Altered morphokinetics and differential reproductive outcomes associated with cell exclusion events in human embryos

RESEARCH QUESTION

Can embryos harbouring cell exclusion and their reproductive outcomes be classified based on morphokinetic profiles?

DESIGN

A total of 469 time-lapse videos of embryos transferred between 2013 and 2019 from a single clinic were analysed. Videos were assessed and grouped according to the presence or absence of one or more excluded cells before compaction. Cell division timings, intervals between subsequent cell divisions and dynamic intervals were analysed to determine the morphokinetic profiles of embryos with cell exclusion (CE+), compared with fully compacted embryos without cell exclusion or extrusion (CE-).

RESULTS

Transfer of CE+ embryos resulted in lower proportions of fetal heartbeat (FHB) and live birth compared with CE- embryos (both, P < 0.001). CE+ embryos were associated with delays in t2 (P = 0.030), t6 (P = 0.018), t7 (P < 0.001), t8 (P = 0.001), tSC (P < 0.001) and tM (P < 0.001). Earlier timings for t3 (P = 0.014) and t5 (P < 0.001) were positively associated with CE+; CE+ embryos indicated prolonged S2, S3, ECC3, cc2 and cc4. Logistic regression analysis revealed that t5, tM, S2 and ECC3 were the strongest predictive indicators of cell exclusion. Timings for S2 and ECC3 were useful in identifying increased odds of FHB when a cell exclusion event was present.

CONCLUSION

Embryos harbouring cell exclusion indicated altered morphokinetic profiles. Their overall lower reproductive success was associated with two morphokinetic parameters. Morphokinetic profiles could be used as adjunct indicators for reproductive success during cycles producing few, low-quality embryos. This may allow more objective identification of cell exclusion and refinement of embryo ranking procedures before transfer.

Sperm motility assessed by deep convolutional neural networks into WHO categories

Semen analysis is central in infertility investigation. Manual assessment of sperm motility according to the WHO recommendations is the golden standard, and extensive training is a requirement for accurate and reproducible results. Deep convolutional neural networks (DCNN) are especially suitable for image classification. In this study, we evaluated the performance of the DCNN ResNet-50 in predicting the proportion of sperm in the WHO motility categories. Two models were evaluated using tenfold cross-validation with 65 video recordings of wet semen preparations from an external quality assessment programme for semen analysis. The corresponding manually assessed data was obtained from several of the reference laboratories, and the mean values were used for training of the DCNN models. One model was trained to predict the three categories progressive motility, non-progressive motility, and immotile spermatozoa. Another model was used in predicting four categories, where progressive motility was differentiated into rapid and slow. The resulting average mean absolute error (MAE) was 0.05 and 0.07, and the average ZeroR baseline was 0.09 and 0.10 for the three-category and the four-category model, respectively. Manual and DCNN-predicted motility was compared by Pearson's correlation coefficient and by difference plots. The strongest correlation between the mean manually assessed values and DCNN-predicted motility was observed for % progressively motile spermatozoa (Pearson's r = 0.88, p < 0.001) and % immotile spermatozoa (r = 0.89, p < 0.001). For rapid progressive motility, the correlation was moderate (Pearson's r = 0.673, p < 0.001). The median difference between manual and predicted progressive motility was 0 and 2 for immotile spermatozoa. The largest bias was observed at high and low percentages of progressive and immotile spermatozoa. The DCNN-predicted value was within the range of the interlaboratory variation of the results for most of the samples. In conclusion, DCNN models were able to predict the proportion of spermatozoa into the WHO motility categories with significantly lower error than the baseline. The best correlation between the manual and the DCNN-predicted motility values was found for the categories progressive and immotile. Of note, there was considerable variation between the mean motility values obtained for each category by the reference laboratories, especially for rapid progressive motility, which impacts the training of the DCNN models.

