TR202003833A1 - MYELOID ORIGIN SUPPRESSOR CELLS SPECIFIC BIOBARKER PANEL - Google Patents
MYELOID ORIGIN SUPPRESSOR CELLS SPECIFIC BIOBARKER PANELInfo
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- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
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Abstract
Buluş, granülositik miyeloid kökenli baskılayıcı hücrelerin (gMKBH) yüzeyinde bulunduğu bilinen yüzey proteinlerini kodlayan genlerin transkript varyantlarının MKBH popülasyonlarının (eMKBH, gMKBH ve mMKBH popülasyonları) karakterizasyonunda kullanılması ile ilgilidir. MKBH'lere özgü olduğu belirlenen transkript varyantlarının kodladığı izoform proteinlerin yüzey belirteci olarak kullanılabilirliği kronik enflamasyon, otoimmün hastalıklar ve kanserde yeni tedavi yaklaşımlarının üretilebilmesine de olanak sağlayacaktır.The invention relates to the use of transcript variants of genes encoding surface proteins known to be located on the surface of granulocytic myeloid-derived suppressor cells (gMCKD) in the characterization of MCKD populations (mCKD, gMCKD and mMCD populations). The use of isoform proteins encoded by transcript variants determined to be specific to MCKDs as surface markers will also enable the production of new treatment approaches in chronic inflammation, autoimmune diseases and cancer.
Description
TARIFNAME MIYELOID KÖKENLI BASKILAYlCl HÜCRELERE ÖZGÜ BIYOBELIRTEÇ PANELI Bulusun Ilgili Oldugu Teknik Alan Bulus, granülositik miyeloid kökenli baskilayici hücrelerin (gMKBH) yüzeyinde bulundugu bilinen proteinleri kodlayan genlerin transkript varyantlarinin MKBH popülasyonlarinin karakterizasyonunda kullanilmasi ile ilgilidir. MKBH'lere özgü oldugu belirlenen transkript varyantlarinin kodladigi izoforrn proteinlerin yüzey belirteci olarak kullanilabilirligi kronik enflamasyon, otoimmün hastaliklar ve kanserde yeni tedavi yaklasimlarinin üretilebilmesine de olanak saglayacaktir. DESCRIPTION SUMMARY OF MYELOID ORIGIN CELLS SPECIFIC BIOBETIC PANEL Technical Field of the Invention The invention is based on the presence of granulocytic myeloid-derived suppressor cells (gMCKD) on its surface. of MCKD populations of transcript variants of genes encoding known proteins. related to its use in characterization. Transcript determined to be specific to MCKDs The usability of isoforrn proteins encoded by variants as surface markers is chronic. to produce new treatment approaches in inflammation, autoimmune diseases and cancer. will also provide opportunities.
Bulusla Ilgili Teknigin Bilinen Durumu (Önceki Teknik) Miyeloid kökenli baskilayici hücrelerin (MKBH) kanser hastalarinda kesfedilmcsinin üzerinden yaklasik 20 yil geçmesine ragmen, bu hücrelerin immün sistemdeki fonksiyonel önemi henüz açikliga kavusturulamamistir. Yapilan çalismalarda alinan sonuçlar, MKBH popülasyonunun kanser ve diger hastaliklarda immün sistemin negatif regülasyonunda rol aldigini desteklemektedir. State of the Art of the Invention (Prior Art) Detection of myeloid-derived suppressor cells (MSD) in cancer patients Although approximately 20 years have passed since its importance has not yet been clarified. The results obtained in the studies, MKBH role in negative regulation of the immune system in cancer and other diseases supports it.
MKBH popülasyonlarinin ortak özellikleri miyeloid kökenli olmalari, henüz olgunlasmis olmasalar da patolojik aktivasyon geçirmeleri ve T hücrelerini baskilamadaki dikkate deger kapasiteleridir. Arastirmacilar farkli hastaliklarda çesitli MKBH alt-gruplari tanimlamis olsalar da tanimlanan MKBH popülasyonlarinin karakterizasyonunda kullanilan yöntem ve tekniksel farkliliklar sebebiyle yürütülen çalismalarin genel kabul görmesi çogu kez söz konusu olmamaktadir. MKBH popülasyonuna özgül biyobelirteçlerin henüz kesfedilmemis olmasi, MKBH biyolojisi arastirmalarinda yasanan güven probleminin temelini olusturmaktadir. ve HLA-DR yüzey belirteçlerinin farkli kombinasyonlari kullanilmaktadir. CDllb, CD33 ve lL-4Ra genel MKBH popülasyonunu tespit etmek için kullanilirken; bu üç belirteç yaninda CDl4-CD16 düsük VGFRI +HLA-DR- G-MKBH ve CD15+/-CD16-CD66b+/-VGFRl-HLA- DR düsük M-MKBH alt-tipleri olarak kabul edilmektedir. The common features of MCKD populations are that they are of myeloid origin, they are not yet mature. Although they are not, they are notable for their pathological activation and suppression of T cells. their capacities. Researchers have identified various subgroups of MCKD in different diseases. methods used to characterize identified MCKD populations, and It is often mentioned that the studies carried out due to technical differences are generally accepted. is not the subject. Biomarkers specific to the MCKD population have yet to be discovered. The fact that it is present underlies the trust problem experienced in MCKD biology research. forms. and different combinations of HLA-DR surface markers are used. CDllb, CD33 and IL-4Ra is used to detect the general MCKD population; next to these three markers CD14-CD16 low VGFRI +HLA-DR- G-MCKD and CD15+/-CD16-CD66b+/-VGFR1-HLA- DR are considered low M-MDG subtypes.
Son dönemde yapilan çok renkli immünfenotiplendirme çalismalarinda ise, insanda alti farkli TARIFNAME MIYELOID KÖKENLI BASKILAYlCl HÜCRELERE ÖZGÜ BIYOBELIRTEÇ PANELI Bulusun Ilgili Oldugu Teknik Alan Bulus, granülositik miyeloid kökenli baskilayici hücrelerin (gMKBH) yüzeyinde bulundugu bilinen proteinleri kodlayan genlerin transkript varyantlarinin MKBH popülasyonlarinin karakterizasyonunda kullanilmasi ile ilgilidir. MKBH'lere özgü oldugu belirlenen transkript varyantlarinin kodladigi izoforrn proteinlerin yüzey belirteci olarak kullanilabilirligi kronik enflamasyon, otoimmün hastaliklar ve kanserde yeni tedavi yaklasimlarinin üretilebilmesine de olanak saglayacaktir. In the recent multicolor immunophenotyping studies, six different types of human DESCRIPTION SUMMARY OF MYELOID ORIGIN CELLS SPECIFIC BIOBETIC PANEL Technical Field of the Invention The invention is based on the presence of granulocytic myeloid-derived suppressor cells (gMCKD) on its surface. of MCKD populations of transcript variants of genes encoding known proteins. related to its use in characterization. Transcript determined to be specific to MCKDs The usability of isoforrn proteins encoded by variants as surface markers is chronic. to produce new treatment approaches in inflammation, autoimmune diseases and cancer. will also provide opportunities.
Bulusla Ilgili Teknigin Bilinen Durumu (Önceki Teknik) Miyeloid kökenli baskilayici hücrelerin (MKBH) kanser hastalarinda kesfedilmcsinin üzerinden yaklasik 20 yil geçmesine ragmen, bu hücrelerin immün sistemdeki fonksiyonel önemi henüz açikliga kavusturulamamistir. Yapilan çalismalarda alinan sonuçlar, MKBH popülasyonunun kanser ve diger hastaliklarda immün sistemin negatif regülasyonunda rol aldigini desteklemektedir. State of the Art of the Invention (Prior Art) Detection of myeloid-derived suppressor cells (MSD) in cancer patients Although approximately 20 years have passed since its importance has not yet been clarified. The results obtained in the studies, MKBH role in negative regulation of the immune system in cancer and other diseases supports it.
MKBH popülasyonlarinin ortak özellikleri miyeloid kökenli olmalari, henüz olgunlasmis olmasalar da patolojik aktivasyon geçirmeleri ve T hücrelerini baskilamadaki dikkate deger kapasiteleridir. Arastirmacilar farkli hastaliklarda çesitli MKBH alt-gruplari tanimlamis olsalar da tanimlanan MKBH popülasyonlarinin karakterizasyonunda kullanilan yöntem ve tekniksel farkliliklar sebebiyle yürütülen çalismalarin genel kabul görmesi çogu kez söz konusu olmamaktadir. MKBH popülasyonuna özgül biyobelirteçlerin henüz kesfedilmemis olmasi, MKBH biyolojisi arastirmalarinda yasanan güven probleminin temelini olusturmaktadir. ve HLA-DR yüzey belirteçlerinin farkli kombinasyonlari kullanilmaktadir. CDllb, CD33 ve lL-4Ra genel MKBH popülasyonunu tespit etmek için kullanilirken; bu üç belirteç yaninda CDl4-CD16 düsük VGFRI +HLA-DR- G-MKBH ve CD15+/-CD16-CD66b+/-VGFRl-HLA- DR düsük M-MKBH alt-tipleri olarak kabul edilmektedir. The common features of MCKD populations are that they are of myeloid origin, they are not yet mature. Although they are not, they are notable for their pathological activation and suppression of T cells. their capacities. Researchers have identified various subgroups of MCKD in different diseases. methods used to characterize identified MCKD populations, and It is often mentioned that the studies carried out due to technical differences are generally accepted. is not the subject. Biomarkers specific to the MCKD population have yet to be discovered. The fact that it is present underlies the trust problem experienced in MCKD biology research. forms. and different combinations of HLA-DR surface markers are used. CDllb, CD33 and IL-4Ra is used to detect the general MCKD population; next to these three markers CD14-CD16 low VGFRI +HLA-DR- G-MCKD and CD15+/-CD16-CD66b+/-VGFR1-HLA- DR are considered low M-MDG subtypes.
Son dönemde yapilan çok renkli immünfenotiplendirme çalismalarinda ise, insanda alti farkli MKBH alt-tipi [MKBHI, CDI4+IL-4Roc+; MKBHZ, CD15+IL-4Ra+; MKBH3, Lin- (CD3, MKBHS, CDllb+CDl4-CD15+ ve MKBH6, CD15+FSC düsük SSC yüksek] bulunduguna dair veriler sunulmustur. Bu belirteçlere ek olarak, yaklasik 32 adet farkli yüzey molekülünün de MKBH fenotipi ile iliskili olabilecegine dair yayinlar mevcuttur. In the recent multicolor immunophenotyping studies, six different types of human MCKD subtype [MKBHI, CDI4+IL-4Roc+; MKBHZ, CD15+IL-4Ra+; MKBH3, Lin- (CD3, MKBHS, CDllb+CD14-CD15+ and MKBH6, CD15+FSC low SSC high] data are presented. In addition to these markers, there are approximately 32 different surface molecules. There are also publications indicating that it may be associated with the MCKD phenotype.
