scholarly journals Modeling colorectal cancer evolution

2021 ◽  
Author(s):  
Atsushi Niida ◽  
Koshi Mimori ◽  
Tatsuhiro Shibata ◽  
Satoru Miyano
Keyword(s):  
Mathematical Modeling ◽  
Colorectal Cancer ◽  
Early Stage ◽  
Technological Development ◽  
Acquired Resistance ◽  
Genomic Analysis ◽  
Evolutionary Model ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Neutral Mutations

AbstractUnderstanding cancer evolution provides a clue to tackle therapeutic difficulties in colorectal cancer. In this review, together with related works, we will introduce a series of our studies, in which we constructed an evolutionary model of colorectal cancer by combining genomic analysis and mathematical modeling. In our model, multiple subclones were generated by driver mutation acquisition and subsequent clonal expansion in early-stage tumors. Among the subclones, the one obtaining driver copy number alterations is endowed with malignant potentials to constitute a late-stage tumor in which extensive intratumor heterogeneity is generated by the accumulation of neutral mutations. We will also discuss how to translate our understanding of cancer evolution to a solution to the problem related to therapeutic resistance: mathematical modeling suggests that relapse caused by acquired resistance could be suppressed by utilizing clonal competition between sensitive and resistant clones. Considering the current rate of technological development, modeling cancer evolution by combining genomic analysis and mathematical modeling will be an increasingly important approach for understanding and overcoming cancer.

scholarly journals Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities

2021 ◽  
Author(s):  
Jason I. Griffiths ◽  
Jinfeng Chen ◽  
Onalisa Winblad ◽  
Anne O’Dea ◽  
Priyanka Sharma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mathematical Models ◽  
Tumor Progression ◽  
Tumor Size ◽  
Early Stage ◽  
Acquired Resistance ◽  
Cancer Evolution ◽  
Breast Cancer Patients ◽  
Measurement Models ◽  
Long Term Treatment

AbstractBackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution.MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms.ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population.ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

scholarly journals Immunotherapy for Colorectal Cancer: Mechanisms and Predictive Biomarkers

2021 ◽  
Author(s):  
Lindsey Carlsen ◽  
Kelsey E. Huntington ◽  
Wafik S. El-Deiry
Keyword(s):  
Colorectal Cancer ◽  
Immune System ◽  
Cancer Cells ◽  
Mismatch Repair ◽  
Early Stage ◽  
Adoptive Cell Therapy ◽  
Acquired Resistance ◽  
Predictive Biomarkers ◽  
Immune Checkpoint Blockade ◽  
Oncolytic Viruses

Though early-stage colorectal cancer has a high 5-year survival rate of 65-92% depending on the specific stage, this probability drops to 13% after the cancer metastasizes. Frontline treatments for colorectal cancer such as chemotherapy and radiation often produce dose-limiting toxicities in patients and acquired resistance in cancer cells. Additional targeted treatments are needed to improve patient outcomes and quality of life. Immunotherapy involves treatment with peptides, cells, antibodies, viruses, or small molecules to engage or train the immune system to kill cancer cells. Preclinical and clinical investigations of immunotherapy for treatment of colorectal cancer including immune checkpoint blockade, adoptive cell therapy, monoclonal antibodies, oncolytic viruses, anti-cancer vaccines, and immune system modulators have been promising, but demonstrate limitations for patients with proficient mismatch repair enzymes. In this review, we discuss preclinical and clinical studies investigating immunotherapy for treatment of colorectal cancer and predictive biomarkers for response to these treatments. We also consider open questions including optimal combination treatments to maximize efficacy, minimize toxicity, and prevent acquired resistance and approaches to sensitize mismatch repair proficient patients to immunotherapy.

scholarly journals A unified simulation model for understanding the diversity of cancer evolution

2019 ◽  
Author(s):  
Atsushi Niida ◽  
Takanori Hasegawa ◽  
Hideki Innan ◽  
Tatsuhiro Shibata ◽  
Koshi Mimori ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Mutation Rate ◽  
Evolutionary Dynamics ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Evolutionary Processes ◽  
Stem Cell Hierarchy ◽  
Neutral Mutations ◽  
Short Time

