Phase II trial of humanized anti-Lewis Y monoclonal antibody for advanced hormone receptor-positive breast cancer that progressed following endocrine therapy

OBJECTIVES: The Lewis-Y antigen is expressed in 44%-90% of breast cancers (BCs). The expression of the antigen in carcinoma tissue differs from that in normal tissues. This study aimed to evaluate the clinical benefit of the humanized anti-Lewis Y monoclonal antibody, hu3S193, in advanced hormone receptor-positive and Lewis Y-positive BC after administration of endocrine therapy (ET). METHODS: A single-arm phase II study was conducted in seven centers. Patients with advanced hormone receptor-positive BC who failed first-line ET were included. The inclusion criterion was the observation of tumoral expression of the Lewis Y antigen during immunohistochemistry. The treatment comprised hu3S193 antibody administration at weekly intravenous doses of 20 mg/m2 for 8-week cycles. The primary endpoint was the clinical benefit rate. ClinicalTrials.gov NCT01370239. RESULTS: The study stopped accrual following an unplanned interim analysis as the hu3S193 antibody lacked sufficient activity to justify continuation of the study. Twenty-two patients were enrolled, of whom 21 were included in the efficacy analysis. The clinical benefit rate was 19%, with four patients presenting with stable disease after 24 weeks. One patient with prolonged stable disease received medication for over 2 years. No partial or complete responses were observed. The median time to progression and overall survival was 5.4 and 37.5 months, respectively. CONCLUSIONS: The humanized anti-Lewis Y monoclonal antibody, hu3S193, exhibited insufficient activity in this cohort. However, the possibility of activity in a more strictly selected subgroup of patients with higher levels of Lewis Y tumoral expression cannot be overlooked

Dual-Layer Spectral CT as Innovative Imaging Guidance in Lung Biopsies: Could Color-Coded Z-Effective Images Allow More Diagnostic Samplings and Biomarkers Information?

The aim of the study was to try to obtain more information on diagnostic samplings and biomarkers using dual-layer spectral CT in lung biopsies. Lung biopsies were performed by merging images obtained with CBCT with those from spectral CT to use them as functional guidance, experimenting with double sampling to determine the difference between the area with a higher Z-effective number and that with a lower Z-effective number. Ten patients with large lung lesions on spectral CT were selected and underwent percutaneous transthoracic lung mass biopsy. Technical success was calculated. The percentage of neoplastic, inflammatory, fibrotic, necrotic cells, or non-neoplastic lung parenchyma was reported. The possibility of carrying out immunohistochemical or molecular biology investigations was analyzed. All lesions were results malignant in 10/10 samples in the Zmax areas; in the Zmin areas, malignant cells were found in 7/10 samples. Technical success was achieved in 100% of cases for Zmax sampling and in 70% for Zmin sampling (p-value: 0.2105). The biomolecular profile was detected in 9/10 (90%) cases in Zmax areas, while in 4/10 (40%) cases in Zmin areas (p-value: 0.0573). The advantage of Z-effective imaging would be to identify a region of the lesion that is highly vascularized and probably richer in neoplastic cells, thus decreasing the risk of obtaining a non-diagnostic biopsy sample

Reaction rate reconstruction from biomass concentration measurement in bioreactors using modified second-order sliding mode algorithms