Bugüne dek yapilan çalismalarda çesitli miyeloid regülatör hücresi alt-tipleri tanimlanmis olsa da miyeloid regülatör hücreleri üç ana alt-tip olmak üzere: granülositik MKBH (veya polimorfonükleer (PMN)-MKBH), monositik MKBH ve erken-evre MKBH popülasyonlarindan olusmaktadir. Arastirmacilarin ortak bir konsorsiyumla bu üç ana popülasyon için kullandigi immünfenotipik siniflandirma ise su sekildedir: o CDllb+ CD 14' CD66b+veya CD1 lb+ CD 14' CD15+ granülositik MKBH popülasyonu . CDiib+ CD14+ HLA-DR-fdüsük CD66b' monositik MKBH popülasyonu (mMKBH), popülasyonunu (eMKBH) göstermektedir. adayi olarak sunulan OLR-l (LOX-l) (lectin-type oxidized LDL receptor-l) proteininin, MKBH populasyonlarindan olan gMKBH veya PMN-MKBH olarak adlandirilan bir alt populasyonu belirlemede kullanilabilecegi söylenmektedir. Fakat OLR-'l proteininin gMKBH biyobelirteci olarak kullanilabilirligi miyeloid hücre çalismasi yürüten diger ekiplerce yeterli düzeyde destek bulamamis, yapilan çalismalarda farkli sonuclar alinmasi sebebiyle tutarsiz bulunmustur. Özellikle tümör mikroçevresinde bulunan gMKBH populasyonunun OLR-l proteinini heterojen olarak ifade etmesi sebebiyle, OLR-l proteininin yalnizca gMKBH popülasyonuna ait bir alt grup tarafindan ifade edildigi sonucuna varilmis ve diger polimorfonükleer hücrelerce de ifadesinin söz konusu oldugu tespit edilmistir. Bu sebeple, OLR- 1 ”in gMKBH veya PMN-MKBH olarak adlandirilan MKBH alt popülasyonuna özgü bir belirteç olmadigi anlasilmistir. Although various myeloid regulator cell subtypes have been described in studies to date, myeloid regulator cells in three main subtypes: granulocytic MCKD (or polymorphonuclear (PMN)-MBD), monocytic MCKD and early-stage MCKD consists of populations. With a joint consortium of researchers, these three main The immunophenotypic classification used for the population is as follows: o CDllb+ CD 14' CD66b+ or CD1 lb+ CD 14' CD15+ granulocytic MCKD population . CDiib+ CD14+ HLA-DR-flow CD66b' monocytic MCKD population (mMCKD), population (eMKBD). OLR-l (LOX-l) (lectin-type oxidized LDL receptor-l) protein presented as a candidate, A subgroup of MCKD populations called mMCKD or PMN-MCD It is said that it can be used to determine the population. But the OLR-'l protein's gMKBD Its usability as a biomarker is sufficient by other teams carrying out myeloid cell studies. level of support, inconsistent due to different results in studies. has been found. In particular, OLR-l of the gMCKD population in the tumor microenvironment Because it expresses the protein heterogeneously, the OLR-1 protein can only be found in gMCKD. It was concluded that it was expressed by a subgroup belonging to the It has been determined that it is also expressed by polymorphonuclear cells. Therefore, A specific MCKD subpopulation of OLR-1 called gMCKD or PMN-MCD It is understood that it is not an indicator.
EP2619585B1 numarali patent dokümaninda miyeloid hücre biyobelirteçlerinin renal hücre karsinomunun (RCC) ve kolorektal kanserlerlerin (CRC) belirlenmesinde, öngörüsünde ve takibinde kullanilmasindan bahsedilmektedir. MKBH fenotip 5”e özgü belirteçler (CDllb, CD14, CD15. CDSO, CD83, CD86 ve HLA-DR), MKBH 5 popülasyonunu diger popülasyonlardan akis sitometrisi araciligiyla ayirinada kullanilmaktadir. In the patent document numbered EP2619585B1, myeloid cell biomarkers were determined by renal cell cancer (RCC) and colorectal cancers (CRC) detection, prediction and It is mentioned to be used in follow-up. Markers specific to MCKD phenotype 5 (CDllb, CD14, CD15. CDSO, CD83, CD86 and HLA-DR), MCKD 5 population It is also used to separate populations by means of flow cytometry.
MKBH alt-tipi [MKBHI, CDI4+IL-4Roc+; MKBHZ, CD15+IL-4Ra+; MKBH3, Lin- (CD3, MKBHS, CDllb+CDl4-CD15+ ve MKBH6, CD15+FSC düsük SSC yüksek] bulunduguna dair veriler sunulmustur. Bu belirteçlere ek olarak, yaklasik 32 adet farkli yüzey molekülünün de MKBH fenotipi ile iliskili olabilecegine dair yayinlar mevcuttur. MCKD subtype [MKBHI, CDI4+IL-4Roc+; MKBHZ, CD15+IL-4Ra+; MKBH3, Lin- (CD3, MKBHS, CDllb+CD14-CD15+ and MKBH6, CD15+FSC low SSC high] data are presented. In addition to these markers, there are approximately 32 different surface molecules. There are also publications indicating that it may be associated with the MCKD phenotype.
Bugüne dek yapilan çalismalarda çesitli miyeloid regülatör hücresi alt-tipleri tanimlanmis olsa da miyeloid regülatör hücreleri üç ana alt-tip olmak üzere: granülositik MKBH (veya polimorfonükleer (PMN)-MKBH), monositik MKBH ve erken-evre MKBH popülasyonlarindan olusmaktadir. Arastirmacilarin ortak bir konsorsiyumla bu üç ana popülasyon için kullandigi immünfenotipik siniflandirma ise su sekildedir: o CDllb+ CD 14' CD66b+veya CD1 lb+ CD 14' CD15+ granülositik MKBH popülasyonu . CDiib+ CD14+ HLA-DR-fdüsük CD66b' monositik MKBH popülasyonu (mMKBH), popülasyonunu (eMKBH) göstermektedir. adayi olarak sunulan OLR-l (LOX-l) (lectin-type oxidized LDL receptor-l) proteininin, MKBH populasyonlarindan olan gMKBH veya PMN-MKBH olarak adlandirilan bir alt populasyonu belirlemede kullanilabilecegi söylenmektedir. Fakat OLR-'l proteininin gMKBH biyobelirteci olarak kullanilabilirligi miyeloid hücre çalismasi yürüten diger ekiplerce yeterli düzeyde destek bulamamis, yapilan çalismalarda farkli sonuclar alinmasi sebebiyle tutarsiz bulunmustur. Özellikle tümör mikroçevresinde bulunan gMKBH populasyonunun OLR-l proteinini heterojen olarak ifade etmesi sebebiyle, OLR-l proteininin yalnizca gMKBH popülasyonuna ait bir alt grup tarafindan ifade edildigi sonucuna varilmis ve diger polimorfonükleer hücrelerce de ifadesinin söz konusu oldugu tespit edilmistir. Bu sebeple, OLR- 1 ”in gMKBH veya PMN-MKBH olarak adlandirilan MKBH alt popülasyonuna özgü bir belirteç olmadigi anlasilmistir. Although various myeloid regulator cell subtypes have been described in studies to date, myeloid regulator cells in three main subtypes: granulocytic MCKD (or polymorphonuclear (PMN)-MBD), monocytic MCKD and early-stage MCKD consists of populations. With a joint consortium of researchers, these three main The immunophenotypic classification used for the population is as follows: o CDllb+ CD 14' CD66b+ or CD1 lb+ CD 14' CD15+ granulocytic MCKD population . CDiib+ CD14+ HLA-DR-flow CD66b' monocytic MCKD population (mMCKD), population (eMKBD). OLR-l (LOX-l) (lectin-type oxidized LDL receptor-l) protein presented as a candidate, A subgroup of MCKD populations called mMCKD or PMN-MCD It is said that it can be used to determine the population. But the OLR-'l protein's gMKBD Its usability as a biomarker is sufficient by other teams carrying out myeloid cell studies. level of support, inconsistent due to different results in studies. has been found. In particular, OLR-l of the gMCKD population in the tumor microenvironment Because it expresses the protein heterogeneously, the OLR-1 protein can only be found in gMCKD. It was concluded that it was expressed by a subgroup belonging to the It has been determined that it is also expressed by polymorphonuclear cells. Therefore, A specific MCKD subpopulation of OLR-1 called gMCKD or PMN-MCD It is understood that it is not an indicator.
EP2619585B1 numarali patent dokümaninda miyeloid hücre biyobelirteçlerinin renal hücre karsinomunun (RCC) ve kolorektal kanserlerlerin (CRC) belirlenmesinde, öngörüsünde ve takibinde kullanilmasindan bahsedilmektedir. MKBH fenotip 5”e özgü belirteçler (CDllb, CD14, CD15. CDSO, CD83, CD86 ve HLA-DR), MKBH 5 popülasyonunu diger popülasyonlardan akis sitometrisi araciligiyla ayirinada kullanilmaktadir. In the patent document numbered EP2619585B1, myeloid cell biomarkers were determined by renal cell cancer (RCC) and colorectal cancers (CRC) detection, prediction and It is mentioned to be used in follow-up. Markers specific to MCKD phenotype 5 (CDllb, CD14, CD15. CDSO, CD83, CD86 and HLA-DR), MCKD 5 population It is also used to separate populations by means of flow cytometry.
MKBH popülasyonlarini isaretlemede kullanilan belirteçler ve uygulanan stratejilerden bahsedilen baska bir dökümanda da benzer sekilde MKBH popülasyonlarini akis sitometrisi araciligiyla ayirmada kullanilacak belirteçlerden söz edilmektedir. Bu dökümanin ana hattini, MKBH popülasyonlarina özgü belirteçlerin henüz kesfedilmemis olmasi sebebiyle, MKBH biyolojisi çalismalarinda yürütülecek strateji olusturmaktadir. Dokümanda da bahsedildigi sekilde, önerilen belirteç kombinasyonlarinin akis sitemetrisinde kullanilmasinin yaninda fonksiyonel, biyokimyasal ve moleküler testlerin MKBH popülasyonlarini dogrulamak için kaçinilmaz oldugu sunucuna varilmaktadir. Önceki tekniklerde belirtilen hücre yüzey belirteçlerinin normal miyeloid hücre farklilasmasi, olgunlasmasi veya aktivasyon süreçleri sirasinda da çesitli düzeylerde ve/veya geçici süreyle tasindigi bilininektedir. Bu nedenle, MKBH'ler tanimlanirken kullanilan yüzey belirteçlerine ek olarak, immün-baskilayici fonksiyonlarinin da hemen her zaman gösterilmesi gerekmektedir. Kanser gibi kisiden kisiye farkliliklar gösteren inflamatuvar hastaliklarin iminün sistem üzerindeki etkisi göz önünde bulundumldugunda, bu miyeloid düzenleyici hücrelerin dogru ve güvenilir sekilde tanimlanmasi için standardizasyon çalismalarinin önemi vurgulanmaktadir. Markers used and strategies used to mark MCKD populations Similarly, in another document mentioned, flow cytometry of MCKD populations It is mentioned about the markers to be used in the separation. The outline of this document, Because markers specific to MCKD populations have yet to be discovered, MCKD constitutes the strategy to be carried out in biology studies. Also mentioned in the document In the figure, besides the use of suggested combinations of indicators in flow cytometry, functional, biochemical, and molecular tests to confirm MCKD populations It is inevitable that the server is reached. Normal myeloid cell differentiation of cell surface markers indicated in prior art, at various levels and/or temporarily during maturation or activation processes. is known to have been carried. Therefore, the surface markers used in identifying MCKDs in addition, immunosuppressive functions are almost always demonstrated required. Inflammatory diseases that differ from person to person, such as cancer Considering the effect of imine on the system, this myeloid regulator The importance of standardization studies for accurate and reliable identification of cells is emphasized.
