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16 april 2015: Nederlandse onderzoekers tonen aan dat uitzaaiingen bij borstkanker vaak te maken heeft met bepaalde tumorafwijkingen. Zo zaaien ER en PR positieve tumoren vaker uit naar de botten en Her2 negatieve tumoren naar andere organen en lymfklieren. Met ook gevolgen voor de prognose op overall overleving.

Maar lees dit verslag maar van hun studie naast het artikel over receptorenexpressie en DNA afwijkingen bij borstkanker daaronder:  

http://www.cancernetwork.com/bone-metastases/breast-cancer-subtype-associated-metastasis-pattern-survival?GUID=93D62D96-FA4C-40F4-A25F-BD3441DB08C3&rememberme=1&ts=15042015

17 februari 2015: Bron: Geburtshilfe Frauenheilkd 2015; 75(1): 41-50
DOI: 10.1055/s-0034-1396215

De afgelopen jaren is er bij borstkanker  met name veel progressie geboekt in de diagnose en ontdekken van receptorenexpressie en DNA mutaties gerelateerd aan borstkankertumoren. Maar nog te weinig behandelingen worden daar dan ook op afgestemd in de klinische praktijk, aldus vele onderzoekers in binnen- en buitenland. Deels door te weinig bewijs uit goed gekwalificeerde studies, deels door onwetendheid bij de behandelend artsen, vooral in de niet-academische ziekenhuizen, deels ook door te grote ego's van de behandelend artsen, maar vooral door de onderliggende financiële belangen van de farmaceutische bedrijven en ziekenhuizen. 

Zie hier een lijst van tot nu toe bekende receptorenafwijkingen en DNA mutaties gerelateerd aan borstkanker:

Table 1 Genes whose mutations could potentially play a role in the pathogenesis or prognosis of breast cancer or affect the therapeutic efficacy of breast cancer treatment [28], [32], [34].

AFF2

CREBBP

JAK2

NCOR1

PTPN22

USH2A

AGTR2

CSF1R

KIT

NCOR2

PTPRD

XBP1

AKT1

CTCF

KRAS

NF1

RB1

AKT2

DCAF4L2

LCLAT1

NOTCH4

RB1CC1

AKT3

DDR1

LTK

NRAS

RELN

ARID1A

EGFR

LYN

OR4N4

RERG

ARID1B

ERBB2

MAGI3

OR6A2

RPGR

ATM

ERBB3

MALAT1

PAPSS2

RRM2

ATR

ERBB4

MAN2A2

PDGFRA

RUNX1

AURKA

ESR1

MAP2K4

PGM2

RYR2

BIRC6

FBXW7

MDM2

PIK3CA

SEPT13

BRAF

FOXA1

MDM4

PIK3R1

SF3B1

BRCA1

FOXC1

MED12

PIN1

SMARCD1

BRCA2

FRG1B

MET

PLD1

SMG1

CASP8

FZD7

MLL

POLR1A

TAB1

CAV1

GATA3

MLL2

PPP2R2A

TAB2

CBFB

GPR32

MLL3

PRKCZ

TBL1XR1

CCND3

HEXA

MTAP

PRKDC

TBX3

CDH1

HMGCS2

MTPR

PRKX

TGFB1

CDKN1B

IDH3B

MYBB

PRLR

TGFB2

CLCA1

INSRR

MYBL2

PRPS2

TP53

CLEC19A

JAK1

NCOA3

PTEN

TPH2

Meer dan tien jaar na de eerste publicaties van DNA mutaties zijn de analyse methoden zo sterk verbeterd dat op dit moment elke borstkankerpatiënt , zeker met uitgezaaide borstkanker een personalised medicine programma zou kunnen volgen op basis van een goed receptoren- en DNA profiel. Helaas blijft de klinische praktijk ver achter bij wat al bekend is.

