Détection moléculaire des métastases des ganglions lymphatique dans le cancer du col de l'utérus

Le Cancer du Col Utérin (CCU) chez la femme est provoqué par le virus oncogénique VPH. La métastase lymphatique ganglionnaire est un facteur pronostique majeur pour l’évolution de ce cancer et sa présence influence la décision thérapeutique. En général, l’envahissement ganglionnaire est diagnostiqué par histologie, mais cette méthode est laborieuse et parfois prise en défaut pour détecter les micrométastases et les cellules cancéreuses isolées et pour donner des résultats rapides en per opératoire. L’outil moléculaire que nous désirons développer pour combler cette lacune est basé sur une analyse d’ARN des gènes du VPH exprimés par les cellules du CCU. Ceci sera fait par transcription réverse de l’ARN cellulaire couplé à une réaction quantitative en chaine par polymérase en temps réel (RT-qPCR). Cette technique devrait nous permettre une détection et une évaluation rapide des micrométastases pour aider à déterminer immédiatement un pronostic fiable et la thérapie associée. C’est un test précis, sensible et rapide pour détecter un envahissement ganglionnaire dans le CCU visant à améliorer la gestion thérapeutique. Le projet est basé sur trois objectifs. En premier lieu, valider les marqueurs moléculaires E6 et E7 de VPH16 et 18 à partir des échantillons frais et des échantillons fixés dans des blocs de paraffine. En deuxième lieu, déterminer la fiabilité et la sensibilité des marqueurs pour la détection des macrométastases, des micrométastases et les cellules tumorales isolées en utilisant la technique de RT-qPCR. En troisième lieu et parallèlement au travail présenté dans ce mémoire, il est nécessaire de constituer une base de données des patientes qui ont le virus VPH16 et 18 intégré dans leur génome, qui ont été traitées et dont nous connaissons déjà le diagnostic final afin de valider la méthode (biobanque). Nous avons réussi à extraire de l’ARNm de haute qualité à partir d’échantillons complexes, à détecter les gènes E6 et E7 de VPH16 et 18 en RT-qPCR, et à déterminer précisément la limite de détection de E6 et E7 dans les échantillons frais qui est une proportion de 0,008% de cellules cancéreuses. Dans les échantillons fixés dans la paraffine, cette limite est de 0,02% et 0,05% pour E6-E7-VPH16 et E6-E7-VPH18 respectivement. Ceci comparativement à une limite de détection histologique de 1% qui est déterminée par immunohistochimie de CK19. Enfin, notre protocole est validé pour VPH18 dans les ganglions lymphatiques du CCU.The presence of lymph nodes metastasis in uterine cervical carcinoma influences therapeutic management and patient survival. The gold standard for metastasis detection is histology. However, histology lacks sensitivity to detect micrometastasis or isolated cancer cells and is not an efficient method for immediate diagnosis during surgery. The molecular tool that we want to develop to fill this gap is based on an analysis of expressed RNA transcripts derived from the HPV genome in cells of uterine cervical carcinoma (UCC). This will be done by reverse transcription of cellular RNA coupled to a quantitative polymerase chain reaction in real-time (RT-qPCR). This technique could allow detection and rapid assessment of micrometastasis to help determine prognosis and an immediate reliable combination therapy. The proposed technique would be a specific test, sensitive and rapid to detect lymph node involvement in the UCC to improve therapy management. Our objective is to constitute a patient bank containing genetic and clinical information. This genetic information will be used to test and improve new molecular markers for UCC metastasis. These markers will be validated using comparisons to traditional histological results and evaluated for their capacity to detect lymph nodes micrometastasis. Ultimately, we wish to develop a reliable molecular diagnosis method useful during surgery and improve our knowledge about the clinical evolution of metastatic UCC. Currently, we are able to extract high quality mRNA from formalin-fixed cells mounted in paraffin blocks and to detect E6 and E7 from HPV16 and HPV18 using RT-qPCR. We have specifically determined the detection limit of E6 and E7, which is 0.008% in the fresh samples and 0.02% and 0.05% for HPV16-E6-E7 and HPV18- E6-E7 respectively in the samples fixed in paraffin blocks. Comparatively, the histological detection limit was determined to be around 1% using immunohistochemistry for CK19 expression. Finally, our protocol has been validated for HPV18 in UCC patient lymph node

