O-222 An artificial intelligence model that was trained on pregnancy outcomes for embryo viability assessment is highly correlated with Gardner Score

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
S Diakiw ◽  
M VerMilyea ◽  
J M M Hall ◽  
K Sorby ◽  
T Nguyen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Pregnancy Outcomes ◽  
Embryo Quality ◽  
Cell Mass ◽  
Clinical Pregnancy ◽  
Morphological Features ◽  
Embryo Morphology ◽  
Embryo Viability ◽  
Viability Assessment ◽  
Highly Correlated

Abstract Study question Do artificial intelligence (AI) models used to assess embryo viability (based on pregnancy outcomes) also correlate with known embryo quality measures such as Gardner score? Summary answer An AI for embryo viability assessment also correlated with Gardner score, further substantiating the use of AI for assessment and selection of good quality embryos. What is known already The Gardner score consists of three separate components of embryo morphology that are graded individually, then combined to give a final score describing Day 5 embryo (blastocyst) quality. Evidence suggests the Gardner score has some correlation with clinical pregnancy. We hypothesized that an AI model trained to evaluate likelihood of clinical pregnancy based on fetal heartbeat (in clinical use globally) would also correlate with components of the Gardner score itself. We also compared the ability of the AI and Gardner score to predict pregnancy outcomes. Study design, size, duration This study involved analysis of a prospectively collected dataset of single static Day 5 embryo images with associated Gardner scores and AI viability scores. The dataset comprised time-lapse images of 1,485 embryos (EmbryoScope) from 638 patients treated at a single in vitro fertilization (IVF) clinic between November 2019 and December 2020. The AI model was not trained on data from this clinic. Participants/materials, setting, methods Average patient age was 35.4 years. Embryologists manually graded each embryo using the Gardner method, then subsequently used the AI to obtain a score between 0 (predicted non-viable, unlikely to lead to a pregnancy) and 10 (predicted viable, likely to lead to a pregnancy). Correlation between the AI viability score and Gardner score was then assessed. Main results and the role of chance The average AI score was significantly correlated with the three components of the Gardner score: expansion grade, inner cell mass (ICM) grade, and trophectoderm grade. Average AI score generally increased with advancing blastocyst developmental stage. Blastocysts with expansion grades of ≥ 3 are generally considered suitable for transfer. This study showed that embryos with expansion grade 3 had lower AI scores than those with grades 4-6, consistent with a reduced pregnancy rate. AI correlation with trophectoderm grade was more significant than with ICM grade, consistent with studies demonstrating that trophectoderm grade is more important than ICM in determining clinical pregnancy likelihood. The AI predicted Gardner scores of ≥ 2BB with an accuracy of 71.7% (sensitivity 75.1%, specificity 45.9%), and an AUC of 0.68. However, when used to predict pregnancy outcome, the AI performed 27.9% better than the Gardner score (accuracies of 49.8% and 39.0% respectively). Even though the AI was highly correlated with the Gardner score, the improved efficacy for predicting pregnancy suggests that a) the AI provides an advantage in standardization of scoring over the manual and subjective Gardner method, and b) the AI is likely identifying and evaluating morphological features of embryo quality that are not captured by the Gardner method. Limitations, reasons for caution The Gardner score is not a linear score, creating challenges with setting a suitable threshold relating to the prediction of pregnancy. The 2BB treshold was chosen based on literature (Munné et al 2019) and verified by experienced embryologists. This correlative study may also require additional confirmatory studies on independent datasets. Wider implications of the findings The correlation between AI scores and known features of embryo quality (Gardner score) substantiates the use of the AI for embryo assessment. The AI score provides further insight into components of the Gardner score, and may detect morphological features related to clinical pregnancy beyond those evaluated by the Gardner method. Trial registration number Not applicable

P–202 Past embryo viability is not always a good predictor of future pregnancy: dynamic viability suggests video has limited benefit over static images for AI assessment

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
J M M Hall ◽  
M A Dakka ◽  
D Perugini ◽  
S Diakiw ◽  
T Nguyen ◽  
...  
Keyword(s):  
Pregnancy Outcome ◽  
Pregnancy Outcomes ◽  
Embryo Quality ◽  
Time Lapse ◽  
Embryo Viability ◽  
Viability Assessment ◽  
Time Points ◽  
Static Images ◽  
Future Pregnancy ◽  
Over Time

