Biomarkers, medical treatment and fetal intrapartum surveillance in intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific disorder characterized by maternal pruritus and elevated liver enzymes. It usually begins in the third trimester of pregnancy and resolves spontaneously after delivery. ICP is considered benign for the pregnant woman, but it is associated with an increased risk for unexplained term stillbirth and preterm delivery. There are no specific laboratory markers to diagnose ICP. The diagnosis is currently based on the presence of maternal pruritus and elevated values of alanine aminotransaminases (ALT) and serum bile acids (BA). Recently, ursodeoxycholic acid (UDCA) has been used for treatment. Mechanisms leading to intrauterine fetal death (IUFD) may be multifactorial and are unknown at present. For this thesis, 415 pregnant women with ICP were studied. The aim was to evaluate the value of the liver enzyme glutathione S-transferase alpha (GSTA) as a specific marker of ICP and to assess the effect of maternal UDCA therapy on maternal laboratory values and fetal outcome. The specific markers predisposing the fetus to heart arrhythmia were studied by comparing waveform analysis of fetal electrocardiograms (FECG) during labor in pregnancies complicated by ICP with controls. The levels of maternal GSTA were high and the values correlated with the value of ALT in patients with ICP. UDCA therapy reduced the values of the liver enzymes and alleviated maternal pruritus, but it did not influence maternal hormonal values. Although the newborns experienced an uneventful perinatal outcome, severe ICP was still associated with preterm birth and admission to the neonatal intensive care unit (NICU). There were no significant differences in intrapartum FECG findings between fetuses born to ICP women and controls.Raskaudenaikaisen maksan toimintahäiriön diagnosointi, hoito ja sikiön synnytyksenaikainen seuranta Äidin raskaudenaikainen maksan toimintahäiriö eli hepatogestoosi aiheuttaa ihokutinaa ja maksa-arvojen nousua odotusaikana. Häiriö alkaa tavallisesti loppuraskauden aikana ja korjaantuu itsestään synnytyksen jälkeen. Hepatogestoosi ei ole vaarallinen äidille, mutta siihen liittyy kuitenkin suurentunut sikiökuoleman riski sekä usein ennenaikainen synnytys. Tämän vuoksi hepatogestoosiraskaudet ovat riskiraskauksia ja tarvitsevat polikliinistä seurantaa loppuraskauden aikana sekä synnytyksen suunnittelua. Hepatogestoosin diagnosointi on perustunut äidin kutinaoireisiin ja kohonneisiin maksa-arvoihin. Mitään erityistä laboratoriokoetta ei ole ollut. Lääkityksenä on yleisesti käytetty ursodeoksikoolihappoa. Sikiön äkkikuoleman syy on edelleen epäselvä, mutta sydämen rytmihäiriö saattaa olla sen takana. Tähän tutkimukseen kuului yhteensä 415 naista, joilla todettiin raskausaikana hepatogestoosi. Maksan erittämän entsyymin (plasman glutathione S-transferaasi alphan) osuvuutta selvitettiin hepatogestoosin diagnostiikassa. Ursodeoksikoolihapon vaikutuksia tutkittiin äitiin ja syntyvään lapseen. Lisäksi etsittiin sikiön sydänsähkökäyrästä tekijöitä, jotka saattavat altistaa rytmihäiriöille. Tutkimamme maksaentsyymin todettiin nousevan yleisesti käytetyn maksaentsyymin (ALAT) nousun kanssa ja siten mahdollisesti tarkentavan diagnoosia. Ursodeoksikoolihappo parantaa maksa-arvoja ja vähentää äidin kutinaoireita. Käyttämämme ursodeoksikoolihapon annos oli pieni. Vastasyntyneet lapset olivat hyväkuntoisia. Tutkimuksessani ei löydetty merkittäviä sydänsähkökäyrän muutoksia synnytyksen aikana hepatogestoosiäitien sikiöiltä terveiden äitien sikiöihin verrattuna.Siirretty Doriast

Kohdunrunkosyövän kirurgisen ja liitännäishoidon suunnittelu

Teema : gynekologinen syöpä. English summaryPeer reviewe

Molecular subtype diagnosis of endometrial carcinoma: comparison of the next-generation sequencing panel and Proactive Molecular Risk Classifier for Endometrial Cancer classifier

