Leader in war on cancer looks ahead: talking with Vincent T. DeVita, Jr, MD

Vt, DeVita

doi:10.1001/jama.273.7.525

Cited by 10 publications

(14 citation statements)

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“…There is therefore a major incentive to try to identify genes that could be reliable early diagnostic and prognostic markers and therapeutic targets. Recent studies have identified a number of genes that discriminate prostate tumor from nontumor samples (2)(3)(4)(5). However, prostate tissue contains several cell types such as glandular epithelial cells, stromal cells, and cells of other supporting structures interspersed with neoplastic and hypertrophic epithelial cells.…”

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confidence: 99%

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

Stuart

Wachsman

Berry

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

182

173

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Prostate tumors are complex entities composed of malignant cells mixed and interacting with nonmalignant cells. However, molecular analyses by standard gene expression profiling are limited because spatial information and nontumor cell types are lost in sample preparation. We scored 88 prostate specimens for relative content of tumor, benign hyperplastic epithelium, stroma, and dilated cystic glands. The proportions of these cell types were then linked in silico to gene expression levels determined by microarray analysis, revealing unique cell-specific profiles. Gene expression differences for malignant and nonmalignant epithelial cells (tumor versus benign hyperplastic epithelium) could be identified without being confounded by contributions from stroma that dominate many samples or sacrificing possible paracrine influences. Cellspecific expression of selected genes was validated by immunohistochemistry and quantitative PCR. The results provide patterns of gene expression for these three lineages with relevance to pathogenetic, diagnostic, and therapeutic considerations.microarray ͉ expression profiles ͉ linear regression ͉ biomarkers ͉ paracine

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confidence: 99%

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

Stuart

Wachsman

Berry

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

182

173

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“…Examples of such models include optimal-control-theory models [3], game-theoretical models [4], as well as models of drug resistance and/or chemotherapy scheduling, which can be either stochastic [5][6][7][8] or deterministic [9][10][11]. 15 In current clinical practice, chemotherapy is usually given at "maximum tolerated dose" for the "minimum possible duration", which is usually 3-6 months, in the belief that this will have the most benefit to the patient in the least possible time [13]. This is based on modeling tumor cells as continuously dividing at some fixed deterministic rate [14].…”

Section: Introductionmentioning

confidence: 99%

A Quasi Birth-and-Death Model For Tumor Recurrence

Santana

Ganesan

Bhanot

2019

Preprint

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A major cause of chemoresistance and recurrence in tumors is the presence of dormant tumor foci that survive chemotherapy and can eventually transition to active growth to regenerate the cancer. In this paper, we propose a Quasi Birth-and-Death (QBD) model for the dynamics of tumor growth and recurrence/remission of the cancer. Starting from a discrete-state master equation that describes the timedependent transition probabilities between states with different numbers of dormant and active tumor foci, we develop a framework based on a continuum-limit approach to determine the time-dependent probability that an undetectable residual tumor will become large enough to be detectable. We derive an exact formula for the probability of recurrence at large times and show that it displays a phase transition as a function of the ratio of the death rate µ A of an active tumor focus to its doubling rate λ. We also derive forward and backward Kolmogorov equations for the transition probability density in the continuum limit and, using a first-passage time formalism, we obtain a drift-diffusion equation for the mean recurrence time and solve it analytically to leading order for a large detectable tumor size N . We show that simulations of the discretestate model agree with the analytical results, except for O(1/N ) corrections. Finally, we describe a scheme to fit the model to recurrence-free survival (Kaplan-Meier) curves from clinical cancer data, using ovarian cancer data as an example. Our model has potential applications in predicting how changing chemotherapy schedules may affect disease recurrence rates, especially in cancer types for which no targeted therapy is available.model is formulated in terms of a continuous-time master equation in the discrete state space that represents the numbers of dormant and active tumor foci. In Section 4, it is shown that an expansion of the master equation for a large detectable-tumor size N leads to a simplified approach by mapping the original discretestate model to a stochastic process in a continuous two-dimensional state space. In Section 5, we find the large-time probability of recurrence in closed analytic form and calculate the mean recurrence time (MRT) 70 analytically to leading order in N . In Section 5, we compare these analytical results to simulations and describe a scheme to fit the model to recurrence-free survival (Kaplan-Meier) curves from clinical cancer data, using ovarian cancer data as an example. Finally, in Section (6) we present our concluding remarks. Overview of the discrete-state modelThe precise discrete model for tumor recurrence that will be described in this section was inspired by 75 previous work on the effect of quiescence (i.e., the presence of dormant tumor foci) on treatment success, such as the work of Komarova and Wodarz [8], which inspired the stochastic model described below, or to deterministic versions of their model, proposed in [9], [10], or [11]. However, in contrast to these earlier studies, the focus of our paper is on finding a relatio...

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“…Historically, ATC was said to constitute 5-15% of all thyroid carcinomas in UnitedStates 1 and 10-50% in 3% worldwide of the total number of cases 3 . The decrease over time may be partially related to iodine prophylaxis and an overall decrease in endemic iodine deficient goiter [3][4][5][6] . Available online at: www.ijmrr.in 163 | P a g e death [4][5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Protracted Cisplatinum Infusion in Advanced Anaplastic Thyroid Cancer

Ghosh¹,

Singh

2013

Int J Med Res Rev

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Introduction: Anaplastic thyroid cancer (ATC) constitutes 1-3% of all thyroid malignancies. Most of the patients of anaplastic thyroid cancer presents with advanced inoperable lesion associated with neck mass dysphagia, and SVC syndrome. At this stage only treatment that can be offered is chemotherapy. Present study evaluates protracted (8 hr) Cisplatinum (CDDP) infusion along with doxorubucin in comparison to conventional (1hr) Cisplatinum + doxorubucin in advanced anaplastic thyroid cancer in terms of tolerance, toxicities and response rates. Methods: 32 previously untreated cases of stage III/IV inoperable anaplastic thyroid cancer were included in the present study. Patients were divided into 2 arms of 16 patients each. Arm I (16 patients) received 1 hr Cisplatin (CDDP) infusion 75mg/m2 + Doxorubicin 60mg/m2 infusion & Arm II (16 patients) received protracted 8 hrs CDDP infusion 75mg/m2+ Doxorubicin 60mg/m2 infusion. All patients were evaluated for tolerance, toxicities and response rate. Results: Arm II patients showed better locoregional response with CR 31.25%, PR 50%, SD 6.25%,PrD. 12.5% as compared to Arm I patients with CR 12.5%, PR 43.75%, SD 18.75%, Pr. D 25%, p= .02. Toxicities like mucositis, nausea & vomiting, diarrhea, nephrotoxicity were also significantly less in Arm II. After completion of 3-4cycles of Induction CT, all patients were treated with External Radiotherapy of 60-66Gy, followed with 2-3 cycles of adjuvant CT. Conclusion: From the present study it can be concluded that protracted cisplatinum infusion along with other chemotherapeutic drugs is an effective and acceptable CT regimen in advanced inoperable thyroid cancer.

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Leader in war on cancer looks ahead: talking with Vincent T. DeVita, Jr, MD

Cited by 10 publications

References 0 publications

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

In silico dissection of cell-type-associated patterns of gene expression in prostate cancer

A Quasi Birth-and-Death Model For Tumor Recurrence

Evaluation of Protracted Cisplatinum Infusion in Advanced Anaplastic Thyroid Cancer

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