Abstract Study question Does embryo quality/viability change over time, suggesting the use of video for AI-based embryo quality assessment has limited benefit over single point-in-time images? Summary answer AI assessment of single static embryo images at multiple time-points indicates embryo viability is dynamic, and past viability is a limited predictor of future pregnancy. What is known already Artificial Intelligence (AI) has been applied to the problem of embryo quality (viability) assessment using either video or single static images. However, whether historical data within video provide an additional advantage over single static images of embryos (at the time of transfer) for assessing embryo viability is not known. This applies to both manual and AI-based embryo assessment. If embryo viability changes over time prior to transfer, then the implication is that the assessment of future pregnancy using historical embryo data from videos would provide limited additional value over single static images taken immediately prior to transfer. Study design, size, duration Retrospective dataset of single embryo images taken at up-to three time-points prior to transfer: Early Day 5, Late Day 5 (8 hours later), and Early Day 6 (16 hours later), with corresponding fetal heartbeat (pregnancy) outcomes. The AI assessed the viability of each embryo at its available timepoints. Viability prediction was compared with pregnancy outcome to assess viability predictiveness at each timepoint prior to transfer, and assess the variability of viability over time. Participants/materials, setting, methods Single static images of 173 embryos were taken using time-lapse incubators from a single IVF clinic. 116 embryos were viable (led to a pregnancy) and 57 were non-viable (did not lead to a pregnancy). The AI was trained on thousands of Day 5 static embryo images taken from multiple IVF laboratories and countries, but was not trained on data from this clinic. Main results and the role of chance When embryos were assessed as viable by the AI immediately prior to transfer (no delay), the AI accuracy (sensitivity) in predicting pregnancy was 88.1% (59/67) for Early Day 5, 84.8% (28/33) for Late Day 5 and 87.5% (14/16) for Early Day 6. When the delay between AI assessment and transfer is 8 hours, 16 hours and 24 hours, the the accuracy drops to 66.7% (22/33), 31.3% (5/16) and 12.5% (2/16), respectively. These results indicate that the viability of the embryo is dynamic, and therefore time series analysis, i.e. using video, may not be well suited for embryo viability assessment because past viability is not necessarily a good predictor of future viability or pregnancy outcome. The viability of the embryo immediately prior to transfer, from a single static image, is a reliable predictor of viability. This is consistent with the current clinical practice of using Gardner score end-point assessment for embryo quality. Results also suggest significant benefits from using time-lapse with AI, where AI continually assesses embryo viability over time using static images. The time point at which the embryo should be transferred to maximize pregnancy outcome is when the embryo has the greatest AI viability score. Limitations, reasons for caution Although evidence suggests past embryo viability is a limited predictor of future pregnancy, a side-by-side comparison of video versus single static image AI assessment would further verify that the historical or change in embryo development or viability has minimal impact on embryo viability assessment at the time prior to transfer. Wider implications of the findings: Time-lapse and AI can beneficially change the way embryos are assessed. Continual AI monitoring of embryos enables optimization of which embryo to transfer and when, to ultimately improve pregnancy outcomes for patients. The findings also suggest that static end-point AI assessment is sufficient for predicting embryo implantation potential. Trial registration number Not applicable

P–249 Does the re-expansion of thawed embryos affect the clinical outcomes of human blastocyst vitrification?

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
T Huong ◽  
A Ph. Th. Tú ◽  
L H Mai ◽  
N Doã. Thảo ◽  
C A Mạnh
Keyword(s):  
Pregnancy Rate ◽  
Clinical Outcomes ◽  
Embryo Quality ◽  
Cell Mass ◽  
Clinical Pregnancy ◽  
Clinical Pregnancy Rate ◽  
Ongoing Pregnancy ◽  
Ongoing Pregnancy Rate ◽  
Group 2 ◽  
Group 1