The Cancer Genome Atlas -based molecular classification of endometrial carcinoma (EC) has the potential to better identify those patients whose disease is likely to behave differently than predicted when using traditional risk stratification; however, the optimal approach to molecular subtype assignment in routine practice remains undetermined. The aim of this study was to compare the results of two different widely available approaches to diagnosis the EC molecular subtype. EC specimens from 60 patients were molecularly subclassified using two different methods, by using the FoundationOne CDx next-generation sequencing (NGS) panel and using the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) classifier and performing immunostaining for mismatch repair proteins and p53. POLE mutation status was derived from FoundationOne results in both settings. Molecular classification based on ProMisE was successful for all 60 tumors. Microsatellite instability status could be determined based on the NGS panel results in 53 of 60 tumors, so ProMisE and NGS molecular subtype assignment could be directly compared for these 53 tumors. Molecular subtype diagnosis based on NGS and ProMisE was in agreement for 52 of 53 tumors. One tumor was microsatellite stable but showed loss of MLH1 and PMS2 expression. Molecular subtype diagnosis of EC based on the NGS panel of formalin-fixed paraffin-embedded ECs and based primarily on immunostaining (ProMisE) yields identical results in 98.1% (52/53, kappa Z 0.97) of cases. Although results obtained using these two approaches are comparable, each has advantages and disadvantages that will influence the choice of the method to be used in clinical practice

Genetic, clinic and histopathologic characterization of BRCA-associated hereditary breast and ovarian cancer in southwestern Finland

We have analyzed the histopathological, clinical, and genetic characteristics in hereditary breast and ovarian cancer patients of counselled families from 1996 up to today in the southwestern Finland population. In this study we analyzed the incidence of different BRCA1 and BRCA2 pathogenic variants (PV). 1211 families were evaluated, and the families were classified as 38 BRCA1 families, 48 BRCA2 families, 689 non-BRCA families and 436 other counselled families (criteria for genetic testing was not met). In those families, the study consisted of 44 BRCA1 breast and/or ovarian cancer patients, 58 BRCA2 cancer patients, 602 non-BRCA patients and 328 other counselled patients. Breast cancer mean onset was 4.6 years earlier in BRCA1 carriers compared to BRCA2 (p = 0.07, a trend) and ovarian cancer onset almost 11 years earlier in BRCA1 families (p BRCA families the onset of ovarian cancer was later than 40 years, and BRCA2-origin breast cancer was seen as late as 78 years. The BRCA PV (9%) increases the risk for same patient having both ovarian and breast cancer with a twofold risk when compared to non-BRCA group (4%) (95% CI p BRCA1 (42%) carriers is approximately 2.6 times vs more common than in BRCA2 carriers (16%) (p BRCA2 (17%) and other counselled patients' group (4%) (p BRCA2-families have a unique PV, and correspondingly 39% of BRCA1-families. The results of this analysis allow improved prediction of cancer risk in high-risk hereditary breast and ovarian families in southwestern Finland and improve long term follow-up programs. According to the result it could be justified to have the discussion about prophylactic salpingo-oophorectomy by the age of 40 years. The possibility of late breast cancer onset in BRCA2 carriers supports the lifelong follow-up in BRCA carriers. Cancer onset is similar between BRCA2 carries and non-BRCA high-risk families. This study evaluated mutation profile of BRCA in southwestern Finland. In this study genotype-phenotype correlation was not found</p

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.</p

Biomarkers, medical treatment and fetal intrapartum surveillance in intrahepatic cholestasis of pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific disorder characterized by maternal pruritus and elevated liver enzymes. It usually begins in the third trimester of pregnancy and resolves spontaneously after delivery. ICP is considered benign for the pregnant woman, but it is associated with an increased risk for unexplained term stillbirth and preterm delivery.&nbsp; There are no specific laboratory markers to diagnose ICP. The diagnosis is currently based on the presence of maternal pruritus and elevated values of alanine aminotransaminases (ALT) and serum bile acids (BA). Recently, ursodeoxycholic acid (UDCA) has been used for treatment. Mechanisms leading to intrauterine fetal death (IUFD) may be multifactorial and are unknown at present.&nbsp; For this thesis, 415 pregnant women with ICP were studied. The aim was to evaluate the value of the liver enzyme glutathione S-transferase alpha (GSTA) as a specific marker of ICP and to assess the effect of maternal UDCA therapy on maternal laboratory values and fetal outcome. The specific markers predisposing the fetus to heart arrhythmia were studied by comparing waveform analysis of fetal electrocardiograms (FECG) during labor in pregnancies complicated by ICP with controls.&nbsp; The levels of maternal GSTA were high and the values correlated with the value of ALT in patients with ICP. UDCA therapy reduced the values of the liver enzymes and alleviated maternal pruritus, but it did not influence maternal hormonal values. Although the newborns experienced an uneventful perinatal outcome, severe ICP was still associated with preterm birth and admission to the neonatal intensive care unit (NICU). There were no significant differences in intrapartum FECG findings between fetuses born to ICP women and controls.</p

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

bbab272Each patient’s cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.Peer reviewe

Functional Homologous Recombination Assay on FFPE Specimens of Advanced High-Grade Serous Ovarian Cancer Predicts Clinical Outcomes

Peer reviewe