Immün hücrelerin geçirdigi farklilasma, olgunlasma ve aktivasyon süreçleri sonucunda biyolojik davranislari ve gen ekspresyon profilleri degisir. Gen ifadelenmesi ile sentezlenen öncül mRNA, çesitli mekanizmalar araciligi ile islenerek protein kodlayabilecek olgunluga ulastirilir. Bu asamada post-transkripsiyonel "alternatif kirpilma" (alternative splicing) mekanizmalari devreye girer ve ilgili proteinin bazi birimlerini tasimayan farkli uzunluktaki izoformlari sentezlenir. Eger gen bölgesi içerisinde yer aliyorsa, "alternatif transkripsiyon baslangiç bölgeleri"nin kullanilmasi da farkli varyantlarin üretilmesine neden olan diger bir mekanizmadir. As a result of differentiation, maturation and activation processes of immune cells their biological behavior and gene expression profiles change. Synthesized by gene expression The precursor mRNA is processed through various mechanisms to reach maturity to code for proteins. is delivered. At this stage, post-transcriptional "alternative splicing" mechanisms come into play and different lengths of protein do not carry some units of the relevant protein. isoforms are synthesized. If located within the gene region, "alternative transcription The use of "starter regions" is another factor that causes different variants to be produced. is the mechanism.
Bazi proteinlerin izoformlari arasinda fonksiyonel farkliliklar oldugu bilinirken; çogu proteine ait izoforrnlarin fonksiyonu ve ekspresyon dinamigi hakkindaki bilgiler sinirlidir. Miyeloid hücrelerde alternatif transkripsiyon mekanizmalarinin önemine dair sinirli sayida çalisma mevcuttur. Dahasi, insan MKBH'lerinin bulundugu farklilasma, olgunlasma ve aktivasyon basamaklarinda bu hücrelere ait yüzey belirteçlerinin hangi transkript varyantlari tarafindan kodlandigina dair bilgiye literatürde rastlanmamistir. While it is known that there are functional differences between the isoforms of some proteins; to most proteins Information on the function and expression dynamics of the isoforrns is limited. myeloid Limited number of studies on the importance of alternative transcription mechanisms in cells available. Moreover, differentiation, maturation, and activation of human MCKDs by which transcript variants of the surface markers of these cells There is no information about the coding in the literature.
Bulusun Kisa Açiklamasi Bulusta öncelikle, MKBH'lerin belirleninesi için siklikla kullanilan, tutarlilik veya MKBH popülasyonlarini isaretlemede kullanilan belirteçler ve uygulanan stratejilerden bahsedilen baska bir dökümanda da benzer sekilde MKBH popülasyonlarini akis sitometrisi araciligiyla ayirmada kullanilacak belirteçlerden söz edilmektedir. Bu dökümanin ana hattini, MKBH popülasyonlarina özgü belirteçlerin henüz kesfedilmemis olmasi sebebiyle, MKBH biyolojisi çalismalarinda yürütülecek strateji olusturmaktadir. Dokümanda da bahsedildigi sekilde, önerilen belirteç kombinasyonlarinin akis sitemetrisinde kullanilmasinin yaninda fonksiyonel, biyokimyasal ve moleküler testlerin MKBH popülasyonlarini dogrulamak için kaçinilmaz oldugu sunucuna varilmaktadir. Önceki tekniklerde belirtilen hücre yüzey belirteçlerinin normal miyeloid hücre farklilasmasi, olgunlasmasi veya aktivasyon süreçleri sirasinda da çesitli düzeylerde ve/veya geçici süreyle tasindigi bilininektedir. Bu nedenle, MKBH'ler tanimlanirken kullanilan yüzey belirteçlerine ek olarak, immün-baskilayici fonksiyonlarinin da hemen her zaman gösterilmesi gerekmektedir. Kanser gibi kisiden kisiye farkliliklar gösteren inflamatuvar hastaliklarin iminün sistem üzerindeki etkisi göz önünde bulundumldugunda, bu miyeloid düzenleyici hücrelerin dogru ve güvenilir sekilde tanimlanmasi için standardizasyon çalismalarinin önemi vurgulanmaktadir. Brief Description of the Invention The invention primarily focuses on consistency or Markers used and strategies used to mark MCKD populations Similarly, in another document mentioned, flow cytometry of MCKD populations It is mentioned about the markers to be used in the separation. The outline of this document, Because markers specific to MCKD populations have yet to be discovered, MCKD constitutes the strategy to be carried out in biology studies. Also mentioned in the document In the figure, besides the use of suggested combinations of indicators in flow cytometry, functional, biochemical, and molecular tests to confirm MCKD populations It is inevitable that the server is reached. Normal myeloid cell differentiation of cell surface markers indicated in prior art, at various levels and/or temporarily during maturation or activation processes. is known to have been carried. Therefore, the surface markers used in identifying MCKDs in addition, immunosuppressive functions are almost always demonstrated required. Inflammatory diseases that differ from person to person, such as cancer Considering the effect of imine on the system, this myeloid regulator The importance of standardization studies for accurate and reliable identification of cells is emphasized.
Immün hücrelerin geçirdigi farklilasma, olgunlasma ve aktivasyon süreçleri sonucunda biyolojik davranislari ve gen ekspresyon profilleri degisir. Gen ifadelenmesi ile sentezlenen öncül mRNA, çesitli mekanizmalar araciligi ile islenerek protein kodlayabilecek olgunluga ulastirilir. Bu asamada post-transkripsiyonel "alternatif kirpilma" (alternative splicing) mekanizmalari devreye girer ve ilgili proteinin bazi birimlerini tasimayan farkli uzunluktaki izoformlari sentezlenir. Eger gen bölgesi içerisinde yer aliyorsa, "alternatif transkripsiyon baslangiç bölgeleri"nin kullanilmasi da farkli varyantlarin üretilmesine neden olan diger bir mekanizmadir. As a result of differentiation, maturation and activation processes of immune cells their biological behavior and gene expression profiles change. Synthesized by gene expression The precursor mRNA is processed through various mechanisms to reach maturity to code for proteins. is delivered. At this stage, post-transcriptional "alternative splicing" mechanisms come into play and different lengths of protein do not carry some units of the relevant protein. isoforms are synthesized. If located within the gene region, "alternative transcription The use of "starter regions" is another factor that causes different variants to be produced. is the mechanism.
Bazi proteinlerin izoformlari arasinda fonksiyonel farkliliklar oldugu bilinirken; çogu proteine ait izoforrnlarin fonksiyonu ve ekspresyon dinamigi hakkindaki bilgiler sinirlidir. Miyeloid hücrelerde alternatif transkripsiyon mekanizmalarinin önemine dair sinirli sayida çalisma mevcuttur. Dahasi, insan MKBH'lerinin bulundugu farklilasma, olgunlasma ve aktivasyon basamaklarinda bu hücrelere ait yüzey belirteçlerinin hangi transkript varyantlari tarafindan kodlandigina dair bilgiye literatürde rastlanmamistir. While it is known that there are functional differences between the isoforms of some proteins; to most proteins Information on the function and expression dynamics of the isoforrns is limited. myeloid Limited number of studies on the importance of alternative transcription mechanisms in cells available. Moreover, differentiation, maturation, and activation of human MCKDs by which transcript variants of the surface markers of these cells There is no information about the coding in the literature.
Bulusun Kisa Açiklamasi Bulusta öncelikle, MKBH'lerin belirleninesi için siklikla kullanilan, tutarlilik veya güvenilirlik problemi tasiyan yüzey moleküllerinin yerini alabilecek özgüllükte biyobelirteç adaylarinin ortaya çikartilabilmesi için gMKBH yüzeyinde bulundugu bilinen yüzey moleküllerinin transkript varyantlari gerçek-zamanli PZR yöntemiyle taranmaktadir. Brief Description of the Invention The invention primarily focuses on consistency or A specific biomarker that can replace surface molecules with reliability problems surface known to be present on the gMKBH surface in order to reveal the candidates The transcript variants of the molecules are screened by real-time PCR method.
Taranan varyantlardan, farklilik gösterdigi tespit edilen transkript varyantlari tarafindan kodlanan protein izoformlarinin, MKBH'lerin takibi ve/veya hedeflenmesi için yeni ve özgün moleküller olarak kullanilabilecegi gösterilmektedir. Bulus ile, CDld tv2, CD44 tvl ve CD44 tv2 varyantlarinin monosit popülasyonu içinde dagilan eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olabilecekleri; CD33 tv2, CDld tvl, CD16 tvl, CD16 tv2 ve CD16 tv3 transkript varyantlarinin ise gMKBH popülasyonlanna özgü biyobelirteçler olabilecekleri gösterilmektedir. By transcript variants found to differ from the variants screened Novel and novel encoded protein isoforms for tracking and/or targeting MCKDs shown to be used as molecules. With the invention, CDld tv2, CD44 tvl and CD44 mMCD and/or mMCD distributed within the monocyte population of tv2 variants they may be biomarkers specific to their populations; CD33 tv2, CDld tvl, CD16 tvl, CD16 On the other hand, tv2 and CD16 tv3 transcript variants are biomarkers specific to gMCKD populations. possible are shown.
MKBH'lere özgü oldugu belirlenen transkript varyantlarinin kodladigi izoform proteinlerin yüzey belirteci olarak kullanilabilirligi kronik enflamasyon, otoimmün hastaliklar ve kanserde yeni tedavi yaklasimlarinin üretilebilmesine de olanak saglayacaktir. Isoform proteins encoded by transcript variants determined to be specific to MCKDs Usability as a surface marker in chronic inflammation, autoimmune diseases and cancer It will also enable the production of new treatment approaches.