Biomarkers op elk niveau, genetisch, epigenetisch, receptorenexpressie, micro-RNA, proteometics enz. kunnne worden gebruikt voor een gedegen persoonlijke analyse en diagnose. Dit heeft geleid tot veranderingen in de opzet van klinische studies maar te vaak voor te kleine groepen patiënten zodat de resultaten vaak niet worden geaccepteerd voor grotere aantallen patiënten. De screening en registratie van al die afwijkingen in een algemene databank is daarom heel belangrijk om toekomstige klinische studies succesvol en bepalend te laten zijn voor de behandelingen. 

praegant study bij borstkanker

De Netwerk groep Preagnant is zo'n groep van ziekenhuizen en onderzoekers die gegevens verzamelen en daaruit weer nieuwe studies ontwerpen en laat zien aan oncologen en behandelaars welke behandelingen en medicijnen verder ontwikkeld zouden moeten worden voor een juiste personalised medicine aanpak.

Dit studierapport: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network vat recente ontwikkelingen samen en beschrijft hoe het Preagnant netwerk een professionele infrastructuur creeërt voor patiënten en professionals, artsen en onderzoekers. 

Ik heb maar geen vertaling gemaakt van alles wat in dit studierapport staat beschreven, maar hier het studierapport opgedeeld in enkele belangrijke delen met de referentielijst erbij die correspondeert met de cijfers achter bepaalde citaten.

Prognostic and Predictive Factors in Metastatic Breast Cancer

Source: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Factors described in some studies as prognostic factors for breast cancer patients with metastatic disease include age, tumor mass, grading, time from primary diagnosis to metastasis, and the site of metastasis [2]. Molecular factors have also been associated with prognosis. Most studies have focused on the prognostic characteristics of the primary tumor and the prognosis for the patient after metastasis. Hormone receptor status, HER2 status and Ki-67 are the most commonly investigated parameters [3]. However, tumor characteristics are known to change during the course of disease [4], [5], [6], [7], [8], [9], [10], [11], and the recommendation to carry out bioptic evaluation of metastases to determine their molecular characteristics has therefore been included in national therapy recommendations [12]. But although obtaining tumor tissue from the breast is relatively uncomplicated, for practical reasons and to avoid complications physicians often object to taking biopsies of metastatic tissue. Etc,: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Molecular Patterns in Breast Cancer

Source: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

As our knowledge of the human genome increases and the cost of genome-wide analysis decreases, the relationships between genetics, epigenetics, gene expression and protein functions are becoming clearer. The existence of molecular subgroups for breast cancer types and their prognostic relevance based on mRNA measurements were already discussed in the literature more than 10 years ago [13], [14], [15]. One classification differentiates between basal, luminal A, luminal B and HER2-enriched breast cancer subtypes. An attempt was subsequently made to classify these molecular subtypes using known histopathological characteristics [16], [17], [18], [19]. Triple negative tumors (ER negative, PgR negative and HER2 negative) were found to most closely resemble basal tumors. Slow-proliferating (e.g. Ki-67 < 14 %) and hormone receptor-positive tumors generally correspond to luminal A tumors, while hormone receptor-positive tumors with high proliferation rates (e.g. Ki-67 > 14 %) are most closely correlated with luminal B tumors [20], [21], [22]. These cut-offs mirror the biological subtypes. However, other cut-offs (for example 20 %) are also being discussed in clinical practice [23].

Etc.>>>>>>Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Genetic variants as prognostic or predictive factors

Source: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Another genetic tumor change can consist of an increase or decrease in the number of gene copies. In a large investigation carried out as part of the METABRIC study, the number of gene copies and the associated gene expressions were determined for every gene [29]. This allowed positions to be identified in the genome where changes in gene copy numbers and an associated change in gene expression occurred most commonly. Genes in which such changes occurred include ZNF703, PTEN, MYC, CCND1, MDM2, ERBB2, CCNE1, MDM1, MDM4, CDK3, CDK4, CAMK1D, PI4KB and NCOR1 (amplifications) and PPP2R2A, MTAP und MAP2K4 (deletions). The strongest association was found between amplification in the genes HER2 (ERBB2) and cyclin D1 (CCND1). Etc.>>>>>Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Significance of genetic germline variants

