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In this work, we investigate the population dynamics of tumor cells under therapeutic pressure. Although drug treatment initially induces a reduction in tumor burden, treatment failure frequently occurs over time due to the emergence of…

Probability · Mathematics 2025-10-02 Kevin Leder , Zicheng Wang , Xuanming Zhang

Despite initial success, cancer therapies often fail due to the emergence of drug-resistant cells. In this study, we use a mathematical model to investigate how cancer evolves over time, specifically focusing on the state of the tumor when…

Probability · Mathematics 2023-08-01 Kevin Leder , Zicheng Wang

Mutation-induced drug resistance in cancer often causes the failure of therapies and cancer recurrence, despite an initial tumor reduction. The timing of such cancer recurrence is governed by a balance between several factors such as…

Probability · Mathematics 2013-07-22 Jasmine Foo , Kevin Leder

Resistance to therapy remains a significant challenge in cancer treatment, often due to the presence of a stem-like cell population that drives tumor recurrence post-treatment. Moreover, many anticancer therapies induce plasticity,…

Populations and Evolution · Quantitative Biology 2024-12-25 Chenyu Wu , Einar Bjarki Gunnarsson , Jasmine Foo , Kevin Leder

Tumor recurrence, driven by the evolution of drug resistance is a major barrier to therapeutic success in cancer. Resistance is often caused by genetic alterations such as point mutation, which refers to the modification of a single genomic…

Populations and Evolution · Quantitative Biology 2023-08-23 Aaron Li , Danika Kibby , Jasmine Foo

As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where…

Populations and Evolution · Quantitative Biology 2019-12-05 Stefano Avanzini , Tibor Antal

In oncology, recurrence after treatment is one of the major challenges, related to patients' survival and quality of life. Conventionally, prediction of cancer relapse has always relied on clinical observation with statistical model…

Machine Learning · Computer Science 2025-02-25 Muhammad Umer Qayyum , Muhammad Fahad , Nasrullah Abbasi

According to the National Cancer Institute, there were 9.5 million cancer-related deaths in 2018. A challenge in improving treatment is resistance in genetically unstable cells. The purpose of this study is to evaluate unsupervised machine…

Genomics · Quantitative Biology 2021-08-12 Anastasia Dunca , Frederick R. Adler

In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint…

Computational Engineering, Finance, and Science · Computer Science 2011-09-08 Luca Bortolussi , Alberto Policriti

In a mathematical model of interacting biological organisms, where external interventions may alter behavior over time, traditional models that assume fixed parameters usually do not capture the evolving dynamics. In oncology, this is…

Machine Learning · Computer Science 2025-12-18 Kayode Olumoyin , Lamees El Naqa , Katarzyna Rejniak

Major efforts to sequence cancer genomes are now occurring throughout the world. Though the emerging data from these studies are illuminating, their reconciliation with epidemiologic and clinical observations poses a major challenge. In the…

Populations and Evolution · Quantitative Biology 2010-11-18 Ivana Bozic , Tibor Antal , Hisashi Ohtsuki , Hannah Carter , Dewey Kim , Sining Chen , Rachel Karchin , Kenneth W. Kinzler , Bert Vogelstein , Martin A. Nowak

When confronted with an undesired cell population, such as bacterial infections or tumors, we seek the most effective treatment, designed to eliminate the population as rapidly as possible. A common practice is to monitor the cells…

Biological Physics · Physics 2025-01-23 Uzi Harush , Ravid Straussman , Baruch Barzel

We propose an extension of a standard stochastic individual-based model in population dynamics which broadens the range of biological applications. Our primary motivation is modelling of immunotherapy of malignant tumours. In this context…

Populations and Evolution · Quantitative Biology 2016-04-18 Martina Baar , Loren Coquille , Hannah Mayer , Michael Hölzel , Meri Rogava , Thomas Tüting , Anton Bovier

Some clinical and pre-clinical data suggests that treating some tumors at a mild, patient-specific dose might delay resistance to treatment and increase survival time. A recent mathematical model with sensitive and resistant tumor cells…

Dynamical Systems · Mathematics 2022-12-01 Frank Alvarez , Yannick Viossat

Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, and proteome of multiple systems at single-cell resolution. Now widely applied to cancer models, these assays…

Genomics · Quantitative Biology 2020-05-05 Allen W Zhang , Kieran R Campbell

Complex data features, such as unmodelled censored event times and variables with time-dependent effects, are common in cancer recurrence studies and pose challenges for Bayesian survival modelling. Current methodologies for predictive…

Methodology · Statistics 2026-01-12 Saku Suorsa , Aki Vehtari

Cancer cell lines have frequently been used to link drug sensitivity and resistance with genomic profiles. To capture genomic complexity in cancer, the Cancer Genome Project (CGP) (Garnett et al., 2012) screened 639 human tumor cell lines…

Applications · Statistics 2017-02-09 Hongmei Liu , J. Sunil Rao

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has…

Molecular Networks · Quantitative Biology 2014-09-09 Edwin Wang , Jinfeng Zou , Naif Zaman , Lenore K. Beitel , Mark Trifiro , Miltiadis Paliouras

We study large deviation events in the timing of disease recurrence. In particular, we are interested in modeling cancer treatment failure due to mutation-induced drug resistance. We first present a two-type branching process model of this…

Probability · Mathematics 2021-08-06 Pranav Hanagal , Kevin Leder , Zicheng Wang

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often…

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