H. Crouet

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.

Abstract The purpose of this prospective multicenter study was to assess one‐step nucleic acid amplification (OSNA) for intraoperative sentinel lymph node (SLN) metastasis detection in breast cancer patients, using final histology as the reference standard. OSNA results were also compared to intraoperative histology SLN evaluation and to standard clinicopathological risk markers. For this study, fresh SLNs were cut in four blocks, and alternate blocks were used for OSNA and histology. CK19 mRNA copy number was categorized as strongly positive, positive or negative. Positive histology was defined as presence of macrometastasis or micrometastasis. When discrepancies occurred, the entire SLNs were subjected to histological studies and the node lysates to additional molecular studies. Five hundred three SLN samples from 233 patients were studied. Mean time to evaluate two SLNs was 40 min. Sensitivity per patient was 91.4% (95% CI, 76.9–98.2%), specificity 93.3% (95% CI, 88.6–96.6%), positive likelihood ratio 13.7 and negative likelihood ratio 0.1. Sensitivity was 63.6% for frozen sections and 47.1% for touch imprint cytology. Both methods were 100% specific. Positive histology and positive OSNA were significantly associated with highest clinical stage, N1 status and vascular invasion; and OSNA results correlated with HER2/neu status and benefited patients with negative histology. These findings show that OSNA assay can allow detection of SLN metastasis in breast cancer patients intraoperatively with a good sensitivity, thus minimizing the need for second surgeries for axillary lymph node detection.

PURPOSE: Point spread function (PSF) reconstruction improves spatial resolution throughout the entire field of view of a PET system and can detect smaller metastatic deposits than conventional algorithms such as OSEM. We assessed the impact of PSF reconstruction on quantitative values and diagnostic accuracy for axillary staging of breast cancer patients, compared with an OSEM reconstruction, with emphasis on the size of nodal metastases. METHODS: This was a prospective study in a single referral centre in which 50 patients underwent an (18)F-FDG PET examination before axillary lymph node dissection. PET data were reconstructed with an OSEM algorithm and PSF reconstruction, analysed blindly and validated by a pathologist who measured the largest nodal metastasis per axilla. This size was used to evaluate PET diagnostic performance. RESULTS: On pathology, 34 patients (68%) had nodal involvement. Overall, the median size of the largest nodal metastasis per axilla was 7 mm (range 0.5 - 40 mm). PSF reconstruction detected more involved nodes than OSEM reconstruction (p = 0.003). The mean PSF to OSEM SUVmax ratio was 1.66 (95 % CI 1.01 - 2.32). The sensitivities of PSF and OSEM reconstructions were, respectively, 96% and 92% in patients with a largest nodal metastasis of >7 mm, 60% and 40% in patients with a largest nodal metastasis of ≤7 mm, and 92% and 69% in patients with a primary tumour ≤30 mm. Biggerstaff graphical comparison showed that globally PSF reconstruction was superior to OSEM reconstruction. The median sizes of the largest nodal metastasis in patients with nodal involvement not detected by either PSF or OSEM reconstruction, detected by PSF but not by OSEM reconstruction and detected by both reconstructions were 3, 6 and 16 mm (p = 0.0064) respectively. In patients with nodal involvement detected by PSF reconstruction but not by OSEM reconstruction, the smallest detectable metastasis was 1.8 mm. CONCLUSION: As a result of better activity recovery, PET with PSF reconstruction performed better than PET with OSEM reconstruction in detecting nodal metastases ≤7 mm. However, its sensitivity is still insufficient for it to replace surgical approaches for axillary staging. PET with PSF reconstruction could be used to perform sentinel node biopsy more safely in patients with a primary tumour ≤30 mm and with unremarkable PET results in the axilla.

Cancer 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.