Abstract Study question Is that essential for prolonged culture of thawed blastocysts in order to be fully re-expanded before transferring? Summary answer Ongoing pregnancy rates decreased in blastocysts that not fully re-expanded after thawing. What is known already: The thaw survival of blastocysts is examined based on morphology of inner cell mass (ICM) and trophectoderm (TE). However, thawed blastocysts experience multiple changes in morphology and might be collapse after thawing due to the presence of blastocoel cavity. It is then difficult to evaluate blastocyst quality. Therefore, the blastocyst re-expansion is considered as a criteria to assess quickly the competent embryos. It also reflects the status energy metabolism from high quality embryo. After all, there are still some controversial opinions about the influence of re-expansion status after thawing. Study design, size, duration This was a retrospective study based on data collected between October 2019 and December 2020. A total 528 thawed blastocysts which were divided into two groups according to the post-thaw reexpansion status: fully re-expanded blastocysts (n = 416), partial or no re-expanded blastocysts (n = 112). The re-expansion status of blastocyst was assess prior to loading on the catheter by senior embryologists. Participants/materials, setting, methods Primary outcome is ongoing pregnancy. Only frozen single D5 transfer cycles were included. We excluded the frozen sperm/oocytes/embryos donation cycles, missing data, non-intact embryos after thawing. Statistical analyses were performed with T or chi-squared tests. Multivariable regression analysis was performed adjusting for the following confounding factors: age, BMI, embryo quality, re-expansion status, biopsied blastocyst. Main results and the role of chance Female age, BMI, number of previous cycles, endometrial thickness, positive HCG results, clinical pregnancy rate were comparable among patients within two groups. The rate of ongoing pregnancy rate in group 1 was significant higher compared with group 2 (51 vs 40.2, p < 0.05). The number of good quality blastocyst transferred in group 1 was higher than in group 2 (p < 0.001). However, under the same embryo quality, there were no difference between clinical pregnancy rate and ongoing pregnancy rate between two groups. When logistic regression were performed: only embryo quality, but not the re-expansion status, was noted to be an independent predictor of ongoing pregnancy (OR = 3.53;95% CI; 1.734–7.184;p=0.001). Limitations, reasons for caution The main limitation of the study is its retrospective design. Wider implications of the findings: Clinical outcomes are comparable between re-expanded blastocyst and partial or no re-expanded blastocysts, although ongoing pregnancy can be improved when embryos are fully expanded. As expected, blastocysts quality has the most important impact on ongoing pregnancy rate. Trial registration number Not applicable

scholarly journals Effectiveness of HP-hMG vs r-FSH in Patients undergoing IVF/ICSI Cycles with Moderate Male Factor Infertility

2012 ◽  
Vol 3 (2) ◽  
pp. 51-56
Author(s):  
Rutvij Jay Dalal
Keyword(s):  
Gnrh Agonist ◽  
Pregnancy Outcomes ◽  
Embryo Quality ◽  
Study Groups ◽  
Fertilization Rate ◽  
Clinical Pregnancy ◽  
Human Menopausal Gonadotropin ◽  
Male Factor Infertility ◽  
Male Factor ◽  
Control Study

ABSTRACT Aim The aim of this case-control study was to compare the efficacy of highly purified human menopausal gonadotropin (HPhMG) vs recombinant follicle stimulating hormone (r-FSH) treatments following GnRH agonist suppression in patients undergoing intracytoplasmic sperm injection (ICSI) with moderate male factor infertility in terms of oocyte and embryo quality and clinical pregnancy outcomes. Materials and methods A total of 240 infertile women were treated with HP-hMG group (n: 120 patients) or (r-FSH group, n: 120 patients) following GnRH agonist suppression (long regimen). Inclusion criteria for the study groups were infertility due to moderate oligoastheno-teratospermia with no associated female infertility factor, previous ART cycles <2, female patients aged 19 to 35 years with normal basal FSH, regular ovulatory cycles and BMI <30 kg/m2. Results Treatment durations and gonadotropin doses were similar in both groups. Cycle cancellation rates, clinical pregnancy and miscarriage rates, total and metaphase II oocytes retrieved, fertilization rate, number of embryos transferred were all similar in both groups. The clinical pregnancy rates were 45.9% (n: 50/109) in the r-FSH group and 40.4% (n: 44/109) in the HP-hMG group. Conclusion HP-hMG is effective as r-FSH in terms of oocyte and embryo quality and clinical pregnancy outcomes in patients undergoing ICSI with moderate male factor infertility. How to cite this article Dalal RJ, Pai H, Palshetkar N. Effectiveness of HP-hMG vs r-FSH in Patients undergoing IVF/ICSI Cycles with Moderate Male Factor Infertility. Int J Infertility Fetal Med 2012;3(2):51-56.

scholarly journals The Morphology of Inner Cell Mass Is the Strongest Predictor of Live Birth After a Frozen-Thawed Single Embryo Transfer

2021 ◽  
Vol 12 ◽  
Author(s):  
Jihui Ai ◽  
Lei Jin ◽  
Yu Zheng ◽  
Peiwen Yang ◽  
Bo Huang ◽  
...  
Keyword(s):  
Embryo Transfer ◽  
Live Birth ◽  
Pregnancy Outcomes ◽  
Birth Rate ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Live Birth Rate ◽  
Single Embryo Transfer ◽  
Clinical Pregnancy ◽  
Stage 4

