Memorial Sloan Kettering Cancer Center

About: Memorial Sloan Kettering Cancer Center is a healthcare organization based out in New York, New York, United States. It is known for research contribution in the topics: Cancer & Population. The organization has 30293 authors who have published 65381 publications receiving 4462534 citations. The organization is also known as: MSKCC & New York Cancer Hospital.

Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup.

Abstract: Background The current practice of removing adenomatous polyps of the colon and rectum is based on the belief that this will prevent colorectal cancer. To address the hypothesis that colonoscopic polypectomy reduces the incidence of colorectal cancer, we analyzed the results of the National Polyp Study with reference to other published results. Methods The study cohort consisted of 1418 patients who had a complete colonoscopy during which one or more adenomas of the colon or rectum were removed. The patients subsequently underwent periodic colonoscopy during an average follow-up of 5.9 years, and the incidence of colorectal cancer was ascertained. The incidence rate of colorectal cancer was compared with that in three reference groups, including two cohorts in which colonic polyps were not removed and one general-population registry, after adjustment for sex, age, and polyp size. Results Ninety-seven percent of the patients were followed clinically for a total of 8401 person-years, and 80 percent returned...

Drug Combination Studies and Their Synergy Quantification Using the Chou-Talalay Method

Abstract: 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) 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.

Theoretical Basis, Experimental Design, and Computerized Simulation of Synergism and Antagonism in Drug Combination Studies

Abstract: The median-effect equation derived from the mass-action law principle at equilibrium-steady state via mathematical induction and deduction for different reaction sequences and mechanisms and different types of inhibition has been shown to be the unified theory for the Michaelis-Menten equation, Hill equation, Henderson-Hasselbalch equation, and Scatchard equation. It is shown that dose and effect are interchangeable via defined parameters. This general equation for the single drug effect has been extended to the multiple drug effect equation for n drugs. These equations provide the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI 1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to allow automated simulation of synergism and antagonism at all dose or effect levels. It displays the dose-effect curve, median-effect plot, combination index plot, isobologram, dose-reduction index plot, and polygonogram for in vitro or in vivo studies. This theoretical development, experimental design, and computerized data analysis have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical sciences. In this review, selected examples of applications are given, and step-by-step examples of experimental designs and real data analysis are also illustrated. The merging of the mass-action law principle with mathematical induction-deduction has been proven to be a unique and effective scientific method for general theory development. The median-effect principle and its mass-action law based computer software are gaining increased applications in biomedical sciences, from how to effectively evaluate a single compound or entity to how to beneficially use multiple drugs or modalities in combination therapies.

Tolerance of normal tissue to therapeutic irradiation.

Abstract: The importance of knowledge on tolerance of normal tissue organs to irradiation by radiation oncologists cannot be overemphasized. Unfortunately, current knowledge is less than adequate. With the increasing use of 3-D treatment planning and dose delivery, this issue, particularly volumetric information, will become even more critical. As a part of the NCI contract N01 CM-47316, a task force, chaired by the primary author, was formed and an extensive literature search was carried out to address this issue. In this issue. In this manuscript we present the updated information on tolerance of normal tissues of concern in the protocols of this contract, based on available data, with a special emphasis on partial volume effects. Due to a lack of precise and comprehensive data base, opinions and experience of the clinicians from four universities involved in the contract have also been contributory. Obviously, this is not and cannot be a comprehensive work, which is beyond the scope of this contract.

Comprehensive molecular profiling of lung adenocarcinoma: The cancer genome atlas research network

Abstract: Adenocarcinoma of the lung is the leading cause of cancer death worldwide. Here we report molecular profiling of 230 resected lung adenocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses. High rates of somatic mutation were seen (mean 8.9 mutations per megabase). Eighteen genes were statistically significantly mutated, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification. EGFR mutations were more frequent in female patients, whereas mutations in RBM10 were more common in males. Aberrations in NF1, MET, ERBB2 and RIT1 occurred in 13% of cases and were enriched in samples otherwise lacking an activated oncogene, suggesting a driver role for these events in certain tumours. DNA and mRNA sequence from the same tumour highlighted splicing alterations driven by somatic genomic changes, including exon 14 skipping in MET mRNA in 4% of cases. MAPK and PI(3)K pathway activity, when measured at the protein level, was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation. These data establish a foundation for classification and further investigations of lung adenocarcinoma molecular pathogenesis.