Source: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

A patientʼs genetic heredity can be associated with a specific molecular breast cancer subtype. The most famous examples of this are patients with the BRCA1 mutation. If a patient with the BRCA1 mutation develops breast cancer, the probability that this cancer will be triple negative is more than 50 % [27], [35], [36]. Other low-penetrance genetic variants reported in the literature were also found to be associated with a specific molecular subtype [37], [38], [39], [40], [41], [42], [43], [44], [45]. Some of them are similar to BRCA1 and BRCA2 in that they play important roles in both breast cancer and ovarian cancer [46], [47], [48]. Table 2 Breast cancer studies which have integrated molecular tests in their study design or use them as predictors for the primary study goal (* relevant for therapy or study means that the results of biomarker tests affected the choice of therapy or the study design over and above stratification or subgroup analysis; ** in some of these studies, inoperable locally advanced disease was sufficient for inclusion in the study). Etc.>>>>>> Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

Study name

Test

Test results relevant for therapy or study*

Drug

Therapy setting

BRIGHTNESS (NCT02032277)

germline DNA testing for BRCA1/2 mutation

veliparib

neoadjuvant

Olympia (NCT02032823)

germline DNA testing for BRCA1/2 mutation

X

olaparib

adjuvant/post-neoadjuvant

EMBRACA (NCT01945775)

germline DNA testing for BRCA1/2 mutation

X

talazoparib

1st–3rd line metastasized**

ABRAZO (NCT02034916)

germline DNA testing for BRCA1/2 mutation

X

talazoparib

4th+ line metastasized**

Neoadjuvant BYL719 vs. BKM120 Study (NCT01923168)

tumor PI3K testing

X

buparlisib (BKM120)/alpelisib (BYL719)

neodjuvant

PRESENT (NCT01479244)

HLA testing/HER2 testing

X

nelipepimut-S

adjuvant

DETECT III/IV (NCT01619111)

measurement of HER2 and ER expression in CTCs

X

lapatinib, everolimus, eribulin

FERGI (NCT01437566)

tumor PI3K testing

pictilisib

metastasized**

BT062 (EudraCT No. 2013–003 252–20)

TNBC, CD138 expression

X

indatuximab, ravtansine

metastasized

Belle 2/3/4 (NCT01610284, NCT01633060, NCT01572727)

tumor PI3K testing

buparlisib (BKM120)

metastasized**

GLOW (NCT01202591)

tumor FGFR1 amplification

X

AZD4547

metastasized**

ADAPT (NCT01817452, NCT01745965)

21-gene expression testing; serial gene expression testing

X

various

neoadjuvant/adjuvant

PreFace (NCT01908556)

genome-wide germline genotyping

letrozole

adjuvant

SUCCESS C (NCT00847444)

CTC determination

X

exemestan/
tamoxifen

adjuvant

Circulating Tumor Cells and Circulating Tumor Nucleic Acids

Source: Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network

The presence of circulating tumor cells (CTC) in plasma has been consistently associated with prognosis in patients with metastasized breast cancer [66], [67], [68], [69]. The presence of CTCs was found to be an independent prognostic factor even in the non-metastatic setting [70]. The next logical step was to determine the molecular properties of circulating tumor cells [71], [72]. Several clinical studies are currently looking at whether this could help with treatment planning and offer useful information for prognosis [73], [74], [75], [76]. However, isolating the CTCs is still relatively expensive and time-consuming and requires large, cost-intensive equipment which is expensive to run.

A less expensive approach could be to analyze circulating nucleic acids. Tumor cells in the body release small amounts of DNA into the bloodstream, known as circulating DNA (ctDNA). This process was first described in 1948 [77], [78]. Etc.>>>>>>>>>Biomarkers in Patients with Metastatic Breast Cancer and the PRAEGNANT Study Network


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