BackgroundThe scoring system for human blastocysts is traditionally based on morphology; however, there are controversies on the effect of morphology parameters on pregnancy outcomes. The aim of this study is to evaluate the predicting value of each morphology parameter on pregnancy outcomes in a setting of single embryo transfer.MethodsThis is a retrospective cohort study on patients undergoing frozen-thawed single blastocyst transfer at our center, between Jan. 2009 and Dec. 2018. A total of 10,482 cycles were analyzed. The blastocysts were scored according to the expansion and hatching status, morphology of inner cell mass (ICM), and cells of trophectoderm (TE). The primary outcome measure was live birth rate. One-way analysis of variance, chi-square test, and multiple logistic regression were used for statistical analysis.ResultsThe clinical pregnancy rate was lower in the blastocysts of stage 3 (48.15%), compared with those of stage 4 (56.15%), stage 5 (54.91%), and stage 6 (53.37%). The live birth rate was lower in the blastocysts of stage 3 (37.07%), compared with those of stage 4 (44.21%) and stage 5 (41.67%). The rates of clinical pregnancy (A: 66.60%, B: 53.25%, C: 39.33%) and live birth (A: 54.62%, B: 41.29%, C: 28.45%) were both decreased with decreasing grade of ICM morphology, and these differences were pairwise significant. The miscarriage rate of blastocysts with ICM grade A was lower, compared with ICM grade C (17.53 vs. 27.66%). Blastocysts with TE morphology of C had lower rates of clinical pregnancy (43.53%) and live birth (32.57%), compared with those with TE morphology of A and B (clinical pregnancy rate: 64.26% for A, 58.11% for B; live birth rate: 52.74% for A, 45.64% for B). There were no significant differences in rates of clinical pregnancy, live birth, and miscarriage between the blastocysts with TE grade A and B.ConclusionsThe blastocyst expansion stage, ICM grade, and TE grade are all associated with pregnancy outcomes. ICM grade is the strongest predictor of live birth. A blastocyst with stage 4–5, ICM grade A, and TE grade A/B should be given priority for single embryo transfer.

P–228 AI-based assessment of embryo viability correlates with features of embryo ploidy

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
M VerMilyea ◽  
S Diakiw ◽  
J Hall ◽  
M Dakka ◽  
T Nguyen ◽  
...  
Keyword(s):  
Pregnancy Outcome ◽  
Confidence Score ◽  
Linear Increase ◽  
Morphological Features ◽  
Image Correlation ◽  
Average Score ◽  
Embryo Viability ◽  
Viability Assessment ◽  
Ploidy Status ◽  
Viability Score

