Understanding Genotype-Phenotype Effects in Cancer via Network Approaches

Kim, Yoo-Ah; Cho, Dong-Yeon; Przytycka, Teresa M.

doi:10.1371/journal.pcbi.1004747

Cited by 59 publications

(41 citation statements)

References 84 publications

(87 reference statements)

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“…However, as has become clear in other solid tumor types, models based solely on clinicopathologic variables may fall short in assessing individual tumor prognosis, and are even more unlikely to be predictive of response to individual therapeutic agents. This has led to an interest in biomarker identification and pathway network integration that might provide an alternative window into relevant tumor cell biology and behavior …”

Section: Discussionmentioning

confidence: 99%

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

Hyams

Cook²,

Buzaid

2018

Journal of Surgical Oncology

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New therapeutic modalities for melanoma promise benefit in selected individuals. Efficacy appears greater in patients with lower tumor burden, suggesting an important role for risk‐stratified surveillance. Robust predictive markers might permit optimization of agent to patient, while low‐risk prognostic markers might guide more conservative management. This review evaluates protein, gene, and multiplexed marker panels that may contribute to better risk assessment and improved management of patients with cutaneous melanoma.

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Section: Discussionmentioning

confidence: 99%

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

Hyams

Cook²,

Buzaid

2018

Journal of Surgical Oncology

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“…Constraint (4) impose that the total number of sets (i.e., selected genes) in the solution is at most k. Constraints (5) and (6) define how many times each sample has been covered by genes in I and D, respectively. Constraints (7) (resp., Constraints (8)) ensure that for each sample j ∈ P , if j is covered by increased (resp., decreased) sensitivity genes in the current solution then the number of times j is covered by I (resp., D) in the solution is at least 1.…”

Section: S12 Ilp Formulationmentioning

confidence: 99%

Identifying Drug Sensitivity Subnetworks with NETPHLIX

Kim

Basso

Wójtowicz

et al. 2019

Preprint

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Phenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. One of the important challenges in the area is to predict drug response on a personalized level and to understand the causes of different responses. The pathway-centric view of cancer significantly advanced the understanding of genotype-phenotype relationships. However, most network identification methods in cancer focus on identifying subnetworks that include general cancer drivers or are associated with discrete features such as cancer subtypes, hence cannot be applied directly for the analysis of continuous features like drug response. On the other hand, existing genome wide association approaches do not fully utilize the complex and heterogeneous proprieties of cancer mutational landscape. To address these challenges, we developed a computational method, named NETPHIX (NETwork-to-PHenotype assocIation with eXclusivity), which aims to identify subnetworks of genes whose genetic alterations are associated with a continuous cancer phenotype. Leveraging the properties of cancer mutations such as mutual exclusivity and the interactions among genes, we formulate the problem as an integer linear program and solve it optimally to obtain a set of associated genes. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with drug responses, and many of the modules are also validated in another independent dataset. Utilizing interaction information, NETPHIX modules are functionally coherent, and can thus provide important insights into drug action.

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“…Na druhou stranu i fenotyp geneticky identických buněk může být odlišný, neboť přestože jsou nádory architektonicky komplexní, liší se v míře regionální vaskulatury, infilt race hostitelskými (nenádorovými) buň kami zánětlivými nebo buňkami imunit ního systému, složkami pojivové tkáně a dalšími vlastnostmi. Tyto specifické re gionální vlastnosti vedou ke vzniku roz dílných mikroprostředí a tím k rozvoji fenotypové heterogenity [18]. ITH se tedy projevuje nejednotností na mnoha úrovních, vč.…”

Section: Vnitřní Heterogenita Nádorůunclassified

Variability of Solid Cancer Cell Population and Its Consequences for Cancer Diagnostics and Treatment

Brychtová¹,

Valík²,

Vojtesek³

2018

Klin Onkol

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Regionální centrum aplikované molekulární onkologie, Masarykův onkologický ústav, Brno Souhrn Východiska: Nádorové onemocnění se vyvíjí na základě vzniklé somatické mutace evolučním proce sem podle Darwinovských pravidel. Vývoj nádoru je proces dynamické klonální expanze a následné selekce vedoucí ke vzniku geneticky odlišných subpopulací přizpůsobených odlišným podmín kám nádorového mikroprostředí konkrétního hostitele. Genom jednotlivých nádorových buněk je utvářen různými selekčními tlaky. Evoluční dráha vývoje nádoru má ve většině případů rozvětvený charakter a jednotlivé nádorové subklony se tak vyvíjejí paralelně. Diverzita klonů v rámci jediné ná dorové tkáně vede ke vzniku genetické, epigenetické a fenotypové variability, což současně předsta vuje hlavní překážku exaktní dia gnostiky a účinné personalizované léčby konkrétního nádorového onemocnění u konkrétního jedince. Pokroky v sekvenačních technikách nám v současnosti umož ňují odpovědět na otázky ohledně růstu a progrese heterogenních nádorů a také jejich schopnosti odpovídat na léčbu. Porozumění mechanizmu vzniku a sledování změn na úrovni nádorových klonů v průběhu progrese nádorového onemocnění může pomoci zlepšit účinnost protinádorové léčby. Cíl: Tento přehledový článek se zabývá nádorovou heterogenitou a ukazuje, jak klonální diverzita ovlivňuje nádorovou heterogenitu na úrovni genetické, epigenetické i proteinové. Dále popisuje, jak fylogenetika, efektivní nástroj systémové bio logie, může pomoci při sledování klonální evoluce ná doru v průběhu jeho progrese a tvorbě metastáz. Na závěr také hodnotí, jakým způsobem přispívá nádorová heterogenita k problémům v dia gnostice nádorových onemocnění a jejich léčbě. Klíčová slova evoluce nádorů-nádorová heterogenita-nádorová fylogenetika-klonální evoluce Summary Background: Cancer develops as a result of somatic mutations and evolutionary processes with a Darwinian character. Tumors evolve by dynamic clonal expansion and selection to form geneti cal ly diverse cell subpopulations adapted to different tumor microenvironmental conditions. Within cancer cells, the genome is shaped by various selective pressures. Cancer evolution often follows a branched trajectory with divergent subclones evolving simultaneously. Clonal diversity within the same tumor results in genetic, epigenetic and phenotypic variability in tumor mass, which re presents a major obstacle for the development of efficient diagnostics and personalized treatment. Advances in sequencing techniques have enabled a better understanding of the growth, progres sion and response to cancer treatment in heterogeneous cancers. Concurrently, understanding the mechanisms involved and monitoring changes in cancer clones during disease progression may improve the efficiency of cancer therapy. Aim: In this review, we summarize available data on intra tumor heterogeneity. We show how intratumor heterogeneity, arising from clonal diversity, mani fests itself at various levels, including at the genetic, epigenetic, and protein levels. We describe how phylog...

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Understanding Genotype-Phenotype Effects in Cancer via Network Approaches

Cited by 59 publications

References 84 publications

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

Identification of risk in cutaneous melanoma patients: Prognostic and predictive markers

Identifying Drug Sensitivity Subnetworks with NETPHLIX

Variability of Solid Cancer Cell Population and Its Consequences for Cancer Diagnostics and Treatment

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