Serial analysis of circulating tumor cells in metastatic breast cancer receiving first-line chemotherapy

Background: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2,202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs (bCTC), combined CTC status at baseline to the end of cycle 1 (cCTC), and tCTC. Akaike Information Criterion (AIC) was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (tCTCneg, 56.9% ), low (tCTClo, 23.7%), intermediate (tCTCmid, 14.5%), or high (tCTChi, 4.9%). Patients with tCTClo, tCTCmid and tCTChi patterns had statistically significant inferior PFS and OS compared to those with tCTCneg (P<.001). AIC indicated that the tCTC model best predicted PFS and OS when compared to bCTC and cCTC models. Validation studies in an independent cohort of 1,856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified four novel prognostic groups in MBC based on similarities in CTC trajectory patterns during chemotherapy. Prognostic groups included patients with very poor outcome (tCTCmid+tCTChi, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be utilized for fine-tuning of CTC-based risk-stratification strategies to guide future prospective clinical trials in MBC

Deciphering the stem cell machinery as a basis for understanding the molecular mechanism underlying reprogramming

Stem cells provide fascinating prospects for biomedical applications by combining the ability to renew themselves and to differentiate into specialized cell types. Since the first isolation of embryonic stem (ES) cells about 30 years ago, there has been a series of groundbreaking discoveries that have the potential to revolutionize modern life science. For a long time, embryos or germ cell-derived cells were thought to be the only source of pluripotency—a dogma that has been challenged during the last decade. Several findings revealed that cell differentiation from (stem) cells to mature cells is not in fact an irreversible process. The molecular mechanism underlying cellular reprogramming is poorly understood thus far. Identifying how pluripotency maintenance takes place in ES cells can help us to understand how pluripotency induction is regulated. Here, we review recent advances in the field of stem cell regulation focusing on key transcription factors and their functional interplay with non-coding RNAs

Serial Analysis of Circulating Tumor Cells in Metastatic Breast Cancer Receiving First-Line Chemotherapy

32siBackground: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. Methods: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS. Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9%), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P <. 001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. Conclusions: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC.reservedmixedMagbanua M.J.M.; Hendrix L.H.; Hyslop T.; Barry W.T.; Winer E.P.; Hudis C.; Toppmeyer D.; Carey L.A.; Partridge A.H.; Pierga J.-Y.; Fehm T.; Vidal-Martinez J.; Mavroudis D.; Garcia-Saenz J.A.; Stebbing J.; Gazzaniga P.; Manso L.; Zamarchi R.; Antelo M.L.; Mattos-Arruda L.D.; Generali D.; Caldas C.; Munzone E.; Dirix L.; Delson A.L.; Burstein H.J.; Qadir M.; Ma C.; Scott J.H.; Bidard F.-C.; Park J.W.; Rugo H.S.Magbanua, M. J. M.; Hendrix, L. H.; Hyslop, T.; Barry, W. T.; Winer, E. P.; Hudis, C.; Toppmeyer, D.; Carey, L. A.; Partridge, A. H.; Pierga, J. -Y.; Fehm, T.; Vidal-Martinez, J.; Mavroudis, D.; Garcia-Saenz, J. A.; Stebbing, J.; Gazzaniga, P.; Manso, L.; Zamarchi, R.; Antelo, M. L.; Mattos-Arruda, L. D.; Generali, D.; Caldas, C.; Munzone, E.; Dirix, L.; Delson, A. L.; Burstein, H. J.; Qadir, M.; Ma, C.; Scott, J. H.; Bidard, F. -C.; Park, J. W.; Rugo, H. S

Diet and feeding daily rhythm of Pimelodella lateristriga (Osteichthyes, Siluriformes) in a coastal stream from Serra do Mar - RJ

The present study was carried out in Mato Grosso fluvial system, a costal drainage from Serra do Mar. We analysed the diet and the feeding daily rhythm of Pimelodella lateristriga from samples carried out during 24 hours over a 4 hour fishing interval, in June, July and September, 2006 as well as in January and February, 2007. Diet was described from the Feeding Index (IAi) and feeding daily rhythm was verified through the Gut Fullness Index (GFI). Pimelodella lateristriga diet was composed of 37 items, being aquatic insects the most important ones. IAi analysis revealed that Diptera, Trichoptera and Ephemeroptera amounted to 90% of the diet. Autochthonous invertebrates were the most important consumed items. Pimelodella lateristriga concentrated its feeding activities in the nocturnal period (10:00 PM to 2:00 AM) with marked significant differences (F = 16.11; gl = 5; p < 0.05) between each diurnal and nocturnal periods. Between 6:00 AM and 6:00 PM, foraging activity was gradually reduced. We concluded that P. lateristriga has an insectivorous diet and a nocturnal feeding habit with greater activity between 10:00 PM to 2:00 AM