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  • American Association for Cancer Research (AACR)  (8)
  • 1
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2009
    In:  Cancer Research Vol. 69, No. 10 ( 2009-05-15), p. 4493-4501
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 69, No. 10 ( 2009-05-15), p. 4493-4501
    Abstract: Clinical outcome prognostication in oncology is a guiding principle in therapeutic choice. A wealth of qualitative empirical evidence links disease progression with tumor morphology, histopathology, invasion, and associated molecular phenomena. However, the quantitative contribution of each of the known parameters in this progression remains elusive. Mathematical modeling can provide the capability to quantify the connection between variables governing growth, prognosis, and treatment outcome. By quantifying the link between the tumor boundary morphology and the invasive phenotype, this work provides a quantitative tool for the study of tumor progression and diagnostic/prognostic applications. This establishes a framework for monitoring system perturbation towards development of therapeutic strategies and correlation to clinical outcome for prognosis.[Cancer Res 2009;69(10):4493–501] Major Findings We apply a biologically founded, multiscale, mathematical model to identify and quantify tumor biologic and molecular properties relating to clinical and morphological phenotype and to demonstrate that tumor growth and invasion are predictable processes governed by biophysical laws, and regulated by heterogeneity in phenotypic, genotypic, and microenvironmental parameters. This heterogeneity drives migration and proliferation of more aggressive clones up cell substrate gradients within and beyond the central tumor mass, while often also inducing loss of cell adhesion. The model predicts that this process triggers a gross morphologic instability that leads to tumor invasion via individual cells, cell chains, strands, or detached clusters infiltrating into adjacent tissue producing the typical morphologic patterns seen, e.g., in the histopathology of glioblastoma multiforme. The model further predicts that these different morphologies of infiltration correspond to different stages of tumor progression regulated by heterogeneity.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2009
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 69, No. 10 ( 2009-05-15), p. 4484-4492
    Abstract: Nearly 30% of women with early-stage breast cancer develop recurrent disease attributed to resistance to systemic therapy. Prevailing models of chemotherapy failure describe three resistant phenotypes: cells with alterations in transmembrane drug transport, increased detoxification and repair pathways, and alterations leading to failure of apoptosis. Proliferative activity correlates with tumor sensitivity. Cell-cycle status, controlling proliferation, depends on local concentration of oxygen and nutrients. Although physiologic resistance due to diffusion gradients of these substances and drugs is a recognized phenomenon, it has been difficult to quantify its role with any accuracy that can be exploited clinically. We implement a mathematical model of tumor drug response that hypothesizes specific functional relationships linking tumor growth and regression to the underlying phenotype. The model incorporates the effects of local drug, oxygen, and nutrient concentrations within the three-dimensional tumor volume, and includes the experimentally observed resistant phenotypes of individual cells. We conclude that this integrative method, tightly coupling computational modeling with biological data, enhances the value of knowledge gained from current pharmacokinetic measurements, and, further, that such an approach could predict resistance based on specific tumor properties and thus improve treatment outcome. [Cancer Res 2009;69(10):4484–92] Major Findings By extracting mathematical model parameter values for drug and nutrient delivery from monolayer (one-dimensional) experiments and using the functional relationships to compute drug delivery in MCF-7 spheroid (three-dimensional) experiments, we use the model to quantify the diffusion barrier effect, which alone can result in poor response to chemotherapy both from diminished drug delivery and from lack of nutrients required to maintain proliferative conditions.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2009
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    detail.hit.zdb_id: 410466-3
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  • 3
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2006
    In:  Cancer Research Vol. 66, No. 3 ( 2006-02-01), p. 1597-1604
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 66, No. 3 ( 2006-02-01), p. 1597-1604
