Harnessing Tumor Evolution to Circumvent Resistance

Pogrebniak, Katherine; Curtis, Christina

doi:10.1016/j.tig.2018.05.007

Cited by 59 publications

(48 citation statements)

References 98 publications

(110 reference statements)

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“…The first and most commonly accepted molecular explanation for both metastatic dissemination and the al-most inevitable emergence of therapy resistance and tumor recurrence invokes genetic intratumor heterogeneity (ITH) (Nowell 1976;Yachida et al 2010;Sottoriva et al 2013;Jamal-Hanjani et al 2015;Pogrebniak and Curtis 2018). Genetic ITH may arise as a consequence of, among others, replication errors, UV-induced mutagenesis, inefficient DNA damage repair, telomere attrition, or chromosome segregation defects (Jeggo et al 2016).…”

Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

“…Note that while genetic diversity within a population may confer some cells with a growth or survival advantage when exposed to a specific stress signal, the same genetic variants may exhibit a selective disadvantage when faced with a different challenge (McGranahan and Swanton 2015). Increasing evidence suggests that, while important, genetic ITH appears insufficient to explain the emergence of therapy resistance and the biology of cancer progression, including the process of metastatic dissemination (Pisco and Huang 2015;Pogrebniak and Curtis 2018).…”

Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

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Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

2019

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An incomplete view of the mechanisms that drive metastasis, the primary cause of cancer-related death, has been a major barrier to development of effective therapeutics and prognostic diagnostics. Increasing evidence indicates that the interplay between microenvironment, genetic lesions, and cellular plasticity drives the metastatic cascade and resistance to therapies. Here, using melanoma as a model, we outline the diversity and trajectories of cell states during metastatic dissemination and therapy exposure, and highlight how understanding the magnitude and dynamics of nongenetic reprogramming in space and time at single-cell resolution can be exploited to develop therapeutic strategies that capitalize on nongenetic tumor evolution.

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Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

Section: Genetic Vs Nongenetic Intratumor Heterogeneitymentioning

confidence: 99%

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

2019

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“…23 Such heterogeneity also provides a substrate for drug resistance in cancer. 24 On the other hand, we can also utilize the principles of evolution to better treat cancer, for example, through so-called adaptive therapy.…”

Section: Cell Lines Change Genetically Over Timementioning

confidence: 99%

Clonal evolution through genetic bottlenecks and telomere attrition: Potential threats to in vitro data reproducibility

Gisselsson

Lichtenzstejn

Kachko

et al. 2018

Genes Chromosomes & Cancer

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Tissue cultures of immortalized human cells, also known as established cell lines, are broadly accessible and cost‐efficient tools for biomedical research. We here review potential genetic sources of systematic error in cell line experiments due to clonal evolution in vitro. In particular, the authors highlight alterations in telomere function over prolonged culture and population bottlenecks, respectively, as two commonly overlooked phenomena that can result in significant alterations in cell line genotypes over just one or a few passages in vitro. These alterations may include changes in mutation status of oncogenes and large scale chromosomal imbalances. We introduce a simple list of factors to be avoided in order to reduce the risk of data misinterpretation due to clonal evolution, including unacknowledged in vitro selection pressures, prolonged culture per se, harsh population size reductions, experiments at early phases after establishment, and the employment of cell lines not sufficiently analyzed by high resolution genetic techniques.

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“…Variation can occur among tumors of the same histological subtype, giving rise to variability in therapeutic responses among patients. Cellular heterogeneity can also occur within tumors, allowing cancer to evolve over the course of disease progression, resulting in drug resistance, treatment failure, and disease recurrence [1][2][3] . An important source of tumor heterogeneity is the molecular variation among subclones and even individual cells within a tumor.…”

Section: Introductionmentioning

confidence: 99%

Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

Davis-Marcisak

Orugunta

Stein-O’Brien

et al. 2018

Preprint

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Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Singlecell RNA-sequencing (scRNA-seq) technologies reveal the prevalence of intra-and inter-tumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intra-and inter-tumor molecular heterogeneity. We devised a new algorithm, Expression Variation Analysis in Single Cells (EVAsc), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVAsc has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. We then apply EVAsc to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics, i.e. immunogenicity, cancer subtypes, and metastasis. Immune pathway heterogeneity in hematopoietic cell populations in breast tumors corresponded to the amount diversity present in the T-cell repertoire of each individual. In head and neck squamous cell carcinoma (HNSCC) patients, we found dramatic differences in pathway dysregulation across basal primary tumors. Within the basal primary tumors we also identified increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. Moreover, cells in HNSCC primary tumors had significantly more heterogeneity across pathways than cells in metastases, consistent with a model of clonal outgrowth. These results demonstrate the broad utility of EVAsc to quantify inter-and intra-tumor heterogeneity from scRNA-seq data without reliance on low dimensional visualization.

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Harnessing Tumor Evolution to Circumvent Resistance

Cited by 59 publications

References 98 publications

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities

Clonal evolution through genetic bottlenecks and telomere attrition: Potential threats to in vitro data reproducibility

Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

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