Abstract Study question Do AI models used to assess embryo viability (based on pregnancy outcome) also correlate with known embryo quality measures such as ploidy status? Summary answer An AI for embryo viability assessment correlated with ploidy status, and with karyotypic features of aneuploidy, supporting its use for embryo selection. What is known already One factor that can influence pregnancy success is the genetic status of the embryo. PGT-A is commonly used to test for embryo ploidy, with the aim of identifying karyotypically normal embryos (euploid embryos), for preferential transfer. There is evidence suggesting that transfer of euploid embryos produces favorable clinical outcomes over aneuploid embryos. Given the AI model was trained to evaluate clinical pregnancy, it was hypothesized that the score might also correlate with ploidy status, and with different types of aneuploidies. Little is known about morphological correlations with embryo ploidy status, so we also sought to explore this relationship. Study design, size, duration This study involved analysis of a retrospective dataset of single static Day 5 embryo (blastocyst) images with associated PGT-A results and AI viability scores. The dataset comprised images of 5,469 embryos from 2,615 consecutive patients treated at five US IVF clinics between February 2015 and April 2020. The AI was trained on thousands of Day 5 embryo images from multiple IVF laboratories in multiple countries, but was not trained on data used in this study. Participants/materials, setting, methods Average patient age was 36.2 years, and average embryo cohort size was 2.1/patient. PGT-A analysis was performed on embryos at time of evaluation. The dataset comprised 3,251 (59.4%) euploid embryos, 1,815 (33.2%) aneuploid embryos, and 403 (7.4%) mosaic embryos. The AI was retrospectively used to provide a score between 0 (predicted non-viable) and 10 (predicted viable) for each image. Correlation between the AI viability score and euploid, mosaic and aneuploid embryos was then assessed. Main results and the role of chance Results showed a statistically significant correlation between AI viability score and PGT-A outcome, consistent with a relationship between pregnancy outcome and ploidy status. The average score for euploid embryos was 8.20, which was significantly higher than the average score for aneuploid embryos of 7.80 (p &lt; 0.0001). There was a significant linear increase in confidence score from full aneuploid embryos, through mosaic embryos (average score 7.97), to full euploid embryos (mosaic threshold of 20–80%). High mosaic embryos tended to have a lower average score (7.60) than low mosaic embryos (7.96), consistent with correlation of viability (pregnancy outcome) with the degree of mosaicism. AI viability score also correlated with ploidy features believed to affect pregnancy outcomes. Trisomic changes had higher average scores than monosomic changes. Segmental changes had higher average scores than full gain or loss. The AI score differentiated euploid from aneuploid status more efficiently in embryos with poorer morphology than those with good morphology. Whilst there was an evident correlation between pregnancy outcome and ploidy status, the AI was only weakly predictive of euploidy, with an accuracy of 57.3% using an AI viability score threshold of 7.5/10.This suggests pregnancy-related morphological features are somewhat correlated with embryo ploidy, but not completely. Limitations, reasons for caution The PGT-A technique is held to have some limitations for evaluating ploidy status, therefore it would be of benefit to perform additional confirmatory studies on independent datasets. It would be of interest to conduct prospective studies evaluating correlations between the AI’s evaluation of morphology and pregnancy outcome with ploidy status. Wider implications of the findings: The AI score correlated with genetic features of embryos that are known to correlate with pregnancy, which further supports the efficacy and use of AI for embryo viability assessment. The AI identified morphological features that are somewhat predictive of ploidy status, with potential application to embryos of poorer Gardner score. Trial registration number none

scholarly journals Comparison of the predictive value of progesterone‐related indicators for pregnancy outcomes of women undergoing the short‐acting GnRH agonist long protocol: a retrospective study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yangyang Zhang ◽  
Yang Xu ◽  
Yuqiong Wang ◽  
Qing Xue ◽  
Jing Shang ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Gnrh Agonist ◽  
Pregnancy Outcomes ◽  
Predictive Value ◽  
Ovarian Response ◽  
Clinical Pregnancy ◽  
Short Acting ◽  
Good Quality Embryo ◽  
Response Group ◽  
Long Protocol

Abstract Background There are many progesterone (P) elevation-related indicators for predicting pregnancy outcomes, including the serum P, P-to-oestradiol ratio (P/E2), P-to-follicle index (PFI), and P-to-mature oocyte index (PMOI); however, due to inconsistencies in study populations and controlled ovarian hyperstimulation (COH) protocols among studies, these indicators are controversial. Moreover, no researchers have included these four commonly used indicators in one study to compare their predictive efficacies. The objective of this study was to compare the predictive value of P-related indicators for pregnancy outcomes of women undergoing the short-acting GnRH agonist long protocol. Methods A total of 612 infertile women undergoing IVF/ICSI were recruited for this study. Serum samples were obtained on the morning of HCG injection for serum P and E2 measurements. Transvaginal ultrasound was performed to determine the follicle count (≥ 14 mm in diameter). The number of mature oocytes was observed in the embryo laboratory after oocyte retrieval. Results In cases of P < 2.5 ng/ml, there was no significant difference in the serum P level or P/E2 between the pregnant group and the non-pregnant group. The PFI and PMOI of the pregnant group were significantly lower than those of the non-pregnant group. According to the stratified analysis of the ovarian response, only the PMI and PMOI of the pregnant women in the normal ovarian response group were lower than those of the non-pregnant women. To compare the predictive value of the PFI and PMOI in IVF/ICSI outcomes, the patients were divided into four groups. The good-quality embryo rate and clinical pregnancy rate were highest in Group A (low PFI and low PMOI) and lowest in Group D (high PFI and high PMOI). In the two groups with discordant PFI and PMOI, namely Group B (low PFI and high PMOI) and Group C (high PFI and low PMOI), the good-quality embryo rate and clinical pregnancy rate were not significantly different. Conclusions The PFI and PMOI had equal value in predicting clinical pregnancy outcomes in the normal ovarian response group undergoing the short-acting GnRH agonist long protocol. Each clinical centre can choose one of the indicators according to their actual situation in clinical practice and establish individual cut-off values for PFI and PMOI based on their own hormonal measurements.

