune2,
  3. Zakhia El Beaino3,
  4. Sophie Vacher4,
  5. Alexandre Degnieau5,
  6. Emmanuelle Jeannot6,
  7. Julien Masliah-Planchon4,
  8. Anne Vincent-Salomon7,
  9. Gwenael Ferron8,
  10. François Golfier9,
  11. Eris Lambaudie10,
  12. Fabrice Narducci11,
  13. Cecile Loaec12,
  14. Jennifer Uzan13,
  15. Fredéric Marchal14,
  16. Marie Plante15,
  17. Patrice Mathevet16,
  18. Maud Kamal17,
  19. Fabrice Lecuru18 and
  20. Ivan Bièche19
  1. 1Department of Gyneacological Oncology and breast surgery, Institut Curie Paris, Paris, France
  2. 2Department of Genetics, Institut Curie, Paris, France, Paris, France
  3. 3Department of Pathology, Hôpital Tenon AP-HP, Paris, France, Paris, France
  4. 4Department of Genetics, Institut Curie, Paris, France
  5. 5Biological Resources Center, Institut Curie, Paris, France
  6. 6Department of Genetics and Departments of Pathology, Institut Curie, Paris, France
  7. 7Department of Pathology, Institut Curie, Paris, France
  8. 8Department of Surgical Oncology, IUCT-Institut Claudius Regaud, Toulouse, France
  9. 9Dept of Gynecological and Oncological Surgery, CHU Lyon Sud – Hospices Civils de Lyon, Lyon, France
  10. 10Department of Gynecologic Oncology, Institut Paoli Calmettes, Marseille, France
  11. 11Department of Gynecologic Oncology, CLCC Centre Oscar Lambret, Lille, France
  12. 12Department of Gynecologic Oncology, Institut de Cancérologie de l’Ouest Centre René Gauducheau,, Saint-Herblain, France
  13. 13Department of Obstetrics and Gynaecology, Centre Hospitalier Intercommunal de Créteil, Créteil, France
  14. 14Dept of Gynecological and Oncological Surgery, Institut de Cancérologie de Lorraine, Université de Lorraine,, Vandoeuvre-Les-Nancy, France
  15. 15Department of Gynecologic Oncology, CHU de Québec, Université Laval, Québec, Canada
  16. 16Department of Gynecologic Oncology, CHUV – Centre Hospitalier Universitaire Vaudois,, Lausanne, Switzerland
  17. 17Drug Development and Innovation Department, Institut Curie,, Paris, France
  18. 18Department of Gyneacological Oncology and breast surgery, Paris, France
  19. 19Department of Genetics, Institut Curie,, Paris, France

Abstract

Introduction/Background Despite of a well managed surgery and good histological and clinical features, some patients relapse after the treatment of early stage cervical cancer. The comprehensive genetic and molecular characteristics of malignant cervical tumours were described by The Cancer Genome Atlas Research Network. However, the TCGA data only published sequencing results with few clinical and histological data. Yet, the literature remains scarce about genetic alterations and outcome correlation in early stage cervical cancer.

Our translational study use a pan-genomic approach to evaluate recurrent genetic alterations seen in early cervical cancer patients. We aim to evaluate the correlation between molecular findings and clinical outcome and to find new prognostic biomarkers in early cervical cancer.

Methodology We included the first 150 patients randomized in the Senticol III trial. This large multicen-tric, prospective, randomized, and international ‘validation study’ tries to validate sentinel node biopsy as nodal staging of early cervical cancers (stage Ia – IIa1).

Cervical tumor slides were analyzed and stratified based on well-established histological criteria (SEDLIS criteria). The immune microenvironment characteristics including TIL’s in-filtration and PDL1 CPS score were assessed. We made HPV detection and typing by PCR of the tumor samples. We performed DNA and RNA extractions from the FFPE tumor specimens. Using the dedicated gene panel developed by our team, we analyzed 571 genes commonly altered in cancer. We performed high throughput RNA sequencing to es-tablish the gene expression profile of each tumor and its associated stroma.

The genomic and transcriptomic analysis assessed the tumor mutational load, the most frequently altered genes and their expression. The biostatistical analyses will correlate mo-lecular alterations, histopathological and clinical classical features, with patient outcome. The different parameters will be first analyzed independently (univariate analysis) and then in a multiparametric manner (logistic regression).

Results TiP : No results

Conclusion TiP : No conclusion

Disclosures No disclosures declared

http://dx.doi.org/10.1136/ijgc-2023-ESGO.144

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