    Abstract: The intracellular and extracellular dynamics that govern tumor growth and invasiveness in vivo remain poorly understood. Cell genotype and phenotype, and nutrient, oxygen, and growth factor concentrations are key variables. In previous work, using a reaction-diffusion mathematical model based on variables that directly describe tumor cell cycle and biology, we formulated the hypothesis that tumor morphology is determined by the competition between heterogeneous cell proliferation caused by spatial diffusion gradients, e.g., of cell nutrients, driving shape instability and invasive tumor morphologies, and stabilizing mechanical forces, e.g., cell-to-cell and cell-to-matrix adhesion. To test this hypothesis, we here obtain variable-based statistics for input to the mathematical model from in vitro human and rat glioblastoma cultures. A linear stability analysis of the model predicts that glioma spheroid morphology is marginally stable. In agreement with this prediction, for a range of variable values, unbounded growth of the tumor mass and invasion of the environment are observed in vitro. The mechanism of invasion is recursive subspheroid component development at the tumor viable rim and separation from the parent spheroid. Results of computer simulations of the mathematical model closely resemble the morphologies and spatial arrangement of tumor cells from the in vitro model. We propose that tumor morphogenesis in vivo may be a function of marginally stable environmental conditions caused by spatial variations in cell nutrients, oxygen, and growth factors, and that controlling these conditions by decreasing spatial gradients could benefit treatment outcomes, whereas current treatment, and especially antiangiogenic therapy, may trigger spatial heterogeneity (e.g., local hypoxia), thus causing invasive instability. (Cancer Res 2006; 66(3): 1597-604)
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2006
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    detail.hit.zdb_id: 410466-3
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1963-1963
    Abstract: Determining early biomarkers of long-term survival remain a significant challenge for solid tumors. Certain spatial patterns of immune and stroma cells within tumors have been correlated with treatment response across cancer types, including breast cancer. Mechanical and physical microenvironmental signatures have emerged as drivers of cancer aggressiveness and invasiveness. This suggests that physio/mechanical structures may drive the formation of favorable immune-tumor-stroma cell patterns. In this work, we use a novel 60-marker imaging mass cytometry panel that included 16 tumor markers, 20 immune markers and 24 microenvironmental markers to resolve spatial patterns of cells, mechanical, structural, and other biomarkers within 700 clinical tumor samples (tissue microarrays from untreated primary breast cancers). Table 1 Sample distribution, patients were also treated surgically. Imaging and clinical data (eg. pathology, treatment, 10+ years survival) were integrated and analyzed to extract cell phenotypes, neighboring cells/markers and establish cell density, microenvironmental marker presence, and repeating spatial cell/marker patterns in all samples. Several markers showed significant increased expression in the survival group including CD3, CD44, CD20 for cellular markers, α-SMA, Pan-Cytokeratin, Cytokeratin 5, MMP2, LOX, and HIF1α for mechanical/microenvironmental markers. Conversely, breast cancer death samples exhibited upregulation of Na+/K+ ATPase, hCA9, and Ki67. Moreover, we identified that the co-localization of mechanical markers such as Integrin β1 and Plakoglobin is a signature of tumors with poor outcome, while the individual presence of either does not affect survival. For each of the cells/markers studied, we investigated functional relationships and identified clusters that drive survival such as Vimentin+/β-actin+ B cells, which suggests that the role of mechanics is critical to the tumor-controlling functions of immune cells. Long-term survival Cohort Survival Breast cancer death N samples 174 113 Long-term disease status Disease-free 94% 14% Local reoccurrence 4% 59% Distant reoccurrence 2% 27% Treatment No adjuvant treatment 3% 10% Adj. radiation 3% 4% Adj. chemo 0% 4% Adj. endocrine 28% 7% Adj .rad + chemo 13% 30% Adj. rad + endocrine 25% 35% Adj. chemo + endocrine 6% 4% Adj. rad + chemo + endocrine 21% 6% Citation Format: Sara Nizzero, Licheng Zhang, Yitian Xu, Maria J. Pelaez-Soni, Prashant Dogra, Brian A. Menegaz, Lee B. Jordan, Colin A. Purdie, Philip R. Quinlan, Chandandeep Nagi, Karla A. Sepulveda, Philipp Oertle, Tobias A. Appenzeller, Shu-Hsia Chen, Marko Loparic, Zhihui Wang, Vittorio Cristini, Marija Plodinec, Alastair M. Thompson. Spatial patterns of microenvironmental biomarkers drive long-term breast cancer outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1963.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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    detail.hit.zdb_id: 410466-3
