IJS KOLOKVIJ, Sreda, 29. 06. 2016; ob 13. uri; prof. dr. Orly Alter

[Tanja Debevec]

Vabimo vas na 21. predavanje iz sklopa "Kolokviji na IJS" v letu 2015/16, ki bo v sredo, 29. junija 2016, ob 13. uri v Veliki predavalnici Instituta »Jožef Stefan«  na Jamovi cesti 39 v Ljubljani. Napovednik predavanja najdete tudi na naslovu http://www.ijs.si/ijsw/Koledar_prireditev, posnetke preteklih predavanj pa na http://videolectures.net/kolokviji_ijs. 

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prof. dr. Orly Alter 

Univerza v Uti, Združene države Amerike

 

Multitenzorske dekompozicije za personalizirano diagnostiko in prognostiko raka

 

Razvijamo nove matematične okvire, s katerimi je mogoče napraviti, česar nobena druga metoda ne zmore, namreč ustvariti en sam koherentni model iz več večdimenzionalnih množic podatkov, znanih kot tenzorjev. Ti okviri - primerjalne spektralne dekompozicije - so posplošitve tistih, na katerih leži teoretični opis fizikalnega sveta, in z njimi primerjamo množice podatkov, ki opisujejo različne vidike izbrane bolezni, kot so genomski profili več vrst celic v isti skupini bolnikov, izmerjeni večkrat z različnimi metodami. Z uporabo kompleksne strukture in ne poenostavljanjem teh množic podatkov ti okviri omogočajo razlikovanje vzorcev sprememb DNA, do katerih pride le v tumorskih genomih, od tistih pri normalnih celicah v telesu ter od variacij, ki so posledica eksperimentalnih nedoslednosti. Pričakujemo, da bodo vzorci, ki jih odkrivamo v podatkih, lahko ponudili odgovore na odprta vprašanja v zvezi s povezavo med tumorskim genomom in razvojem bolezni pri bolniku. Nedavna primerjava genomov tumorskih in normalnih celic v skupinah bolnikov z rakom na jajčnikih oziroma z glioblastomom je razkrila vzorce sprememb v številu kopij DNA, ki so bile korelirane z bolnikovo možnostjo za preživetje in odzivom na kemoterapijo. Zadnja tri desetletja je najboljši prediktor preživetja pri raku na jajčnikih stadij tumorja; čeprav je več kot četrtina tumorjev na jajčnikih odporna na primarno kemoterapijo na osnovi platine, ni nobene diagnostične metode, s katero bi pred terapijo lahko razlikovali med odpornimi in odzivnimi tumorji. Zadnjih pet desetletij je najboljši prognostični indikator pri glioblastomu bolnikova starost ob diagnozi. Podatki o raku na jajčnikih in glioblastomu so bili objavljeni, a vzorci so ostali neznani, dokler jih nismo analizirali s primerjalno spektralno dekompozicijo. Po eksperimentalni revalidaciji bomo odkrite vzorce ponudili klinikam, da jih bodo lahko uporabili pri personaliziranih diagnostičnih in prognostičnih patoloških laboratorijskih testih, s katerimi bo mogoče napovedati bolnikovo možnost prezivetja in odziv na terapijo ter tako pomagati zdravnikom ustrezno prilagoditi zdravljenje.

Predavanje bo v angleščini.

Lepo vabljeni!

 

 

 




We invite you to the 21th Institute colloquium in the academic year 2015/16. The colloquium will be held on Wednesday June 29, 2016 at 1 PM in the main Institute lecture hall, Jamova 39, Ljubljana. To read the abstract click  http://www.ijs.si/ijsw/Koledar_prireditev. Past colloquia are posted on  http://videolectures.net/kolokviji_ijs.

 

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prof. dr. Orly Alter 

University of Utah, United States of America

 

Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics

 

 

We are developing new mathematical frameworks to do what no others currently can, that is, create a single coherent model from multiple high-dimensional datasets, known as tensors. The frameworks – comparative spectral decompositions – generalize those that underlie the theoretical description of the physical world. We are using the frameworks to compare and contrast datasets recording different aspects of a single disease, such as genomic profiles of multiple cell types from the same set of patients, measured more than once by several different methods. By using the complex structure of the datasets, rather than simplifying them as is commonly done, the frameworks enable the separation of patterns of DNA alterations – which occur only in the tumor genomes – from those that occur in the genomes of normal cells in the body, and from variations caused by experimental inconsistencies. The patterns that we uncover in the data are expected to offer answers to the open question of the relation between a tumor's genome and a patient’s outcome. For example, recent comparisons of the genomes of tumor and normal cells from the same sets of ovarian and, separately, glioblastoma brain cancer patients uncovered patterns of DNA copy-number alterations that were found to be correlated with a patient’s survival and response to chemotherapy. For three decades prior, the best predictor of ovarian cancer survival was the tumor's stage; more than a quarter of ovarian tumors are resistant to the platinum-based chemotherapy, the first-line treatment, yet no diagnostic existed to distinguish resistant from sensitive tumors before the treatment. For five decades prior, the best prognostic indicator of glioblastoma was the patient's age at diagnosis. The ovarian and brain cancer data were published, but the patterns remained unknown until the team applied their comparative spectral decompositions. Pending experimental revalidation, we will bring the patterns that we uncover to the clinic, to be used in personalized diagnostic and prognostic pathology laboratory tests. The tests would predict a patient’s survival and response to therapy, and doctors could tailor treatment accordingly.

 

Cordially invited!

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