scholarly journals Effect of blastocyst morphology and developmental speed on transfer strategy for grade “C” blastocyst in vitrified‐warmed cycles

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuxia He ◽  
Shiping Chen ◽  
Jianqiao Liu ◽  
Xiangjin Kang ◽  
Haiying Liu
Keyword(s):  
Pregnancy Rate ◽  
Live Birth ◽  
Pregnancy Outcomes ◽  
Multiple Pregnancy ◽  
Poor Quality ◽  
Clinical Pregnancy ◽  
Neonatal Outcomes ◽  
Blastocyst Transfer ◽  
Blastocyst Development ◽  
Multiple Pregnancy Rate

Abstract Background High-quality single blastocyst transfer (SBT) is increasingly recommended to patients because of its acceptable pregnancy outcomes and significantly reduced multiple pregnancy rate compared to double blastocyst transfer (DBT). However, there is no consensus on whether this transfer strategy is also suitable for poor-quality blastocysts. Moreover, the effect of the development speed of poor-quality blastocysts on pregnancy outcomes has been controversial. Therefore, this study aimed to explore the effects of blastocyst development speed and morphology on pregnancy and neonatal outcomes during the frozen embryo transfer (FET) cycle of poor-quality blastocysts and to ultimately provide references for clinical transfer strategies. Methods A total of 2,038 FET cycles of poor-quality blastocysts from patients 40 years old or less were included from January 2014 to December 2019 and divided based on the blastocyst development speed and number of embryos transferred: the D5-SBT (n = 476), D5-DBT (n = 365), D6-SBT (n = 730), and D6-DBT (n = 467) groups. The SBT group was further divided based on embryo morphology: D5-AC/BC (n = 407), D5-CA/CB (n = 69), D6-AC/BC (n = 580), and D6-CA /CB (n = 150). Results When blastocysts reach the same development speed, the live birth and multiple pregnancy rates of DBT were significantly higher than those of SBT. Moreover, there was no statistical difference in the rates of early miscarriage and live birth between the AC/BC and CA/CB groups. When patients in the SBT group were stratified by blastocyst development speed, the rates of clinical pregnancy (42.44 % vs. 20.82 %) and live birth (32.35 % vs. 14.25 %) of D5-SBT group were significantly higher than those of D6-SBT group. Furthermore, for blastocysts in the same morphology group (AC/BC or CA/CA group), the rates of clinical pregnancy and live birth in the D5 group were also significantly higher than those of D6 group. Conclusions For poor-quality D5 blastocysts, SBT can be recommended to patients because of acceptable pregnancy outcomes and significantly reduced multiple pregnancy rate compared with DBT. For poor-quality D6, the DBT strategy is recommended to patients to improve pregnancy outcomes. When blastocysts reach the same development speed, the transfer strategy of selecting blastocyst with inner cell mass “C” or blastocyst with trophectoderm “C” does not affect the pregnancy and neonatal outcomes.

scholarly journals Disruption of Ini1 Leads to Peri-Implantation Lethality and Tumorigenesis in Mice

2001 ◽  
Vol 21 (10) ◽  
pp. 3598-3603 ◽  
Author(s):  
Cynthia J. Guidi ◽  
Arthur T. Sands ◽  
Brian P. Zambrowicz ◽  
Tod K. Turner ◽  
Delia A. Demers ◽  
...  
Keyword(s):  
Tumor Suppressor ◽  
Germ Line ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Tumor Formation ◽  
Embryo Viability ◽  
Early Embryonic Lethality ◽  
Poorly Differentiated ◽  
Rhabdoid Tumors

ABSTRACT SNF5/INI1 is a component of the ATP-dependent chromatin remodeling enzyme family SWI/SNF. Germ line mutations ofINI1 have been identified in children with brain and renal rhabdoid tumors, indicating that INI1 is a tumor suppressor. Here we report that disruption of Ini1 expression in mice results in early embryonic lethality. Ini1-null embryos die between 3.5 and 5.5 days postcoitum, and Ini1-null blastocysts fail to hatch, form the trophectoderm, or expand the inner cell mass when cultured in vitro. Furthermore, we report that approximately 15% ofIni1-heterozygous mice present with tumors, mostly undifferentiated or poorly differentiated sarcomas. Tumor formation is associated with a loss of heterozygocity at the Ini1 locus, characterizing Ini1 as a tumor suppressor in mice. Thus, Ini1 is essential for embryo viability and for repression of oncogenesis in the adult organism.

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