No abstract

Purpose: Drug resistance is a major obstacle in cancer chemotherapy. Although the statistical probability of therapeutic success is known for larger patient groups from clinical therapy trials, it is difficult to predict the individual response of tumors. The concept of individualized therapy aims to determine in vitro the drug response of tumors beforehand to choose effective treatment options for each individual patient. Experimental Design: We analyzed the cross-resistance profiles of different tumor types (cancers of lung, breast, and colon, and leukemia) towards drugs from different classes (anthracyclines, antibiotics,Vinca alkaloids, epipodophyllotoxins, antimetabolites, and alkylating agents) by nucleotide incorporation and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. Hierarchical cluster analysis and COMPARE analyses were applied. Results:Tumors exert broad resistance profiles, e.g., tumors resistant to one drug tend to also be resistant to other drugs, whereas sensitive tumors reveal sensitivity towards many drugs. Interestingly, the broad spectrum resistance phenotype could reliably be predicted by doxorubicin alone. Expression of the ATP-binding cassette transporter P-glycoprotein (ABCB1, MDR1) and the proliferative activity of tumors were identified as underlying mechanisms of broad spectrum resistance. To find novel compounds with activity against drug-resistant tumors, a database with 2,420 natural products was screened for compounds acting independent of P-glycoprotein and the proliferative state of tumor cells. Conclusions: Tumors exert cross-resistance profiles much broader than the classical multidrug resistance phenotype. Broad spectrum resistance can be predicted by doxorubicin due to the multifactorial mode of action of this drug. Novel cytotoxic compounds from natural resources might be valuable tools for strategies to bypass broad spectrum resistance.

To optimize the extraction of gelatin from channel catfish (Ictalurus punctatus) skin, a 2-step response surface methodology involving a central composite design was adopted for the extraction process. After screening experiments, concentration of NaOH, alkaline pretreatment time, concentration of acetic acid, and extraction temperature were selected as the independent variables. In the 1st step of the optimization the dependent variables were protein yield (YP), gel strength (GS), and viscosity (V). Seven sets of optimized conditions were selected from the 1st step for the 2nd-step screen. Texture profile analysis and the 3 dependent variables from the 1st step were used as responses in the 2nd-step optimization. After the 2nd-step optimization, the most suitable conditions were 0.20 M NaOH pretreatment for 84 min, followed by a 0.115 M acetic acid extraction at 55 degrees C. The optimal values obtained from these conditions were YP = 19.2%, GS = 252 g, and V = 3.23 cP. The gelatin obtained also showed relatively good hardness, cohesiveness, springiness, and chewiness. The yield of protein and viscosity can be predicted by a quadratic and a linear model, respectively.

Elective neck dissection is indicated for cN0 patients with PNI-positive tumors for the efficacy of improving disease-specific survival as well as neck control. However, low-risk PNI-positive patients who undergo neck dissection do not need postoperative adjuvant therapy, because the residual risk from PNI is minimal.