This paper deals with the estimation of unknown signals in bioreactors using sliding observers. Particular attention is drawn to estimate the specific growth rate of microorganisms from measurement of biomass concentration. In a recent article, notions of high-order sliding modes have been used to derive a growth rate observer for batch processes. In this paper we generalize and refine these preliminary results. We develop a new observer with a different error structure to cope with other types of processes. Furthermore, we show that these observers are equivalent, under coordinate transformations and time scaling, to the classical super-twisting differentiator algorithm, thus inheriting all its distinctive features. The new observers’ family achieves convergence to timevarying unknown signals in finite time, and presents the best attainable estimation error order in the presence of noise. In addition, the observers are robust to modeling and parameter uncertainties since they are based on minimal assumptions on bioprocess dynamics. In addition, they have interesting applications in fault detection and monitoring. The observers performance in batch, fed-batch and continuous bioreactors is assessed by experimental data obtained from the fermentation of Saccharomyces Cerevisiae on glucose.This work was supported by the National University of La Plata (Project 2012-2015), the Agency for the Promotion of Science and Technology ANPCyT (PICT2007-00535) and the National Research Council CONICET (PIP112-200801-01052) of Argentina; the Technical University of Valencia (PAID-02-09), the CICYT (DPI2005-01180) and AECID (A/024186/09) of Spain; and by the project FEDER of the European Union.De Battista, H.; Picó Marco, JA.; Garelli, F.; Navarro Herrero, JL. (2012). Reaction rate reconstruction from biomass concentration measurement in bioreactors using modified second-order sliding mode algorithms. Bioprocess and Biosystems Engineering. 35(9):1-11. https://doi.org/10.1007/s00449-012-0752-yS111359Aborhey S, Williamson D (1978) State amd parameter estimation of microbial growth process. Automatica 14:493–498Bastin G, Dochain D (1986) On-line estimation of microbial specific growth rates. Automatica 22:705–709Bastin G, Dochain D (1990) On-line estimation and adaptive control of bioreactors. Elsevier, AmsterdamBejarano F, Fridman L (2009) Unbounded unknown inputs estimation based on high-order sliding mode differentiator. In: Proceedings of the 48th IEEE conference on decision and control, pp 8393–8398Corless M, Tu J (1998) State and input estimation for a class of uncertain systems. Automatica 34(6):757–764Dabros M, Schler M, Marison I (2010) Simple control of specific growth rate in biotechnological fed-batch processes based on enhanced online measurements of biomass. Bioprocess Biosyst Eng 33:1109–1118Davila A, Moreno J, Fridman L (2010) Variable gains super-twisting algorithm: a lyapunov based design. In: American control conference (ACC), 2010, pp 968–973Dávila J, Fridman L, Levant A (2005) Second-order sliding-mode observer for mechanical systems. IEEE Transact Automatic Control 50(11):1785–1789De Battista H, Picó J, Garelli F, Vignoni A (2011) Specific growth rate estimation in (fed-)batch bioreactors using second-order sliding observers. J Process Control 21:1049–1055Dochain D (2001) Bioprocess control. Wiley, HobokenDochain D (2003) State and parameter estimation in chemical and biochemical processes: a tutorial. J Process Control 13(8):801–818Edwards C, Spurgeon S, Patton R (2000) Sliding mode observers for fault detection and isolation. Automatica 36(2):541–553Evangelista C, Puleston P, Valenciaga F, Fridman L (2012) Lyapunov designed super-twisting sliding mode control for wind energy conversion optimization. Indus Electron IEEE Transact. doi: 10.1109/TIE.2012.2188256Farza M, Busawon K, Hammouri H (1998) Simple nonlinear observers for on-line estimation of kinetic rates in bioreactors. Automatica 34(3):301–318Fridman L, Davila J, Levant A (2008) High-order sliding modes observation. In: International workshop on variable structure systems, pp 203–208Fridman L, Levant A (2002) Sliding mode control in engineering, higher-order sliding modes. Marcel Dekker, Inc., New York, pp 53–101Fridman L, Shtessel Y, Edwards C, Yan X (2008) Higher-order sliding-mode observer for state estimation and input reconstruction in nonlinear systems. Int J Robust Nonlinear Control 18(3–4):399–412Gauthier J, Hammouri H, Othman S (1992) A simple observer for nonlinear systems: applications to bioreactors. IEEE Transact Automatic Control 37(6):875–880Gnoth S, Jenzsch M, Simutis R, Lubbert A (2008) Control of cultivation processes for recombinant protein production: a review. Bioprocess Biosyst Eng 31(1):21–39Hitzmann B, Broxtermann O, Cha Y, Sobieh O, Stärk E, Scheper T (2000) The control of glucose concentration during yeast fed-batch cultivation using a fast measurement complemented by an extended kalman filter. Bioprocess Eng 23(4):337–341Kiviharju K, Salonen K, Moilanen U, Eerikainen T (2008) Biomass measurement online: the performance of in situ measurements and software sensors. J Indus Microbiol Biotechnol 35(7):657–665Levant A (1998) Robust exact differentiation via sliding mode technique. Automatica 34(3):379–384Levant A (2003) Higher-order sliding modes, differentiation and output-feedback control. Int J Control 76(9/10):924–941Lubenova V, Rocha I, Ferreira E (2003) Estimation of multiple biomass growth rates and biomass concentration in a class of bioprocesses. Bioprocess Biosyst Eng 25:395–406Moreno J, Alvarez J, Rocha-Cozatl E, Diaz-Salgado J (2010) Super-twisting observer-based output feedback control of a class of continuous exothermic chemical reactors. In: Proceedings of the 9th IFAC international symposium on dynamics and control of process systems, pp 719–724. Leuven, BelgiumMoreno J, Osorio M (2008) A Lyapunov approach to second-order sliding mode controllers and observers. In: Proceedings of the 47th IEEE conference on decision and control. Cancún, México, pp 2856–2861Moreno J, Osorio M (2012) Strict Lyapunov functions for the super-twisting algorithm. IEEE Transact Automatic Control 57:1035–1040Navarro J, Picó J, Bruno J, Picó-Marco E, Vallés S (2001) On-line method and equipment for detecting, determining the evolution and quantifying a microbial biomass and other substances that absorb light along the spectrum during the development of biotechnological processes. Patent ES20010001757, EP20020751179Neeleman Boxtel (2001) Estimation of specific growth rate from cell density measurements. Bioprocess Biosyst Eng 24(3):179–185November E, van Impe J (2002) The tuning of a model-based estimator for the specific growth rate of Candidautilis. Bioprocess Biosyst Eng 25:1–12Park Y, Stein J (1988) Closed-loop, state and input observer for systems with unknown inputs. Int J Control 48(3):1121–1136Perrier M, de Azevedo SF, Ferreira E, Dochain D (2000) Tuning of observer-based estimators: theory and application to the on-line estimation of kinetic parameters. Control Eng Pract 8:377–388Picó J, De Battista H, Garelli F (2009) Smooth sliding-mode observers for specific growth rate and substrate from biomass measurement. J Process Control 19(8):1314–1323. Special section on hybrid systems: modeling, simulation and optimizationSchenk J, Balaszs K, Jungo C, Urfer J, Wegmann C, Zocchi A, Marison I, von Stockar U (2008) Influence of specific growth rate on specific productivity and glycosylation of a recombinant avidin produced by a Pichia pastoris Mut + strain. Biotecnol Bioeng 99(2):368–377Shtessel Y, Taleb M, Plestan F (2012) A novel adaptive-gain supertwisting sliding mode controller: Methodol Appl Automatica (in press)Soons Z, van Straten G, van der Pol L, van Boxtel A (2008) On line automatic tuning and control for fed-batch cultivation. Bioprocess Biosyst Eng 31(5):453–467Utkin V, Poznyak A, Ordaz P (2011) Adaptive super-twist control with minimal chattering effect. In: Proceedings of 50th IEEE conference on decision and control and European control conference. Orlando, pp 7009–7014Veloso A, Rocha I, Ferreira E (2009) Monitoring of fed-batch E. coli fermentations with software sensors. Bioprocess Biosyst Eng 32(3):381–388Venkateswarlu C (2004) Advances in monitoring and state estimation of bioreactors. J Sci Indus Res 63:491–498Zamboni N, Fendt S, Rühl M, Sauer U (2009) 13c-based metabolic flux analysis. Nat Protocols 4:878–892Zorzetto LFM, Wilson JA (1996) Monitoring bioprocesses using hybrid models and an extended kalman filter. Comput Chem Eng 20(Suppl 1):S689–S69