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  • 5
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 24, No. 23 ( 2018-12-01), p. 5883-5894
    Abstract: Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology. Experimental Design: We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology. Results: In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth. Conclusions: At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 5_Supplement ( 2023-03-01), p. PD4-04-PD4-04
    Abstract: Background: Understanding breast cancer progression and the relationships among biomarkers in the tumor and tumor microenvironment could go beyond established prognostic markers of breast cancer. Poor response and recurrence may indeed be a consequence of the highly heterogeneous spatial distribution of biomarkers within cancers, and/or the synergistic and antagonistic relationship between co-localized biomarkers. Recently, mechanical and physical microenvironmental signatures have emerged as relevant in determining cancer aggressiveness and invasiveness. This suggests that physical structures in the tumor tissue may drive favorable immune-tumor-stroma cell patterns. However, current assessment of tumor biopsies is limited in the ability to quantify and spatially resolve several different subtypes of cells and biomarkers within tumors. Methods: We developed a 60-marker imaging mass cytometry panel to resolve high-plex spatial patterns of cells, signaling, and microenvironmental biomarkers within tumor tissues. Our panel includes 16 tumor markers, 20 immune markers and 24 microenvironmental markers. We built an innovative computational tool to identify recurring spatial patterns of these markers within the tumor microenvironment, and define the spatial scale of heterogeneity of such patterns. We correlated the results from this spatial analysis to prospectively collected long term clinical outcome variables (e.g. 10 year survival, local and distant recurrence) in primary breast cancers sampled at baseline. Our patient cohort comprised 287 samples of patients treated with surgery and a radiation, chemotherapy, endocrine therapy, or combinations of these post-surgery. Of these, 174 were from patients alive 5 years post diagnosis, and 113 from patients lost to breast cancer deaths. Living patients were evaluated for recurrence, and of these 94% were disease free at the end of the study, while 4% had local recurrence and 2% distant metastasis. Of the dead patients, 59% had local recurrence while 27% had distant metastasis. Results: We investigated first all patients independent of tumor subtype; in this analysis the presence of both endothelial (CD31+) or HLADR+ cells were consistently associated with long term survival. We further investigated the distribution of all 60 markers in Lum A, Lum B, Lum like, Her2+ and triple negative subtypes. Among the results we confirmed the prognostic role of known biomarkers such as p53+ as a biomarker for poor survival in Luminal B. We also identified complex microenvironmental patterns associated with outcome. For example, the presence of PD1+ cells in collagen rich environments were generally associated with long terms survival in Luminal B patients. With our spatial analysis tool we further investigated intra-patient and inter-patient spatial distribution and classified clusters predictive of outcome beyond heterogeneity. We found that beyond the mere positivity of each marker, the spatial distribution and co-localization of different immune, tumor and mechanical markers determines long term outcome in different subtypes. Specifically, we investigated the role of vimentin within different microenvironments and tumor subtypes. We identified the co-localization of hCa9 and vimentin as strongly associated with poor 5 year outcome, independent of tumor subtype. Moreover, in Luminal A patients while the presence of clusters exclusively positive for vimentin was associated with poor survival, vimentin co-expression with β actin and co-localization of XBP1+ cancer cells and immune cells in a collagen matrix was associated with longer survival. Conclusion: These results suggest the importance of mechanics and physics in determining spatial distribution of tumor-promoting and tumor-inhibiting immune cells, offering new avenues of physics-based therapeutic targets. Citation Format: Sara Nizzero, Maria Pelaez Soni, Yitian Xu, Licheng Zhang, Junjun Zheng, Brian A. Menegaz, Lee B Jordan, Colin A Purdie, Philip R Quinlan, Chandandeep Nagi, Karla A Sepulveda, Philipp Oertle, Tobias A Appenzeller, Marko Loparic, Zhihui Wang, Shu-Hsia Chen, Vittorio Cristini, Marija Plodinec, Alastair M. Thompson. PD4-04 A quantitative spatial analysis of microenvironmental biomarkers for breast cancer outcome [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-04.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 7
