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Chou T.-C.,Sloan Kettering Cancer Center
Cancer Research | Year: 2010

This brief perspective article focuses on the most common errors and pitfalls, as well as the do's and don'ts in drug combination studies, in terms of experimental design, data acquisition, data interpretation, and computerized simulation. The Chou-Talalay method for drug combination is based on the median-effect equation, derived from the mass-action law principle, which is the unified theory that provides the common link between single entity and multiple entities, and first order and higher order dynamics. This general equation encompasses the Michaelis-Menten, Hill, Henderson-Hasselbalch, and Scatchard equations in biochemistry and biophysics. The resulting combination index (CI) theorem of Chou-Talalay offers quantitative definition for additive effect (CI = 1), synergism (CI < 1), and antagonism (CI > 1) in drug combinations. This theory also provides algorithms for automated computer simulation for synergism and/or antagonism at any effect and dose level, as shown in the CI plot and isobologram, respectively. ©2010 AACR.


Dickson M.A.,Sloan Kettering Cancer Center
Clinical Cancer Research | Year: 2014

Unrestrained growth is the hallmark of cancer, and disrupted cell-cycle regulation is, therefore, common. CDK4 is the key regulator of the G 1-S transition. In complex with cyclin D, CDK4 phosphorylates retinoblastoma protein (Rb) and drives cell-cycle progression, a process inhibited by pl6. The pl6-CDK4-cyclin D-Rb is aberrant in the majority of cancers and is, thus, a logical target for anticancer therapy. Previous attempts to block CDK4 with nonselective cyclin-dependent kinase (CDK) inhibitors led to toxicity and little efficacy. However, the recent development of selective CDK4 inhibitors launched the first successful efforts to target the pathway for cancer therapy. Three oral selective CDK4 inhibitors have entered clinical trials: palbociclib (PD0332991), LEEOll, and LY2835219. CDK4 inhibitors have in vitro activity against a broad range of cancers and in patients have shown antitumor activity in breast cancer, lymphoma, sarcoma, and other tumors. Major efforts are under way to develop biomarkers of response, understand potential mechanisms of resistance, and develop rational combinations of CDK4 inhibitors with chemotherapy and other targeted drugs. © 2014 American Association for Cancer Research.


Vickers A.J.,Sloan Kettering Cancer Center
CA Cancer Journal for Clinicians | Year: 2011

Prediction is ubiquitous across the spectrum of cancer care from screening to hospice. Indeed, oncology is often primarily a prediction problem; many of the early stage cancers cause no symptoms, and treatment is recommended because of a prediction that tumor progression would ultimately threaten a patient's quality of life or survival. Recent years have seen attempts to formalize risk prediction in cancer care. In place of qualitative and implicit prediction algorithms, such as cancer stage, researchers have developed statistical prediction tools that provide a quantitative estimate of the probability of a specific event for an individual patient. Prediction models generally have greater accuracy than reliance on stage or risk groupings, can incorporate novel predictors such as genomic data, and can be used more rationally to make treatment decisions. Several prediction models are now widely used in clinical practice, including the Gail model for breast cancer incidence or the Adjuvant! Online prediction model for breast cancer recurrence. Given the burgeoning complexity of diagnostic and prognostic information, there is simply no realistic alternative to incorporating multiple variables into a single prediction model. As such, the question should not be whether but how prediction models should be used to aid decision-making. Key issues will be integration of models into the electronic health record and more careful evaluation of models, particularly with respect to their effects on clinical outcomes. © 2011 American Cancer Society, Inc.


Rudensky A.Y.,Sloan Kettering Cancer Center
Immunological Reviews | Year: 2011

Regulatory T (Treg) cells play central role in regulation of immune responses to self-antigens, allergens, and commensal microbiota as well as immune responses to infectious agents and tumors. Transcriptional factor Foxp3 serves as a lineage specification factor of Treg cells. Paucity of Treg cells due to loss-of-function mutations of the Foxp3 gene is responsible for highly aggressive, fatal, systemic immune-mediated inflammatory lesions in mice and humans. Recent studies of Foxp3 expression and function provided critical novel insights into biology of Treg cells and into cellular mechanisms of the immune homeostasis. © 2011 John Wiley & Sons A/S.


Maluccio M.,Indiana University | Covey A.,Sloan Kettering Cancer Center
CA Cancer Journal for Clinicians | Year: 2012

Hepatocellular carcinoma (HCC) is one of the few cancers in which a continued increase in incidence has been observed over several years. As such, there has been a focus on safe and accurate diagnosis and the development of treatment algorithms that take into consideration the unique complexities of this patient population. In the past decade, there have been improvements in nonsurgical treatment platforms and better standardization with respect to the diagnosis and patient eligibility for liver transplant. How to navigate patients through the challenges of treatment is difficult and depends on several factors: 1) patient-related variables such as comorbid conditions that influence treatment eligibility; 2) liver-related variables such as Child-Pugh score; and 3) tumor-related variables such as size, number, pattern of spread within the liver, and vascular involvement. The objectives of this review are to put into perspective the current treatment options for patients with HCC, the unique advantages and disadvantages of each treatment approach, and the evidence that supports the introduction of sorafenib into the multidisciplinary management of HCC. CA Cancer J Clin 2012;. © 2012 American Cancer Society. Copyright © 2012 American Cancer Society, Inc.

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