Bulusun diger çalismalardan ve patentlerden en büyük farki, MKBH popülasyonlarinin varyant spesifik bir belirteçle taninmasinin saglanabilecek olmasidir. Bulusta MKBH hücrelerine özgü belirteçlerin varyant farkliliklari temel alinmaktadir. Kisaca açiklayacak olursak, örnegin A geninin 3 adet transcript varyanti var: A1, A2 ve A3; bu 3 varyant A genine ait 3 protein isoformu kodlar: AP1, AP2 ve AP3; MKBH hücreleri ayni genin kodlanan proteinlerini (örnegimizdeki API, AP2 ve AP3) yüzeylerinde bulundururlar, Piyasada bulunan antikorlar A geninin tüm protein izofornilarini ayni anda tanir, yani örnegimizdeki APl, AP2 ve AP3 proteinleri ayri ayri görülemez. Eger MKBH populasyonunda AP] çok artmis ve diger hücre gruplarinda AP3 çok artmis ise, piyasada bulunan antikorlar bunu teshis edemez. Önceki teknikte mevcut olan çalismalar, bu ayrimi yapmadan, bir proteinin tüm isoformlarini bir tutarak, sadece stratejik yaklasimlarla MKBH populasyonu olabilecek hücreleri ayirabilmektedir. Ancak bulus “miyeloid kökenli baskilayici hücrelere özgü biyobelirteç paneli”, yalnizca spesifik transkript varyantlarinin kodladigi yüzey proteinlerini baz alarak MKBH popülasyonlarini karakterize edebilmektedir. The major difference of the invention from other studies and patents is that MCKD populations variant can be recognized with a specific marker. MKBH in the invention It is based on variant differences of markers specific to cells. Will briefly explain For example, the A gene has 3 transcript variants: A1, A2 and A3; these 3 variants A encodes 3 protein isoforms of the gene: AP1, AP2 and AP3; MCKD cells of the same gene they have their encoded proteins (API, AP2 and AP3 in our example) on their surface, Commercially available antibodies recognize all protein isophorns of the A gene simultaneously, i.e. The AP1, AP2 and AP3 proteins in our sample cannot be seen separately. If MKBH If AP] is very high in the population and AP3 is very high in other cell groups, the market Antibodies found cannot detect it. Studies available in the prior art have made this distinction without making a protein, keeping all isoforms of a protein together, only with strategic approaches It can separate cells that may be a population. However, the invention “suppressor of myeloid origin” “cell-specific biomarker panel”, encoded only by specific transcript variants characterize MCKD populations based on surface proteins.
Bulusu Açiklayan Sekillerin Tanimlari Sekil 1: Kolorektal kanserde (KRK) saglikli kisilere kiyasla transkript varyant ekspresyonunun yüzdelik oranda farki. Description of Figures Explaining the Invention Figure 1: Transcript variant in colorectal cancer (CRC) compared to healthy subjects percent difference in expression.
Sekil 2: Meme kanserinde (MK) saglikli kisilere kiyasla transkript varyant ekspresyonunun yüzdelik oranda farki. güvenilirlik problemi tasiyan yüzey moleküllerinin yerini alabilecek özgüllükte biyobelirteç adaylarinin ortaya çikartilabilmesi için gMKBH yüzeyinde bulundugu bilinen yüzey moleküllerinin transkript varyantlari gerçek-zamanli PZR yöntemiyle taranmaktadir. Figure 2: Transcript variant expression in breast cancer (BC) compared to healthy subjects percent difference. A specific biomarker that can replace surface molecules with reliability problems surface known to be present on the gMKBH surface in order to reveal the candidates The transcript variants of the molecules are screened by real-time PCR method.
Taranan varyantlardan, farklilik gösterdigi tespit edilen transkript varyantlari tarafindan kodlanan protein izoformlarinin, MKBH'lerin takibi ve/veya hedeflenmesi için yeni ve özgün moleküller olarak kullanilabilecegi gösterilmektedir. Bulus ile, CDld tv2, CD44 tvl ve CD44 tv2 varyantlarinin monosit popülasyonu içinde dagilan eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olabilecekleri; CD33 tv2, CDld tvl, CD16 tvl, CD16 tv2 ve CD16 tv3 transkript varyantlarinin ise gMKBH popülasyonlanna özgü biyobelirteçler olabilecekleri gösterilmektedir. By transcript variants found to differ from the variants screened Novel and novel encoded protein isoforms for tracking and/or targeting MCKDs shown to be used as molecules. With the invention, CDld tv2, CD44 tvl and CD44 mMCD and/or mMCD distributed within the monocyte population of tv2 variants they may be biomarkers specific to their populations; CD33 tv2, CDld tvl, CD16 tvl, CD16 On the other hand, tv2 and CD16 tv3 transcript variants are biomarkers specific to gMCKD populations. possible are shown.
MKBH'lere özgü oldugu belirlenen transkript varyantlarinin kodladigi izoform proteinlerin yüzey belirteci olarak kullanilabilirligi kronik enflamasyon, otoimmün hastaliklar ve kanserde yeni tedavi yaklasimlarinin üretilebilmesine de olanak saglayacaktir. Isoform proteins encoded by transcript variants determined to be specific to MCKDs Usability as a surface marker in chronic inflammation, autoimmune diseases and cancer It will also enable the production of new treatment approaches.
Bulusun diger çalismalardan ve patentlerden en büyük farki, MKBH popülasyonlarinin varyant spesifik bir belirteçle taninmasinin saglanabilecek olmasidir. Bulusta MKBH hücrelerine özgü belirteçlerin varyant farkliliklari temel alinmaktadir. Kisaca açiklayacak olursak, örnegin A geninin 3 adet transcript varyanti var: A1, A2 ve A3; bu 3 varyant A genine ait 3 protein isoformu kodlar: AP1, AP2 ve AP3; MKBH hücreleri ayni genin kodlanan proteinlerini (örnegimizdeki API, AP2 ve AP3) yüzeylerinde bulundururlar, Piyasada bulunan antikorlar A geninin tüm protein izofornilarini ayni anda tanir, yani örnegimizdeki APl, AP2 ve AP3 proteinleri ayri ayri görülemez. Eger MKBH populasyonunda AP] çok artmis ve diger hücre gruplarinda AP3 çok artmis ise, piyasada bulunan antikorlar bunu teshis edemez. Önceki teknikte mevcut olan çalismalar, bu ayrimi yapmadan, bir proteinin tüm isoformlarini bir tutarak, sadece stratejik yaklasimlarla MKBH populasyonu olabilecek hücreleri ayirabilmektedir. Ancak bulus “miyeloid kökenli baskilayici hücrelere özgü biyobelirteç paneli”, yalnizca spesifik transkript varyantlarinin kodladigi yüzey proteinlerini baz alarak MKBH popülasyonlarini karakterize edebilmektedir. The major difference of the invention from other studies and patents is that MCKD populations variant can be recognized with a specific marker. MKBH in the invention It is based on variant differences of markers specific to cells. Will briefly explain For example, the A gene has 3 transcript variants: A1, A2 and A3; these 3 variants A encodes 3 protein isoforms of the gene: AP1, AP2 and AP3; MCKD cells of the same gene they have their encoded proteins (API, AP2 and AP3 in our example) on their surface, Commercially available antibodies recognize all protein isophorns of the A gene simultaneously, i.e. The AP1, AP2 and AP3 proteins in our sample cannot be seen separately. If MKBH If AP] is very high in the population and AP3 is very high in other cell groups, the market Antibodies found cannot detect it. Studies available in the prior art have made this distinction without making a protein, keeping all isoforms of a protein together, only with strategic approaches It can separate cells that may be a population. However, the invention “suppressor of myeloid origin” “cell-specific biomarker panel”, encoded only by specific transcript variants characterize MCKD populations based on surface proteins.
Bulusu Açiklayan Sekillerin Tanimlari Sekil 1: Kolorektal kanserde (KRK) saglikli kisilere kiyasla transkript varyant ekspresyonunun yüzdelik oranda farki. Description of Figures Explaining the Invention Figure 1: Transcript variant in colorectal cancer (CRC) compared to healthy subjects percent difference in expression.
Sekil 2: Meme kanserinde (MK) saglikli kisilere kiyasla transkript varyant ekspresyonunun yüzdelik oranda farki. Figure 2: Transcript variant expression in breast cancer (BC) compared to healthy subjects percent difference.
Sekil 3: Transkript varyant ekspresyonunun gMKBH popülasyonunda saglikli ve hasta PMN popülasyonlarina kiyasla yüzdelik farki. Figure 3: Transcript variant expression of healthy and sick PMN in the gMCKD population percent difference compared to their population.
Sekil 4: gMKBH popülasyonunu belirlemede kullanilabilecek aday protein varyantlarinin Kolaskar ve Tongaonkar yöntemi ile saptanan antijenisite skor grafikleri. Figure 4: Candidate protein variants that can be used to identify the gMCKD population Antigenicity score graphs determined by Kolaskar and Tongaonkar method.
Bulusu Tanimlayan Unsurlar/Parçalar Bulusun Ayrintili Açiklamasi Bulus ile öncelikle farkli çalismalarda MKBH'ler tarafindan tasinabilecegi gösterilen toplam L1(CD, C5AR1, VEGF R2, CD2, lTGAl, lTGA2, ITGA3, ITGAS, ve CD31) gen dizileri ve transkript varyantlarina (tv) ait ekson ve olgun mRNA dizileri Amerika Birlesik Devletleri National Center for Biotechnology Information (NCBI) - GenBank ve Nucleotide; ve ENSEMBL (European Bioinformatics Institute, Wellcome Trust Sanger Institute) veri bankalarinda kayitli referans nükleotid dizileri kullanilarak belirlenmektedir. Elements/Parts Defining the Invention Detailed Description of the Invention With the invention, first of all, the total amount shown to be carried by MCKDs in different studies L1(CD, C5AR1, VEGF R2, CD2, lTGAl, lTGA2, ITGA3, ITGAS, and CD31) gene sequences and transcript Exon and mature mRNA sequences of variants (tv) United States National Center for Biotechnology Information (NCBI) - GenBank and Nucleotide; and ENSEMB (European Bioinformatics Institute, Wellcome Trust Sanger Institute) data banks determined using registered reference nucleotide sequences.
Bulusun esas amaci MKBH'leri tanimlamaya yönelik transkript varyantlari tarafindan kodlanabileeek yeni hücre yüzey antijenlerinin belirlenmesi oldugundan, ilgili transkript varyantlarinin proteinin hücre-disi (ekstrasellüler) bölgesinde degisiklik göstermesi de öncelik kriteri olarak alinmaktadir. The main object of the invention is to identify MCKDs by transcript variants. Since it is the identification of new cell surface antigens that can be encoded, the relevant transcript It is also a priority that variants of the protein vary in the extracellular region of the protein. taken as the criterion.
Primer tasarimi için çevrimiçi Primer-BLAST (NCBI), OligoAnalyzer (Integrated DNA Technologies, ABD), ve çevrimdisi FastPCR (Primer Digital, Finlandiya) araçlari kullanilir. Online Primer-BLAST (NCBI), OligoAnalyzer (Integrated DNA) for primer design Technologies, USA), and offline FastPCR (Primer Digital, Finland) tools are used.
Varyant sekanslarinin analizinde çevrimiçi Clustal Omega çoklu sekans siralayici (The European Bioinformatics Institute, Ingiltere) araci kullanilir. Varyantlara özgül primerlerin tasarlanmasi sirasinda kullanilan tasarim algoritmasi: i. Primerlerden en az birinin ekzon-ekzon birlesme yerinde olmasi, ii. Ekzon-ekzon birlesme yerine baglanacak primerin 5' ucunun en az 7 bp ve 3'-ucunun en az 4 bp eslesme Olacak sekilde birlesme yerindeki iki ekzonun da üzerine konumlanmasi, iii. Primer uzunlugunun 18-22 bp arasinda olmasi, Sekil 3: Transkript varyant ekspresyonunun gMKBH popülasyonunda saglikli ve hasta PMN popülasyonlarina kiyasla yüzdelik farki. The online Clustal Omega multiple sequence sorter (The European Bioinformatics Institute, UK) tool is used. variant-specific primers The design algorithm used during the design: I. At least one of the primers is at the exon-exon junction, ii. At least 7 bp of the 5' end and at least 7 bp of the 3'-end of the primer to be attached to the exon-exon junction. Positioning on both exons at the junction with a 4 bp match, iii. Primer length is between 18-22 bp, Figure 3: Transcript variant expression of healthy and sick PMN in the gMCKD population percent difference compared to their population.