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2005
    In:  Clinical Cancer Research Vol. 11, No. 19 ( 2005-10-01), p. 6772-6779
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 11, No. 19 ( 2005-10-01), p. 6772-6779
    Abstract: Purpose: A solid tumor embedded in host tissue is a three-dimensional arrangement of cells and extracellular matrix that acts as a sink of oxygen and cell nutrients, thus establishing diffusional gradients. This and variations in vascular density and blood flow typically produce intratumoral regions of hypoxia and acidosis, and may result in spatially heterogeneous cell proliferation and migration. Here, we formulate the hypothesis that through these mechanisms, microenvironmental substrate gradients may drive morphologic instability with separation of cell clusters from the tumor edge and infiltration into surrounding normal tissue. Experimental Design: We used computer simulations and in vitro experiments. Results: We provide evidence that morphologic instability could be suppressed in vivo by spatially homogeneous oxygen and nutrient supply because normoxic conditions act both by decreasing gradients and increasing cell adhesion and, therefore, the mechanical forces that maintain a well-defined tumor boundary. A properly working tumor microvasculature can help maintain compact noninfiltrating tumor morphologies by minimizing oxygen and nutrient gradients. In contrast, antiangiogenic therapy, by increasing microenvironmental heterogeneity, may promote morphologic instability, leading to invasive patterns even under conditions in which the overall tumor mass shrinks. Conclusions: We conclude that therapeutic strategies focused solely on reduction of vascular density may paradoxically increase invasive behavior. This theoretical model accounts for the highly variable outcome of antiangiogenic therapy in multiple clinical trials. We propose that antiangiogenic strategies will be more consistently successful when aimed at “normalizing” the vasculature and when combined with therapies that increase cell adhesion so that morphologic instability is suppressed and compact, noninvasive tumor morphologies are enforced.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2005
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    detail.hit.zdb_id: 2036787-9
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  • 8
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2011
    In:  Cancer Research Vol. 71, No. 2 ( 2011-01-15), p. 298-302
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 71, No. 2 ( 2011-01-15), p. 298-302
    Abstract: Cancer models relating basic science to clinical care in oncology may fail to address the nuances of tumor behavior and therapy, as in the case, discussed herein, of the complex multiscale dynamics leading to the often-observed enhanced invasiveness, paradoxically induced by the very antiangiogenic therapy designed to destroy the tumor. Studies would benefit from approaches that quantitatively link the multiple physical and temporal scales from molecule to tissue in order to offer outcome predictions for individual patients. Physical oncology is an approach that applies fundamental principles from the physical and biological sciences to explain certain cancer behaviors as observable characteristics arising from the underlying physical and biochemical events. For example, the transport of oxygen molecules through tissue affects phenotypic characteristics such as cell proliferation, apoptosis, and adhesion, which in turn underlie the patient-scale tumor growth and invasiveness. Our review of physical oncology illustrates how tumor behavior and treatment response may be a quantifiable function of marginally stable molecular and/or cellular conditions modulated by inhomogeneity. By incorporating patient-specific genomic, proteomic, metabolomic, and cellular data into multiscale physical models, physical oncology could complement current clinical practice through enhanced understanding of cancer behavior, thus potentially improving patient survival. Cancer Res; 71(2); 298–302. ©2011 AACR.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2011
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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