Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review

Clinicians can use biomarkers to guide therapeutic decisions in estrogen receptor positive (ER+) breast cancer. One such biomarker is cellular proliferation as evaluated by Ki-67. This biomarker has been extensively studied and is easily assayed by histopathologists but it is not currently accepted as a standard. This review focuses on its prognostic and predictive value, and on methodological considerations for its measurement and the cut-points used for treatment decision. Data describing study design, patients’ characteristics, methods used and results were extracted from papers published between January 1990 and July 2010. In addition, the studies were assessed using the REMARK tool. Ki-67 is an independent prognostic factor for disease-free survival (HR 1.05–1.72) in multivariate analyses studies using samples from randomized clinical trials with secondary central analysis of the biomarker. The level of evidence (LOE) was judged to be I-B with the recently revised definition of Simon. However, standardization of the techniques and scoring methods are needed for the integration of this biomarker in everyday practice. Ki-67 was not found to be predictive for long-term follow-up after chemotherapy. Nevertheless, high KI-67 was found to be associated with immediate pathological complete response in the neoadjuvant setting, with an LOE of II-B. The REMARK score improved over time (with a range of 6–13/20 vs. 10–18/20, before and after 2005, respectively). KI-67 could be considered as a prognostic biomarker for therapeutic decision. It is assessed with a simple assay that could be standardized. However, international guidelines are needed for routine clinical use

Cancers épithéliaux de l' ovaire (analyse de la prise en charge et des résultats à l' échelle de la région de Basse-Normandie sur une période de 17 ans)

CAEN-BU Médecine pharmacie (141182102) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Prognostic significance of tumour vascularisation on survival of patients with advanced ovarian carcinoma

Objective. The prognostic significance of microvessel density in ovarian cancer is still a matter of debate. Classically, the degree of vascularisation is assessed in areas of high vascular density (hot spots), considered as regions of increased probability of metastasis. Since ovarian tumours have a particular progression and dissemination behaviour, vascularisation outside hot spots may also contribute to their evolution. Methods. In the present study, the degree of tumour vascularisation was estimated both in whole histogical sections and in hot spots, in 235 patients with ovarian carcinoma, using fully automatic image analysis methods. Six parameters were estimated: mean microvessel density (MVD) and mean microvessel surface fraction (MSP) on the whole section, mean and maximum values of MVD and MSP inside hot spots (MVDHS1, MSPHS1 and MVDHS2, MSPHS2). Relationships between vascular parameters and clinicopathologic features were analysed. Results. In stage III-IV patients multivariate analysis showed that stage IV disease (hazards ratio (HR)=1.72, p=0.001), post-surgical residual disease 1cm (HR=2.86, p<0.001), upper MVD tercile (HR=1.45, p<0.022) and medial MVDHS1 tercile (HR=1.36, p=0.060) retained an independent prognostic value upon overall survival. Conclusion. Our results suggest that quantification of blood vessels, both on the whole histological section and in hot spots might be helpful in evaluating prognosis in advanced ovarian carcinomas

Genetic profiles of cervical tumors by high‐throughput sequencing for personalized medical care

International audienceCancer treatment is facing major evolution since the advent of targeted therapies. Building genetic profiles could predict sensitivity or resistance to these therapies and highlight disease-specific abnormalities, supporting personalized patient care. In the context of biomedical research and clinical diagnosis, our laboratory has developed an oncogenic panel comprised of 226 genes and a dedicated bioinformatic pipeline to explore somatic mutations in cervical carcinomas, using high-throughput sequencing. Twenty-nine tumors were sequenced for exons within 226 genes. The automated pipeline used includes a database and a filtration system dedicated to identifying mutations of interest and excluding false positive and germline mutations. One-hundred and seventy-six total mutational events were found among the 29 tumors. Our cervical tumor mutational landscape shows that most mutations are found in PIK3CA (E545K, E542K) and KRAS (G12D, G13D) and others in FBXW7 (R465C, R505G, R479Q). Mutations have also been found in ALK (V1149L, A1266T) and EGFR (T259M). These results showed that 48% of patients display at least one deleterious mutation in genes that have been already targeted by the Food and Drug Administration approved therapies. Considering deleterious mutations, 59% of patients could be eligible for clinical trials. Sequencing hundreds of genes in a clinical context has become feasible, in terms of time and cost. In the near future, such an analysis could be a part of a battery of examinations along the diagnosis and treatment of cancer, helping to detect sensitivity or resistance to targeted therapies and allow advancements towards personalized oncology

Genetic profiles of cervical tumors by high-throughput sequencing for personalized medical care

International audienceCancer treatment is facing major evolution since the advent of targeted therapies. Building genetic profiles could predict sensitivity or resistance to these therapies and highlight disease-specific abnormalities, supporting personalized patient care. In the context of biomedical research and clinical diagnosis, our laboratory has developed an oncogenic panel comprised of 226 genes and a dedicated bioinformatic pipeline to explore somatic mutations in cervical carcinomas, using high-throughput sequencing. Twenty-nine tumors were sequenced for exons within 226 genes. The automated pipeline used includes a database and a filtration system dedicated to identifying mutations of interest and excluding false positive and germline mutations. One-hundred and seventy-six total mutational events were found among the 29 tumors. Our cervical tumor mutational landscape shows that most mutations are found in PIK3CA (E545K, E542K) and KRAS (G12D, G13D) and others in FBXW7 (R465C, R505G, R479Q). Mutations have also been found in ALK (V1149L, A1266T) and EGFR (T259M). These results showed that 48% of patients display at least one deleterious mutation in genes that have been already targeted by the Food and Drug Administration approved therapies. Considering deleterious mutations, 59% of patients could be eligible for clinical trials. Sequencing hundreds of genes in a clinical context has become feasible, in terms of time and cost. In the near future, such an analysis could be a part of a battery of examinations along the diagnosis and treatment of cancer, helping to detect sensitivity or resistance to targeted therapies and allow advancements towards personalized oncology