Sensitive molecular detection of small nodal metastasis in uterine cervical cancer using HPV16-E6/CK19/MUC1 cancer biomarkers

International audienceMetastatic nodal involvement is a critical prognostic factor in uterine cervical cancer (UCC). To improve current methods of detecting UCC metastases in lymph nodes (LNs), we used quantitative PCR (qPCR) to assess mRNA expression of potential metastatic biomarkers. We found that expression of HPV16-E6, cytokeratin19 (CK19), and mucin1 (MUC1) is consistently upregulated in tumors and metastatic tissues, supporting a role for these genes in UCC progression. These putative biomarkers were able to predict the presence of histologically positive metastatic LNs with respective sensitivities and specificities of 82% and 99% (CK19), 76% and 95% (HPV16-E6), and 76% and 78% (MUC1). While the biomarkers failed to detect 1.7% to 2.2% of the histologically positive LNs when used individually, combining CK19 and HPV16-E6 enhanced sensitivity and specificity to 100% and 94%, respectively. To explore the sensitivity of qPCR-based detection of varying proportions of invading HPV16-positive UCC cells, we designed a LN metastasis model that achieved a fresh cell detection limit of 0.008% (1:12500 HPV16-positive to HPV16-negative cells), and a paraffin-embedded, formalin-fixed (PEFF) detection limit of 0.02% (1:5000 HPV16-positive to HPV16-negative cells), both of which are within the theoretical detection limit for micrometastasis. Thus, HPV E6/E7 oncogenes may be useful targets for the ultrasensitive detection of nodal involvements like micrometastases in fresh or archived tissue samples. Moreover, our results suggest that the biomarker combination of CK19/HPV-E6 could support a real-time intraoperative strategy for the detection of small, but potentially lethal, metastatic nodal involvements in fresh UCC tissues

The genetics of recurrent hydatidiform moles: new insights and lessons from a comprehensive analysis of 113 patients

Hydatidiform mole is an aberrant human pregnancy characterized by early embryonic arrest and excessive trophoblastic proliferation. Recurrent hydatidiform moles are defined by the occurrence of at least two hydatidiform moles in the same patient. Fifty to eighty percent of patients with recurrent hydatidiform moles have biallelic pathogenic variants in NLRP7 or KHDC3L. However, in the remaining patients, the genotypic types of the moles are unknown. We characterized 80 new hydatidiform mole tissues, 57 of which were from patients with no mutations in the known genes, and we reviewed the genotypes of a total of 123 molar tissues. We also reviewed mutation analysis in 113 patients with recurrent hydatidiform moles. While all hydatidiform moles from patients with biallelic NLRP7 or KHDC3L mutations are diploid biparental, we demonstrate that those from patients without mutations are highly heterogeneous and only a small minority of them are diploid biparental (8%). The other mechanisms that were found to recur in patients without mutations are diploid androgenetic monospermic (24%) and triploid dispermic (32%); the remaining hydatidiform moles were misdiagnosed as moles due to errors in the analyses and/or their unusual mechanisms. We compared three parameters of genetic susceptibility in patients with and without mutations and show that patients without mutations are mostly from non-familial cases, have fewer reproductive losses, and more live births. Our data demonstrate that patients with recurrent hydatidiform moles and no mutations in the known genes are, in general, different from those with mutations; they have a milder genetic susceptibility and/or a multifactorial etiology underlying their recurrent hydatidiform moles. Categorizing these patients according to the genotypic types of their recurrent hydatidiform moles may facilitate the identification of novel genes for this entity