PF-05280014 (a trastuzumab biosimilar) plus paclitaxel compared with reference trastuzumab plus paclitaxel for HER2-positive metastatic breast cancer: a randomised, double-blind study

BACKGROUND: This randomised, double-blind study compared PF-05280014 (a trastuzumab biosimilar) with reference trastuzumab (Herceptin®) sourced from the European Union (trastuzumab-EU), when each was given with paclitaxel as first-line treatment for HER2-positive metastatic breast cancer. METHODS: Between 4 April 2014 and 22 January 2016, 707 participants were randomised 1:1 to receive intravenous PF-05280014 plus paclitaxel (PF-05280014 group; n = 352) or trastuzumab-EU plus paclitaxel (trastuzumab-EU group; n = 355). PF-05280014 or trastuzumab-EU was administered weekly (first dose 4 mg/kg, subsequent doses 2 mg/kg), with the option to change to a 3-weekly regimen (6 mg/kg) from Week 33. Treatment with PF-05280014 or trastuzumab-EU could continue until disease progression. Paclitaxel (starting dose 80 mg/m2 ) was administered on Days 1, 8 and 15 of 28-day cycles for at least six cycles or until maximal benefit of response. The primary endpoint was objective response rate (ORR), evaluating responses achieved by Week 25 and confirmed by Week 33, based on blinded central radiology review. RESULTS: The risk ratio for ORR was 0.940 (95% CI: 0.842–1.049). The 95% CI fell within the pre-specified equivalence margin of 0.80–1.25. ORR was 62.5% (95% CI: 57.2–67.6%) in the PF-05280014 group and 66.5% (95% CI: 61.3–71.4%) in the trastuzumab-EU group. As of data cut-off on 11 January 2017 (using data up to 378 days post-randomisation), there were no notable differences between groups in progression-free survival (median: 12.16 months in the PF-05280014 group vs. 12.06 months in the trastuzumab-EU group; 1-year rate: 54% vs. 51%) or overall survival (median: not reached in either group; 1-year rate: 89.31% vs. 87.36%). Safety outcomes and immunogenicity were similar between the treatment groups. CONCLUSION: When given as first-line treatment for HER2-positive metastatic breast cancer, PF-05280014 plus paclitaxel demonstrated equivalence to trastuzumab-EU plus paclitaxel in terms of ORR. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT0198967

Immunotherapy for gastric premalignant lesions and cancer.

Chronic atrophic gastritis, a precancerous change for gastric cancer, shows a loss of appropriate glands, Helicobacter pylori infection and autoimmune gastritis being the two main etiologic factors. While H. pylori eradication is the mandatory treatment for the former, no etiologic treatment is available for the latter, in which a Th1-type response, modulated by Tregs and Th17 cells, is involved. H. pylori-related atrophic gastritis is a risk factor for gastric adenocarcinoma, while autoimmune atrophic gastritis is also linked to a substantial risk of gastric type I carcinoid, related to the chronic stimulus exerted by hypergastrinemia on enterochromaffin-like cells. Several studies have been published on gastric cancer treatment through an active specific immunotherapy, aimed at improving the immunoregulatory response and increasing the circulating tumor-specific T cells. No study on immunotherapy of carcinoids is available but, in our experience, the administration of an antigastrin 17 vaccine induced carcinoid regression in two out of three patients treated