Sekil 4: gMKBH popülasyonunu belirlemede kullanilabilecek aday protein varyantlarinin Kolaskar ve Tongaonkar yöntemi ile saptanan antijenisite skor grafikleri. Figure 4: Candidate protein variants that can be used to identify the gMCKD population Antigenicity score graphs determined by Kolaskar and Tongaonkar method.
Bulusu Tanimlayan Unsurlar/Parçalar Bulusun Ayrintili Açiklamasi Bulus ile öncelikle farkli çalismalarda MKBH'ler tarafindan tasinabilecegi gösterilen toplam L1(CD, C5AR1, VEGF R2, CD2, lTGAl, lTGA2, ITGA3, ITGAS, ve CD31) gen dizileri ve transkript varyantlarina (tv) ait ekson ve olgun mRNA dizileri Amerika Birlesik Devletleri National Center for Biotechnology Information (NCBI) - GenBank ve Nucleotide; ve ENSEMBL (European Bioinformatics Institute, Wellcome Trust Sanger Institute) veri bankalarinda kayitli referans nükleotid dizileri kullanilarak belirlenmektedir. Elements/Parts Defining the Invention Detailed Description of the Invention With the invention, first of all, the total amount shown to be carried by MCKDs in different studies L1(CD, C5AR1, VEGF R2, CD2, lTGAl, lTGA2, ITGA3, ITGAS, and CD31) gene sequences and transcript Exon and mature mRNA sequences of variants (tv) United States National Center for Biotechnology Information (NCBI) - GenBank and Nucleotide; and ENSEMB (European Bioinformatics Institute, Wellcome Trust Sanger Institute) data banks determined using registered reference nucleotide sequences.
Bulusun esas amaci MKBH'leri tanimlamaya yönelik transkript varyantlari tarafindan kodlanabileeek yeni hücre yüzey antijenlerinin belirlenmesi oldugundan, ilgili transkript varyantlarinin proteinin hücre-disi (ekstrasellüler) bölgesinde degisiklik göstermesi de öncelik kriteri olarak alinmaktadir. The main object of the invention is to identify MCKDs by transcript variants. Since it is the identification of new cell surface antigens that can be encoded, the relevant transcript It is also a priority that variants of the protein vary in the extracellular region of the protein. taken as the criterion.
Primer tasarimi için çevrimiçi Primer-BLAST (NCBI), OligoAnalyzer (Integrated DNA Technologies, ABD), ve çevrimdisi FastPCR (Primer Digital, Finlandiya) araçlari kullanilir. Online Primer-BLAST (NCBI), OligoAnalyzer (Integrated DNA) for primer design Technologies, USA), and offline FastPCR (Primer Digital, Finland) tools are used.
Varyant sekanslarinin analizinde çevrimiçi Clustal Omega çoklu sekans siralayici (The European Bioinformatics Institute, Ingiltere) araci kullanilir. Varyantlara özgül primerlerin tasarlanmasi sirasinda kullanilan tasarim algoritmasi: i. Primerlerden en az birinin ekzon-ekzon birlesme yerinde olmasi, ii. Ekzon-ekzon birlesme yerine baglanacak primerin 5' ucunun en az 7 bp ve 3'-ucunun en az 4 bp eslesme Olacak sekilde birlesme yerindeki iki ekzonun da üzerine konumlanmasi, iii. Primer uzunlugunun 18-22 bp arasinda olmasi, iV. Primer erime sicakliginin (Tm, melting temperature) 57-63°C'de araliginda olmasi ve primer çiftinin erime sicakligi farkinin azami 3°C olmasi, V. Primerdeki GC oraninin %40-60 araliginda olmasi, vi. Sac-tokasi (hairpiri), self-dimer ve çapraz-dimer (cross-dimer) gibi sekonder yapilarin olusmamasi, vii. Di-nükleotid tekrarinin ve ayni nükleotid tekrarinin en çok dört olmasi, iix. Primerin 3'-uounun stabil olmasi ve özgül olmayan baglanmalara neden olmamasi, ix. Amplikon uzunlugunun 70-1000 (optimum 500 hp) araliginda olmasi, x. Primer oligonükleotid dizisinin ekzonun kodlanan bölümüne baglaniyor olmasi, xi. Primerlerin genomik DNA'ya baglanmamasi, olarak kullanilmaktadir. The online Clustal Omega multiple sequence sorter (The European Bioinformatics Institute, UK) tool is used. variant-specific primers The design algorithm used during the design: I. At least one of the primers is at the exon-exon junction, ii. At least 7 bp of the 5' end and at least 7 bp of the 3'-end of the primer to be attached to the exon-exon junction. Positioning on both exons at the junction with a 4 bp match, iii. Primer length is between 18-22 bp, IV. Primary melting temperature (Tm, melting temperature) is in the range of 57-63°C and the difference in melting temperature of the primer pair to be a maximum of 3°C, 40-60% of the GC ratio in the V. Primer to be in range, vi. Secondary structures such as hairpin (hairpiri), self-dimer and cross-dimer (cross-dimer) not occur, vii. Maximum of four di-nucleotide repeats and the same nucleotide repeat, ix. The 3'-loop of the primer is stable and does not cause non-specific binding, ix. Amplicon length is in the range of 70-1000 (optimum 500 hp), x. Binding of the primary oligonucleotide sequence to the encoded portion of the exon, xi. Primers do not bind to genomic DNA is used as
Tablo 1. Çalismada belirlenen miyeloid genlere özgü tasarlanan primer oligonükleotid dizilerine ait bilgiler. iV. Primer erime sicakliginin (Tm, melting temperature) 57-63°C'de araliginda olmasi ve primer çiftinin erime sicakligi farkinin azami 3°C olmasi, V. Primerdeki GC oraninin %40-60 araliginda olmasi, vi. Sac-tokasi (hairpiri), self-dimer ve çapraz-dimer (cross-dimer) gibi sekonder yapilarin olusmamasi, vii. Di-nükleotid tekrarinin ve ayni nükleotid tekrarinin en çok dört olmasi, iix. Primerin 3'-uounun stabil olmasi ve özgül olmayan baglanmalara neden olmamasi, ix. Amplikon uzunlugunun 70-1000 (optimum 500 hp) araliginda olmasi, x. Primer oligonükleotid dizisinin ekzonun kodlanan bölümüne baglaniyor olmasi, xi. Primerlerin genomik DNA'ya baglanmamasi, olarak kullanilmaktadir. Table 1. Primary oligonucleotide designed specific to the myeloid genes identified in the study information about the series. IV. Primary melting temperature (Tm, melting temperature) is in the range of 57-63°C and the difference in melting temperature of the primer pair to be a maximum of 3°C, 40-60% of the GC ratio in the V. Primer to be in range, vi. Secondary structures such as hairpin (hairpiri), self-dimer and cross-dimer (cross-dimer) not occur, vii. Maximum of four di-nucleotide repeats and the same nucleotide repeat, ix. The 3'-loop of the primer is stable and does not cause non-specific binding, ix. Amplicon length is in the range of 70-1000 (optimum 500 hp), x. Binding of the primary oligonucleotide sequence to the encoded portion of the exon, xi. Primers do not bind to genomic DNA is used as
Tablo 1. Çalismada belirlenen miyeloid genlere özgü tasarlanan primer oligonükleotid dizilerine ait bilgiler. Table 1. Primary oligonucleotide designed specific to the myeloid genes identified in the study information about the series.
Gen Varyant# Sense (5'-3') Anti-sense (5”-3') Urün (hp) GenBank No. Gene Variant# Sense (5'-3') Anti-sense (5”-3') Product (hp) GenBank No.
Gen Varyant# Sense (5'-3') Anti-sense (5”-3') Urün (hp) GenBank No. Gene Variant# Sense (5'-3') Anti-sense (5”-3') Product (hp) GenBank No.
Yapilan analizler sonucunda, 48 genin l7'sinin transkript çesitliligine sahip olmadigi (tek kodlayan mRNA'ya sahip oldugu) belirlenmis ve bu genler hedefler arasindan çikartilmistir. As a result of the analyzes, it was found that 17 of 48 genes did not have transcript diversity (only one encoding mRNA) were determined and these genes were removed from the targets.
CDle geni ise hücre yüzeyinde nadiren bulunmasi ve genellikle hücre-içi organellere yerlesmis olmasi nedeniyle analiz disinda tutulmustur. Geriye kalan 31 MKBH-iliskili genin 108 farkli varyantini birbirinden ayirt edebilecek primer oligonükleotid çiftleri tasarlanmis olup sekanslari, ürün uzunluklari (size) ve GenBank referans numaralari Tablo 17de gösterilmektedir. The CDle gene is rarely found on the cell surface and is usually located in intracellular organelles. It was excluded from the analysis due to its location. Of the remaining 31 MCKD-associated genes Primer oligonucleotide pairs were designed to distinguish 108 different variants from each other. sequences, product lengths (size), and GenBank reference numbers are in Table 17. is shown.
Oligonükleotit çiftlerinin optimum çalisacagi reaksiyon kosullari konvansiyonel PZR ile belirlenektedir. Konvansiyonel PZR ile optimizasyonu yapilan varyantlardan 5 tanesi pozitif kontrol örnegi (testis, beyin, pankreas, ve embriyonik kökenli dokular Vb.) bulunamamasi nedeniyle tam olarak çalisilamamistir. Bunlar ITGAL tv2, LGALSS tv3, Bulusta öncelikle hücre-disi protein bölgelerini kodlayan dizileri açisindan farklilik gösteren 19 genin 70 transkripti degerlendirilmektedir. Hücre-disi protein bölgesinde farklilik gösteren bu 70 transkript konvansiyonel PZR analizi ile kolon kanseri hastalari ve saglikli bireylerden izole edilen toplam miyeloid hücre popülasyonu kaynakli cDNA kaliplari kullanilarak sinanmaktadir. Elde edilen PZR ürünleri jel elektroforez ile görüntülenmektedir. Reaction conditions in which oligonucleotide pairs will work optimally, conventional PCR is determined by. 5 of the variants optimized with conventional PCR positive control sample (testicle, brain, pancreas, and tissues of embryonic origin, etc.) could not be fully studied due to lack of availability. These are ITGAL tv2, LGALSS tv3, The difference in the invention primarily in terms of sequences encoding extracellular protein regions. 70 transcripts of 19 genes showing Difference in extracellular protein region with conventional PCR analysis of these 70 transcripts showing colon cancer patients and healthy cDNA patterns from the total myeloid cell population isolated from individuals tested using The obtained PCR products are visualized by gel electrophoresis.