ABSTRACTBecause cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

scholarly journals A unified simulation model for understanding the diversity of cancer evolution

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8842 ◽  
Author(s):  
Atsushi Niida ◽  
Takanori Hasegawa ◽  
Hideki Innan ◽  
Tatsuhiro Shibata ◽  
Koshi Mimori ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Mutation Rate ◽  
Evolutionary Dynamics ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Evolutionary Processes ◽  
Stem Cell Hierarchy ◽  
Neutral Mutations ◽  
Short Time

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

scholarly journals Genomic characterization of intrinsic and acquired resistance to cetuximab in colorectal cancer patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Steven M. Bray ◽  
Jeeyun Lee ◽  
Seung Tae Kim ◽  
Joon Young Hur ◽  
Philip J. Ebert ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Acquired Resistance ◽  
Genomic Analysis ◽  
Braf V600e ◽  
Intrinsic Resistance ◽  
Mtor Inhibition ◽  
Mesenchymal Transition ◽  
Colorectal Cancer Patients

Abstract Anti-EGFR antibodies are effective in therapies for late-stage colorectal cancer (CRC); however, many tumours are unresponsive or develop resistance. We performed genomic analysis of intrinsic and acquired resistance to anti-EGFR therapy in prospectively collected tumour samples from 25 CRC patients receiving cetuximab (an EGFR inhibitor). Of 25 CRC patients, 13 displayed intrinsic resistance to cetuximab; 12 were intrinsically sensitive. We obtained six re-biopsy samples at acquired resistance from the intrinsically sensitive patients. NCOA4–RET and LMNA–NTRK1 fusions and NRG1 and GNAS amplifications were found in intrinsic-resistant patients. In cetuximab-sensitive patients, we found KRAS K117N and A146T mutations in addition to BRAF V600E, AKT1 E17K, PIK3CA E542K, and FGFR1 or ERBB2 amplifications. The comparison between baseline and acquired-resistant tumours revealed an extreme shift in variant allele frequency of somatic variants, suggesting that cetuximab exposure dramatically selected for rare resistant subclones that were initially undetectable. There was also an increase in epithelial-to-mesenchymal transition at acquired resistance, with a reduction in the immune infiltrate. Furthermore, characterization of an acquired-resistant, patient-derived cell line showed that PI3K/mTOR inhibition could rescue cetuximab resistance. Thus, we uncovered novel genomic alterations that elucidate the mechanisms of sensitivity and resistance to anti-EGFR therapy in metastatic CRC patients.

Early stage commercialization strategies: How did Prius family affect Toyota electric vehicle development?

2018 ◽  
Vol 8 (2) ◽  
pp. 51
Author(s):  
Majid A Dehkordi
Keyword(s):  
Electric Vehicle ◽  
Diffusion Of Innovation ◽  
First Generation ◽  
Early Stage ◽  
Technological Development ◽  
Research Development ◽  
Strategic Decisions ◽  
Innovation Studies ◽  
Vehicle Development ◽  
Green Vehicles

Although researches in the eco-friendly innovation studies have contributed much to technological development, a limited contribution has been made to the importance of structural concepts, strategic decisions and early stage marketing in the diffusion of innovation. The uniqueness of this research lies in its effort of exploring Toyota’s commercialization strategies for the first generation of its green vehicles, Prius Hybrid and RAV4 EV. Literature is reviewed from both historical and technological perspectives. The Roger’s Diffusion model was used and on the basis on this review, it has been argued that Toyota’s hybrid vehicle commercialization strategy affected this company’s electric vehicle development at least for a decade. The results fill a gap in the literature, particularly in Green vehicles research, development, and marketing.

scholarly journals Novel genomic classifier for early stage colorectal cancer patients

2018 ◽  
Vol 29 ◽  
pp. viii33-viii34
Author(s):  
E. Letellier ◽  
M. Schmitz ◽  
A. Ginolhac ◽  
E. Koncina ◽  
M. Marchese ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Early Stage ◽  
Colorectal Cancer Patients
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