Biological properties and development of hypoxia in a breast cancer 3D model generated by hanging drop technique

Author(s):  
Madalina Andreea Badea ◽  
Mihaela Balas ◽  
Anca Dinischiotu
1999 ◽  
Vol 55 (11) ◽  
pp. 1903-1905 ◽  
Author(s):  
John N. Lisgarten ◽  
James E. Pitts ◽  
Rex A. Palmer ◽  
Colin D. Reynolds ◽  
Minh Hoa Dao-Thi ◽  
...  

Crystals of Helix pomatia agglutinin (HPA) have been grown by the hanging-drop technique using polyethylene glycol as the precipitant at 293 K. Over a period of one to two weeks the crystals grew to maximum dimensions of 0.10 × 0.05 × 0.02 mm. The crystals belong to space group P6322, with unit-cell dimensions a = b = 63.3, c = 105.2 Å and Z = 12 identical monomers of Mr = 13 kDa, aggregating into two 78 kDa hexameric protein molecules per unit cell, each with symmetry 32 (D 3). The diffraction pattern extends to 3.6 Å at 293 K.


2017 ◽  
Vol 42 (2) ◽  
pp. 220-231 ◽  
Author(s):  
Shaohui Wang ◽  
Ximing Wang ◽  
Jasmine Boone ◽  
Jin Wie ◽  
Kay-Pong Yip ◽  
...  

2020 ◽  
pp. 1-8
Author(s):  
Katarzyna Rygiel

Precision medicine considers specific biological characteristics of each individual patient to tailor diagnostic and therapeutic strategies to a given patient. This approach is particularly important for a growing number of patients with malignancies. Currently, some unique biological properties in the terms of different “omics” platforms (e.g., genomics, proteomics, transcriptomics, metabolomics, epigenomics, and pharmacogenomics) have been introduced to precision medicine. In addition, specific personal characteristics of the patients have been described as personomics. It should be highlighted that personomics include an individual patient’s personality type, set of personal values, priorities, preferences, health-related beliefs, goals, economical status, and different life circumstances, which influence when and how a certain disease (e.g., breast cancer (BC)) can be manifested in a given person. As a consequence, personomics are considered to be an innovative clinical tool that is crucial for making a connection between the existing and emerging, more individualized model of medical care. This is particularly important among patients suffering from the most difficult to treat cancers (e.g., BC subtypes, such as the triple-negative BC (TNBC), and the human epidermal growth factor receptor 2 (HER2)-positive BC). This mini-review addresses some research concepts in personalized medicine, focusing on personomics, which apply individualized data of the patient to the therapeutic plan. In this light, personomics can facilitate the transition from standard medical treatment to personalized medical management of individual women with BC.


2016 ◽  
Author(s):  
Amanda M. Clark ◽  
Sarah E. Wheeler ◽  
Carissa L. Young ◽  
Venkateswaran C. Pillai ◽  
Donna B. Stolz ◽  
...  

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Toru Hanamura ◽  
Koichi Ohno ◽  
Shinya Hokibara ◽  
Hideki Murasawa ◽  
Toshitsugu Nakamura ◽  
...  

Abstract Background Recent preclinical data suggest that androgen receptor (AR) signaling plays a significant role in subsets of breast cancer. Clinical trials testing AR-targeting therapies in breast cancer have been conducted. Assessment of AR-signal in breast cancer tissue maybe useful for treatment selections. Prostate specific antigen (PSA) is the product of an androgen-responsive gene. Serum PSA (sPSA) can be detected in women by a highly sensitive assay although the concentration is much lower than that observed in males. We investigated if sPSA reflects tumor biology, including AR signaling in breast cancer patients. Methods In this study, 132 healthy controls and 144 breast cancer patients were enrolled. sPSA was evaluated by the chemiluminescent enzyme immunoassay (CLEIA) method. Correlations between sPSA and the various clinicopathological factors were analyzed. Results In post-menopausal state, sPSA detection rate was significantly higher in breast cancer patients compared with controls (27.4% vs 11.3%: p = 0.0090), but not in the whole cohort (29.2% vs 25.8%: p = 0.5265) or pre-menopausal subgroup (37.0% vs 42.6%: p = 0.6231). In post-menopausal breast cancer cases, higher sPSA value was associated with clinic-pathological factors including the expression of AR protein in primary legion. In a correlation analysis of quantitative data limited to post-menopausal metastatic breast cancer (MBC), sPSA was positively, albeit weakly correlated with clinic-pathological features including serum testosterone levels and AR positivity. Conclusions Our data suggest that sPSA may reflect tumor biological properties including AR activity in post-menopausal breast cancer.


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