Kolorektal kanser ve saglikli bireylerin toplam miyeloid hücre popülasyonu kaynakli transkript havuzlarindan edinilen varyant analizi araciligiyla, her iki grupta da ekspresyonu olmayan veya birbirine çok yakin ekspresyon gösterdigi gözlemlenen varyantlar bulus ile olusturulan panelin disinda birakilmistir. From colorectal cancer and the total myeloid cell population of healthy individuals expression in both groups by variant analysis from transcript pools. variants observed to express non-specific or very close expression excluded from the created panel.
Hem hücre-disi protein bölgelerini kodlayan dizileri açisindan farklilik gösteren hem de konvansiyonel PZR verilerine dayanarak saglikliya kiyasla farkli oldugu tespit edilen 47 tvl, tv2, tv4; ADGREl tv2 ve tv5; CDlD tvl ve tv2; ILlRl tvl, tv2, tv6, tv7, WEB ve v9; CD33 tv2 ve tv3) için gerçek zamanli PZR ile ifade düzeyi kiyaslamalari yapilmaktadir (Sekil 1). Sekil 1.`de, kolorektal kanser hastalarinin nötrofil (PMN) ve monosit popülasyonlari saglikli bireylerin nötrofil ve monosit popülasyonlari ile normalize edildigi grafik gösterilmektedir. Grafikte gösterilen tüm varyantlar için hein nötrofil hem de monosit yüzde fark degerleri verilmektedir. Bar grafiklerinin olmadigi kisimlar “0” degerine denk Yapilan analizler sonucunda, 48 genin l7'sinin transkript çesitliligine sahip olmadigi (tek kodlayan mRNA'ya sahip oldugu) belirlenmis ve bu genler hedefler arasindan çikartilmistir. They differ both in sequences encoding extracellular protein regions and Based on conventional PCR data, 47 patients who were found to be different compared to healthy tvl, tv2, tv4; ADGREl tv2 and tv5; CDlD tvl and tv2; ILlRl tvl, tv2, tv6, tv7, WEB and v9; Expression level comparisons are made with real-time PCR for CD33 tv2 and tv3) (Fig. one). In Figure 1., neutrophil (PMN) and monocyte populations of colorectal cancer patients graph in which healthy individuals are normalized by neutrophil and monocyte populations is shown. Hein neutrophil and monocyte percentage for all variants shown in the graph difference values are given. Parts without bar graphs are equivalent to “0” As a result of the analyzes, it was found that 17 of 48 genes did not have transcript diversity (only one encoding mRNA) were determined and these genes were removed from the targets.
CDle geni ise hücre yüzeyinde nadiren bulunmasi ve genellikle hücre-içi organellere yerlesmis olmasi nedeniyle analiz disinda tutulmustur. Geriye kalan 31 MKBH-iliskili genin 108 farkli varyantini birbirinden ayirt edebilecek primer oligonükleotid çiftleri tasarlanmis olup sekanslari, ürün uzunluklari (size) ve GenBank referans numaralari Tablo 17de gösterilmektedir. The CDle gene is rarely found on the cell surface and is usually located in intracellular organelles. It was excluded from the analysis due to its location. Of the remaining 31 MCKD-associated genes Primer oligonucleotide pairs were designed to distinguish 108 different variants from each other. sequences, product lengths (size), and GenBank reference numbers are in Table 17. is shown.
Oligonükleotit çiftlerinin optimum çalisacagi reaksiyon kosullari konvansiyonel PZR ile belirlenektedir. Konvansiyonel PZR ile optimizasyonu yapilan varyantlardan 5 tanesi pozitif kontrol örnegi (testis, beyin, pankreas, ve embriyonik kökenli dokular Vb.) bulunamamasi nedeniyle tam olarak çalisilamamistir. Bunlar ITGAL tv2, LGALSS tv3, Bulusta öncelikle hücre-disi protein bölgelerini kodlayan dizileri açisindan farklilik gösteren 19 genin 70 transkripti degerlendirilmektedir. Hücre-disi protein bölgesinde farklilik gösteren bu 70 transkript konvansiyonel PZR analizi ile kolon kanseri hastalari ve saglikli bireylerden izole edilen toplam miyeloid hücre popülasyonu kaynakli cDNA kaliplari kullanilarak sinanmaktadir. Elde edilen PZR ürünleri jel elektroforez ile görüntülenmektedir. Reaction conditions in which oligonucleotide pairs will work optimally, conventional PCR is determined by. 5 of the variants optimized with conventional PCR positive control sample (testicle, brain, pancreas, and tissues of embryonic origin, etc.) could not be fully studied due to lack of availability. These are ITGAL tv2, LGALSS tv3, The difference in the invention primarily in terms of sequences encoding extracellular protein regions. 70 transcripts of 19 genes showing Difference in extracellular protein region with conventional PCR analysis of these 70 transcripts showing colon cancer patients and healthy cDNA patterns from the total myeloid cell population isolated from individuals tested using The obtained PCR products are visualized by gel electrophoresis.
Kolorektal kanser ve saglikli bireylerin toplam miyeloid hücre popülasyonu kaynakli transkript havuzlarindan edinilen varyant analizi araciligiyla, her iki grupta da ekspresyonu olmayan veya birbirine çok yakin ekspresyon gösterdigi gözlemlenen varyantlar bulus ile olusturulan panelin disinda birakilmistir. From colorectal cancer and the total myeloid cell population of healthy individuals expression in both groups by variant analysis from transcript pools. variants observed to express non-specific or very close expression excluded from the created panel.
Hem hücre-disi protein bölgelerini kodlayan dizileri açisindan farklilik gösteren hem de konvansiyonel PZR verilerine dayanarak saglikliya kiyasla farkli oldugu tespit edilen 47 tvl, tv2, tv4; ADGREl tv2 ve tv5; CDlD tvl ve tv2; ILlRl tvl, tv2, tv6, tv7, WEB ve v9; CD33 tv2 ve tv3) için gerçek zamanli PZR ile ifade düzeyi kiyaslamalari yapilmaktadir (Sekil 1). Sekil 1.`de, kolorektal kanser hastalarinin nötrofil (PMN) ve monosit popülasyonlari saglikli bireylerin nötrofil ve monosit popülasyonlari ile normalize edildigi grafik gösterilmektedir. Grafikte gösterilen tüm varyantlar için hein nötrofil hem de monosit yüzde fark degerleri verilmektedir. Bar grafiklerinin olmadigi kisimlar “0” degerine denk gelmektedir. Bu kiyaslama öncelikle kolorektal kanser ve saglikli bireylerden elde edilen toplam monosit ve PMN hücre kaynakli cDNA'lar kullanilarak yapilmaktadir. They differ both in sequences encoding extracellular protein regions and Based on conventional PCR data, 47 patients who were found to be different compared to healthy tvl, tv2, tv4; ADGREl tv2 and tv5; CDlD tvl and tv2; ILlRl tvl, tv2, tv6, tv7, WEB and v9; Expression level comparisons are made with real-time PCR for CD33 tv2 and tv3) (Fig. one). In Figure 1., neutrophil (PMN) and monocyte populations of colorectal cancer patients graph in which healthy individuals are normalized by neutrophil and monocyte populations is shown. Hein neutrophil and monocyte percentage for all variants shown in the graph difference values are given. Parts without bar graphs are equivalent to “0” is coming. This comparison is primarily based on results obtained from colorectal cancer and healthy individuals. It is performed using cDNAs from total monocytes and PMN cells.
Kolorektal kanser ve saglikli transkript havuzlarinda farklilik gösterdigi tespit edilen 47 tv4; FLTl tv2, tv4; lLlR'l tv6; ILÖST tv2,ADGREl tv5; ve IL4R tv4) meme kanseri toplam monosit ve PMN hücre popülasyonlari kaynakli cDNA ile yapilan gerçek-zamanli PZR ile degerlendirilmektedir (Sekil 2). Sekil 2.°de, meme kanseri (MK) hastalarinin nötrofil ve monosit popülasyonlari saglikli bireylerin PMN ve monosit popülasyonlari ile nonnalize edildigi grafik gösterilmektedir. Meme kanseri PMN popülasyonu için CD16 tvl, tv2, tv3 ve tv6, CEACAM21 tvl, tv2 ve tv4, FLTl tv2 ve tv4, ILlRl tv6 ve ILÖST tv2 varyantlari gösterilmekte; monosit popülasyonu için ise CDld tv2, F LT1 tv2, CD44 tvl ve tv2, ADGREI tv5 ve IL4R tv4 varyantlari gösterilmektedir. Hem monosit hem de PMN örneklerinde yalnizca CDld tv2 gösterilmektedir. PMN için gösterilen FLTl tv4 için ifade farki bulunmadigindan dolayi “0” degerine denk gelmektedir. 47 that were found to differ in colorectal cancer and healthy transcript pools tv4; FLT1 tv2, tv4; lllR'l tv6; ILÖST tv2,ADGREl tv5; and IL4R tv4) breast cancer total by real-time PCR with cDNA from monocyte and PMN cell populations are evaluated (Figure 2). In Figure 2.°, breast cancer (BC) patients' neutrophil and monocyte populations are normalized with PMN and monocyte populations of healthy individuals. graph is shown. For the breast cancer PMN population, CD16 tvl, tv2, tv3 and Variants tv6, CEACAM21 tvl, tv2 and tv4, FLTl tv2 and tv4, ILlRl tv6 and ILÖST tv2 is displayed; for the monocyte population, CDld tv2, F LT1 tv2, CD44 tvl and tv2, ADGREI TV5 and IL4R tv4 variants are shown. In both monocyte and PMN samples only CDld tv2 is shown. Expression difference for FLTl tv4 shown for PMN It corresponds to the value “0” because it is not found.
Ilk etapta kolorektal kanser sonrasinda meme kanseri hastalarindan elde edilen veriler isiginda CD16 tvl, tv2, tv3, tv4; CDld tvl, tv2; ve CD33 tv2 transkript varyantlarinin gMKBH popülasyonlarinda degerlendirilmesine karar verilmistir. Bu asamada meme ve kolorektal kanser hastalarindan saflastirilarak fonksiyonel deneylerle de baskilayici hücre karakterinde oldugu dogrulanan gMKBH popülasyonunun bahsedilen 7 varyant için sinanmasi gerçeklestirilmektedir (Sekil 3). Sekil 3.”te meme kanseri (MK) ve kolorektal (KRK) kanser hastalarinin gMKBH popülasyonunun (a) saglikli bireylerin PMN ve (b) hastalarin PMN hücreleri ile normalize edildigi grafik gösterilmektedir. Her iki grafikte de gMKBH popülasyonunun CD33 tv2, CDld tvl ve tv2, CD16 tvl, tv2, tv3 ve tv4 varyantlarinin % fark degerleri gösterilmektedir. In the light of the data obtained from breast cancer patients after colorectal cancer in the first place CD16 tvl, tv2, tv3, tv4; CDld tvl, tv2; and gMKBD of CD33 tv2 transcript variants populations were decided to be evaluated. At this stage, breast and colorectal It was purified from cancer patients and suppressed by functional experiments. testing of the confirmed gMCKD population for the aforementioned 7 variants carried out (Figure 3). Figure 3. Breast cancer (BC) and colorectal (CRC) cancer (a) PMN of healthy individuals and (b) PMN of patients with gMCKD The graph is shown as normalized with cells. gMKBH on both charts % difference of the CD33 tv2, CDld tvl and tv2, CD16 tvl, tv2, tv3 and tv4 variants of the population values are shown.
Yapilan analizler ve sekillerde gösterilen grafik sonuçlari ile CD33 tv2, CDld tvl, CD16 tvl, CD16 tv2, ve CD16 tv3 varyantlarinin gMKBH popülasyonunda transkript düzeyinde hasta PMN hücrelerine kiyasla daha düsük oldugu görülmektedir. Bu varyantlardan CD33 tv2 ve CDld tvl sagliklilara kiyasla transkript düzeyinde gMKBH popülasyonunda daha yüksek, CD 1 6 tvl, CD16 tv2, ve CD16 tv3 varyantlari ise daha düsük düzeydedir. With the analyzes made and the graphic results shown in the figures, CD33 tv2, CDld tvl, CD16 tvl, Patients with CD16 tv2, and CD16 tv3 variants at transcript level in the gMCKD population It appears to be lower compared to PMN cells. Of these variants, CD33 tv2 and CDld tvl transcript level was higher in gMCKD population compared to healthy subjects, CD 1 6 tvl, CD16 tv2, and CD16 tv3 variants are at a lower level.
Transkript düzeyinde belirlenen farkin protein düzeyinde karsiligini biyoenformatik araçlarla gelmektedir. Bu kiyaslama öncelikle kolorektal kanser ve saglikli bireylerden elde edilen toplam monosit ve PMN hücre kaynakli cDNA'lar kullanilarak yapilmaktadir. The protein level of the difference determined at the transcript level was determined by bioinformatics tools. is coming. This comparison is primarily based on results obtained from colorectal cancer and healthy individuals. It is performed using cDNAs from total monocytes and PMN cells.
Kolorektal kanser ve saglikli transkript havuzlarinda farklilik gösterdigi tespit edilen 47 tv4; FLTl tv2, tv4; lLlR'l tv6; ILÖST tv2,ADGREl tv5; ve IL4R tv4) meme kanseri toplam monosit ve PMN hücre popülasyonlari kaynakli cDNA ile yapilan gerçek-zamanli PZR ile degerlendirilmektedir (Sekil 2). Sekil 2.°de, meme kanseri (MK) hastalarinin nötrofil ve monosit popülasyonlari saglikli bireylerin PMN ve monosit popülasyonlari ile nonnalize edildigi grafik gösterilmektedir. Meme kanseri PMN popülasyonu için CD16 tvl, tv2, tv3 ve tv6, CEACAM21 tvl, tv2 ve tv4, FLTl tv2 ve tv4, ILlRl tv6 ve ILÖST tv2 varyantlari gösterilmekte; monosit popülasyonu için ise CDld tv2, F LT1 tv2, CD44 tvl ve tv2, ADGREI tv5 ve IL4R tv4 varyantlari gösterilmektedir. Hem monosit hem de PMN örneklerinde yalnizca CDld tv2 gösterilmektedir. PMN için gösterilen FLTl tv4 için ifade farki bulunmadigindan dolayi “0” degerine denk gelmektedir. 47 that were found to differ in colorectal cancer and healthy transcript pools tv4; FLT1 tv2, tv4; lllR'l tv6; ILÖST tv2,ADGREl tv5; and IL4R tv4) breast cancer total by real-time PCR with cDNA from monocyte and PMN cell populations are evaluated (Figure 2). In Figure 2.°, breast cancer (BC) patients' neutrophil and monocyte populations are normalized with PMN and monocyte populations of healthy individuals. graph is shown. For the breast cancer PMN population, CD16 tvl, tv2, tv3 and Variants tv6, CEACAM21 tvl, tv2 and tv4, FLTl tv2 and tv4, ILlRl tv6 and ILÖST tv2 is displayed; for the monocyte population, CDld tv2, F LT1 tv2, CD44 tvl and tv2, ADGREI TV5 and IL4R tv4 variants are shown. In both monocyte and PMN samples only CDld tv2 is shown. Expression difference for FLTl tv4 shown for PMN It corresponds to the value “0” because it is not found.
Ilk etapta kolorektal kanser sonrasinda meme kanseri hastalarindan elde edilen veriler isiginda CD16 tvl, tv2, tv3, tv4; CDld tvl, tv2; ve CD33 tv2 transkript varyantlarinin gMKBH popülasyonlarinda degerlendirilmesine karar verilmistir. Bu asamada meme ve kolorektal kanser hastalarindan saflastirilarak fonksiyonel deneylerle de baskilayici hücre karakterinde oldugu dogrulanan gMKBH popülasyonunun bahsedilen 7 varyant için sinanmasi gerçeklestirilmektedir (Sekil 3). Sekil 3.”te meme kanseri (MK) ve kolorektal (KRK) kanser hastalarinin gMKBH popülasyonunun (a) saglikli bireylerin PMN ve (b) hastalarin PMN hücreleri ile normalize edildigi grafik gösterilmektedir. Her iki grafikte de gMKBH popülasyonunun CD33 tv2, CDld tvl ve tv2, CD16 tvl, tv2, tv3 ve tv4 varyantlarinin % fark degerleri gösterilmektedir. In the light of the data obtained from breast cancer patients after colorectal cancer in the first place CD16 tvl, tv2, tv3, tv4; CDld tvl, tv2; and gMKBD of CD33 tv2 transcript variants populations were decided to be evaluated. At this stage, breast and colorectal It was purified from cancer patients and suppressed by functional experiments. testing of the confirmed gMCKD population for the aforementioned 7 variants carried out (Figure 3). Figure 3. Breast cancer (BC) and colorectal (CRC) cancer (a) PMN of healthy individuals and (b) PMN of patients with gMCKD The graph is shown as normalized with cells. gMKBH on both charts % difference of the CD33 tv2, CDld tvl and tv2, CD16 tvl, tv2, tv3 and tv4 variants of the population values are shown.
Yapilan analizler ve sekillerde gösterilen grafik sonuçlari ile CD33 tv2, CDld tvl, CD16 tvl, CD16 tv2, ve CD16 tv3 varyantlarinin gMKBH popülasyonunda transkript düzeyinde hasta PMN hücrelerine kiyasla daha düsük oldugu görülmektedir. Bu varyantlardan CD33 tv2 ve CDld tvl sagliklilara kiyasla transkript düzeyinde gMKBH popülasyonunda daha yüksek, CD 1 6 tvl, CD16 tv2, ve CD16 tv3 varyantlari ise daha düsük düzeydedir. With the analyzes made and the graphic results shown in the figures, CD33 tv2, CDld tvl, CD16 tvl, Patients with CD16 tv2, and CD16 tv3 variants at transcript level in the gMCKD population It appears to be lower compared to PMN cells. Of these variants, CD33 tv2 and CDld tvl transcript level was higher in gMCKD population compared to healthy subjects, CD 1 6 tvl, CD16 tv2, and CD16 tv3 variants are at a lower level.
Transkript düzeyinde belirlenen farkin protein düzeyinde karsiligini biyoenformatik araçlarla CDld tvl proteini 203-295 pozisyonundaki aininoasit dizilerinde farklidir. The protein level of the difference determined at the transcript level was determined by bioinformatics tools. The CDld tvl protein differs in amino acid sequences at position 203-295.
Bahsedilen varyant proteinlerinin antijenisite analizleri yapildiginda CD16 tv3 proteini disinda CD33 tv2, CDld tvl, CD16 tvl ve CD16 tv2 proteinlerinin farklilik gösteren pozisyonlarinda antijenisite gösteren peptit dizileri belirlenmektedir (Sekil 4). Sekil 4.7te CD33 tv2, CDld tvl, CD16 tvl ve tv2, ve CD16 tv3 protein sekanslarinin antijenisite skorlari kirmizi ile gösterilmektedir. Yatay kirmizi çizgi ise esik degerini göstermektedir. When the antigenicity analyzes of the mentioned variant proteins are performed, the CD16 tv3 protein Apart from the differences in CD33 tv2, CDld tvl, CD16 tvl and CD16 tv2 proteins, peptide sequences showing antigenicity at their positions are determined (Figure 4). In Figure 4.7 Antigenicity scores of CD33 tv2, CDld tvl, CD16 tvl and tv2, and CD16 tv3 protein sequences is shown in red. The horizontal red line indicates the threshold value.
CD16 tvl ve tv2 varyantlarinin translasyonu ile ayni proteinin elde edildigi, varyant farkliliginin 5'UTR kaynakli oldugu ve antijenite gösteren peptit bölgesinin sinyal dizisinde oldugu belirlenmektedir. CDld tVl proteinin farklilik gösteren 93 aminoasitlik peptit bölgesi ve bu bölgede yüksek antijenisite gösteren aminoasit dizilerinin olmasi, CDld tvl proteinini gMKBH karakterizasyonunda kullanilabilecek en güçlü aday yapmaktadir. A variant in which the same protein is obtained by translation of CD16 tvl and tv2 variants. In the signal sequence of the peptide region showing antigenicity and the difference originating from the 5'UTR is determined. Differential 93 amino acid peptide region of the CDld tVl protein and the presence of amino acid sequences with high antigenicity in this region, the CDld tvl protein makes it the strongest candidate that can be used in the characterization of GMKD.
CD33 tv2 proteini ise bir kismi sinyal dizisi bölgesinde kalan ancak sinyal dizisinin kesiminden sonra da N-terminus bölgesinde yerlesmis farklilik gösteren ve antijenisitesi olan 4 aminoasitlik bir bölgeye sahiptir ve antikor tasariminda kullanilmasi oldukça zordur. CD33 tv2 protein, on the other hand, is partially in the signal sequence region but remains in the signal sequence. After incision, it is located in the N-terminus region, which shows differences and has antigenicity. It has a region of 4 amino acids and is very difficult to use in antibody design.
CD33 tV2 proteinini hücre yüzeyinde tespit edebilmek için CD33 tvl ve CD33 tv3 proteinlerinin hücre-disi bölgesinin kullanilabilecegi görülmektedir. CD33 tVl ve CD33 tV3 proteinlerinin hücre-disi bölgesinin çok daha uzun olmasi sebebiyle, bu proteinler CD33 tv2 proteininde olinayan hücre-disi peptit bölgelerine sahiptirler. Dolayisiyla tüm CD33 protein varyantlarini (tVl, tV2, tv3) taniyan ve CD33 tVl ve CD33 tV3 proteinlerini taniyan antikorlarin tasarlanmasi ile CD33 tv2 protein varyantini tasiyan hücrelerin tespit edilebilmesi mümkün olabilecektir. In order to detect the CD33 tV2 protein on the cell surface, CD33 tvl and CD33 tv3 It appears that the extracellular region of the proteins can be used. CD33 tV1 and CD33 tV3 Because the extracellular region of the proteins is much longer, these proteins are CD33 tv2. They have extracellular peptide regions that are not found in the protein. Therefore, all CD33 protein Antibodies that recognize variants (tV1, tV2, tv3) and CD33 tV1 and CD33 tV3 proteins It is possible to detect cells carrying the CD33 tv2 protein variant. can be.
COST BM1404 aksiyonu mMKBH ve eMKBH popülasyonlan için yeterli bilgi ve teknik destek saglayamamakta, bu sebeple gMKBH popülasyonlarin toplam monositler içinde degerlendirilebilmektedir. Bulus ile saglikli bireylerden elde edilen toplam monosit transkriptlerinin meme kanseri ve kolorektal kanser hastalarindan elde edilen toplam monosit transkriptleriyle kiyaslanmasi neticesinde CDld tv2, CD44 tv] ve CD44 tv2 varyantlari için monosit popülasyonu içinde dagilan eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olabilecekleri gösterilmektedir. COST BM1404 action Adequate information and technique for mMCD and mCKD populations cannot provide support, therefore, in total monocytes of gMCKD populations can be evaluated. Total monocytes obtained from healthy individuals with the invention total monocytes of transcripts from breast cancer and colorectal cancer patients for CDld tv2, CD44 tv] and CD44 tv2 variants as a result of comparison with their transcripts specific for mCKD and/or mMCD populations distributed within the monocyte population shown to be biomarkers.
CDld tvl proteini 203-295 pozisyonundaki aininoasit dizilerinde farklidir. The CDld tvl protein differs in amino acid sequences at position 203-295.
Bahsedilen varyant proteinlerinin antijenisite analizleri yapildiginda CD16 tv3 proteini disinda CD33 tv2, CDld tvl, CD16 tvl ve CD16 tv2 proteinlerinin farklilik gösteren pozisyonlarinda antijenisite gösteren peptit dizileri belirlenmektedir (Sekil 4). Sekil 4.7te CD33 tv2, CDld tvl, CD16 tvl ve tv2, ve CD16 tv3 protein sekanslarinin antijenisite skorlari kirmizi ile gösterilmektedir. Yatay kirmizi çizgi ise esik degerini göstermektedir. When the antigenicity analyzes of the mentioned variant proteins are performed, the CD16 tv3 protein Apart from the differences in CD33 tv2, CDld tvl, CD16 tvl and CD16 tv2 proteins, peptide sequences showing antigenicity at their positions are determined (Figure 4). In Figure 4.7 Antigenicity scores of CD33 tv2, CDld tvl, CD16 tvl and tv2, and CD16 tv3 protein sequences is shown in red. The horizontal red line indicates the threshold value.
CD16 tvl ve tv2 varyantlarinin translasyonu ile ayni proteinin elde edildigi, varyant farkliliginin 5'UTR kaynakli oldugu ve antijenite gösteren peptit bölgesinin sinyal dizisinde oldugu belirlenmektedir. CDld tVl proteinin farklilik gösteren 93 aminoasitlik peptit bölgesi ve bu bölgede yüksek antijenisite gösteren aminoasit dizilerinin olmasi, CDld tvl proteinini gMKBH karakterizasyonunda kullanilabilecek en güçlü aday yapmaktadir. A variant in which the same protein is obtained by translation of CD16 tvl and tv2 variants. In the signal sequence of the peptide region showing antigenicity and the difference originating from the 5'UTR is determined. Differential 93 amino acid peptide region of the CDld tVl protein and the presence of amino acid sequences with high antigenicity in this region, the CDld tvl protein makes it the strongest candidate that can be used in the characterization of GMKD.
CD33 tv2 proteini ise bir kismi sinyal dizisi bölgesinde kalan ancak sinyal dizisinin kesiminden sonra da N-terminus bölgesinde yerlesmis farklilik gösteren ve antijenisitesi olan 4 aminoasitlik bir bölgeye sahiptir ve antikor tasariminda kullanilmasi oldukça zordur. CD33 tv2 protein, on the other hand, is partially in the signal sequence region but remains in the signal sequence. After incision, it is located in the N-terminus region, which shows differences and has antigenicity. It has a region of 4 amino acids and is very difficult to use in antibody design.
CD33 tV2 proteinini hücre yüzeyinde tespit edebilmek için CD33 tvl ve CD33 tv3 proteinlerinin hücre-disi bölgesinin kullanilabilecegi görülmektedir. CD33 tVl ve CD33 tV3 proteinlerinin hücre-disi bölgesinin çok daha uzun olmasi sebebiyle, bu proteinler CD33 tv2 proteininde olinayan hücre-disi peptit bölgelerine sahiptirler. Dolayisiyla tüm CD33 protein varyantlarini (tVl, tV2, tv3) taniyan ve CD33 tVl ve CD33 tV3 proteinlerini taniyan antikorlarin tasarlanmasi ile CD33 tv2 protein varyantini tasiyan hücrelerin tespit edilebilmesi mümkün olabilecektir. In order to detect the CD33 tV2 protein on the cell surface, CD33 tvl and CD33 tv3 It appears that the extracellular region of the proteins can be used. CD33 tV1 and CD33 tV3 Because the extracellular region of the proteins is much longer, these proteins are CD33 tv2. They have extracellular peptide regions that are not found in the protein. Therefore, all CD33 protein Antibodies that recognize variants (tV1, tV2, tv3) and CD33 tV1 and CD33 tV3 proteins It is possible to detect cells carrying the CD33 tv2 protein variant. can be.
COST BM1404 aksiyonu mMKBH ve eMKBH popülasyonlan için yeterli bilgi ve teknik destek saglayamamakta, bu sebeple gMKBH popülasyonlarin toplam monositler içinde degerlendirilebilmektedir. Bulus ile saglikli bireylerden elde edilen toplam monosit transkriptlerinin meme kanseri ve kolorektal kanser hastalarindan elde edilen toplam monosit transkriptleriyle kiyaslanmasi neticesinde CDld tv2, CD44 tv] ve CD44 tv2 varyantlari için monosit popülasyonu içinde dagilan eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olabilecekleri gösterilmektedir. COST BM1404 action Adequate information and technique for mMCD and mCKD populations cannot provide support, therefore, in total monocytes of gMCKD populations can be evaluated. Total monocytes obtained from healthy individuals with the invention total monocytes of transcripts from breast cancer and colorectal cancer patients for CDld tv2, CD44 tv] and CD44 tv2 variants as a result of comparison with their transcripts specific for mCKD and/or mMCD populations distributed within the monocyte population shown to be biomarkers.
Bu sonucu destekleyen bir diger veri ise, yapilan fonksiyonel deneylerde de toplam monosit popülasyonu içinde eMKBH ve mMKBH popülasyonlarinin yansimalarinin görülmesidir. Another data supporting this result is that the total monocytes in the functional experiments. It is the reflection of the mCKD and mMCD populations within the population.
Saglikliya kiyasla hasta toplam inonosit popülasyonlarinda nitrik oksit üretim kapasitesinin arttigi ve arginaz, siklo-oksijenaz ve inhibitör molekül ekspresyonlarinin daha yüksek oldugu görülmektedir. Sonuç olarak bulus ile MKBH popülasyonlarinin tespitinde - eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olarak CDld tv2, CD44 tvl ve CD44 tv2 varyantlari, o gMKBH popülasyonlarina özgü biyobelirteçler olarak ise CD33 tV2, CDld tVl, CD] 6 tvl, CDl 6 tv2, ve CD16 tV3 transkript varyantlari tarafindan kodlanan protein izoformlari kullanilabilmektedir. Nitric oxide production capacity in patient total inocyte populations compared to healthy increased and arginase, cyclo-oxygenase and inhibitory molecule expressions were higher. is seen. As a result, the detection of MCKD populations with the invention - as biomarkers specific to mMCD and/or mMDD populations CDld tv2, CD44 tvl and CD44 tv2 variants, o As biomarkers specific to gMCKD populations Transcript variants CD33 tV2, CDld tV1, CD] 6 tvl, CDl 6 tv2, and CD16 tV3 Protein isoforms encoded by can be used.
Bu sonucu destekleyen bir diger veri ise, yapilan fonksiyonel deneylerde de toplam monosit popülasyonu içinde eMKBH ve mMKBH popülasyonlarinin yansimalarinin görülmesidir. Another data supporting this result is that the total monocytes in the functional experiments. It is the reflection of the mCKD and mMCD populations within the population.
Saglikliya kiyasla hasta toplam inonosit popülasyonlarinda nitrik oksit üretim kapasitesinin arttigi ve arginaz, siklo-oksijenaz ve inhibitör molekül ekspresyonlarinin daha yüksek oldugu görülmektedir. Sonuç olarak bulus ile MKBH popülasyonlarinin tespitinde - eMKBH ve/veya mMKBH popülasyonlarina özgü biyobelirteçler olarak CDld tv2, CD44 tvl ve CD44 tv2 varyantlari, o gMKBH popülasyonlarina özgü biyobelirteçler olarak ise CD33 tV2, CDld tVl, CD] 6 tvl, CDl 6 tv2, ve CD16 tV3 transkript varyantlari tarafindan kodlanan protein izoformlari kullanilabilmektedir. Nitric oxide production capacity in patient total inocyte populations compared to healthy increased and arginase, cyclo-oxygenase and inhibitory molecule expressions were higher. is seen. As a result, the detection of MCKD populations with the invention - as biomarkers specific to mMCD and/or mMDD populations CDld tv2, CD44 tvl and CD44 tv2 variants, o As biomarkers specific to gMCKD populations Transcript variants CD33 tV2, CDld tV1, CD] 6 tvl, CDl 6 tv2, and CD16 tV3 Protein isoforms encoded by can be used.
Claims (1)
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TR2020/03833A TR202003833A1 (en) | 2020-03-12 | 2020-03-12 | MYELOID ORIGIN SUPPRESSOR CELLS SPECIFIC BIOBARKER PANEL |
| DE112021001605.9T DE112021001605T8 (en) | 2020-03-12 | 2021-02-23 | BIOMARKER PANEL SPECIFIC FOR MYELOID-DERIVED SUPPRESSIVE CELLS |
| PCT/TR2021/050166 WO2021183079A1 (en) | 2020-03-12 | 2021-02-23 | Biomarker panel specific to myeloid-derived suppressive cells |
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| Application Number | Priority Date | Filing Date | Title |
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| TR2020/03833A TR202003833A1 (en) | 2020-03-12 | 2020-03-12 | MYELOID ORIGIN SUPPRESSOR CELLS SPECIFIC BIOBARKER PANEL |
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| TR202003833A1 true TR202003833A1 (en) | 2021-09-21 |
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| TR2020/03833A TR202003833A1 (en) | 2020-03-12 | 2020-03-12 | MYELOID ORIGIN SUPPRESSOR CELLS SPECIFIC BIOBARKER PANEL |
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| DE (1) | DE112021001605T8 (en) |
| TR (1) | TR202003833A1 (en) |
| WO (1) | WO2021183079A1 (en) |
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| GB201015765D0 (en) | 2010-09-21 | 2010-10-27 | Immatics Biotechnologies Gmbh | Use of myeloid cell biomarkers for the diagnosis of cancer |
| US11073521B2 (en) | 2015-06-01 | 2021-07-27 | The Wistar Institute Of Anatomy And Biology | Methods for monitoring polymorphonuclear myeloid derived suppressor cells |
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| WO2021183079A1 (en) | 2021-09-16 |
| DE112021001605T8 (en) | 2023-03-23 |
| DE112021001605T5 (en) | 2023-01-05 |
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