VISEM-Tracking, a human spermatozoa tracking dataset

A manual assessment of sperm motility requires microscopy observation, which is challenging due to the fast-moving spermatozoa in the field of view. To obtain correct results, manual evaluation requires extensive training. Therefore, computer-aided sperm analysis (CASA) has become increasingly used in clinics. Despite this, more data is needed to train supervised machine learning approaches in order to improve accuracy and reliability in the assessment of sperm motility and kinematics. In this regard, we provide a dataset called VISEM-Tracking with 20 video recordings of 30 seconds (comprising 29,196 frames) of wet semen preparations with manually annotated bounding-box coordinates and a set of sperm characteristics analyzed by experts in the domain. In addition to the annotated data, we provide unlabeled video clips for easy-to-use access and analysis of the data via methods such as self- or unsupervised learning. As part of this paper, we present baseline sperm detection performances using the YOLOv5 deep learning (DL) model trained on the VISEM-Tracking dataset. As a result, we show that the dataset can be used to train complex DL models to analyze spermatozoa.

Standards in semen examination: publishing reproducible and reliable data based on high-quality methodology

Biomedical science is rapidly developing in terms of more transparency, openness and reproducibility of scientific publications. This is even more important for all studies that are based on results from basic semen examination. Recently two concordant documents have been published: the 6th edition of the WHO Laboratory Manual for the Examination and Processing of Human Semen, and the International Standard ISO 23162:2021. With these tools, we propose that authors should be instructed to follow these laboratory methods in order to publish studies in peer-reviewed journals, preferable by using a checklist as suggested in an Appendix to this article.

Association Study between Polymorphisms in DNA Methylation-Related Genes and Testicular Germ Cell Tumor Risk

BACKGROUND

Testicular germ cell tumors (TGCT), histologically classified as seminomas and nonseminomas, are believed to arise from primordial gonocytes, with the maturation process blocked when they are subjected to DNA methylation reprogramming. SNPs in DNA methylation machinery and folate-dependent one-carbon metabolism genes have been postulated to influence the proper establishment of DNA methylation.

METHODS

In this pathway-focused investigation, we evaluated the association between 273 selected tag SNPs from 28 DNA methylation-related genes and TGCT risk. We carried out association analysis at individual SNP and gene-based level using summary statistics from the Genome Wide Association Study meta-analysis recently conducted by the international Testicular Cancer Consortium on 10,156 TGCT cases and 179,683 controls.

RESULTS

In individual SNP analyses, seven SNPs, four mapping within MTHFR, were associated with TGCT risk after correction for multiple testing (q ≤ 0.05). Queries of public databases showed that three of these SNPs were associated with MTHFR changes in enzymatic activity (rs1801133) or expression level in testis tissue (rs12121543, rs1476413). Gene-based analyses revealed MTHFR (q = 8.4 × 10-4), methyl-CpG-binding protein 2 (MECP2; q = 2 × 10-3), and ZBTB4 (q = 0.03) as the top TGCT-associated genes. Stratifying by tumor histology, four MTHFR SNPs were associated with seminoma. In gene-based analysis MTHFR was associated with risk of seminoma (q = 2.8 × 10-4), but not with nonseminomatous tumors (q = 0.22).

CONCLUSIONS

Genetic variants within MTHFR, potentially having an impact on the DNA methylation pattern, are associated with TGCT risk.

IMPACT

This finding suggests that TGCT pathogenesis could be associated with the folate cycle status, and this relation could be partly due to hereditary factors.

A Role of the TEX101 Interactome in the Common Aetiology Behind Male Subfertility and Testicular Germ Cell Tumor

Patients who develop testicular germ cell tumours (TGCT) are at higher risk to be subfertile than the general population. The conditions are believed to originate during foetal life, however, the mechanisms behind a common aetiology of TGCT and male subfertility remains unknown. Testis-expressed 101 (TEX101) is a glycoprotein that is related to male fertility, and downregulation of the TEX101 gene was shown in pre-diagnostic TGCT patients. In this review, we summarize the current knowledge of TEX101 and its interactome related to fertility and TGCT development. We searched literature and compilation of data from curated databases. There are studies from both human and animals showing that disruption of TEX101 result in abnormal semen parameters and sperm function. Members of the TEX101 interactome, like SPATA19, Ly6k, PICK1, and ODF genes are important for normal sperm function. We found only two studies of TEX101 related to TGCT, however, several genes in its interactome may be associated with TGCT development, such as PLAUR, PRSS21, CD109, and ALP1. Some of the interactome members are related to both fertility and cancer. Of special interest is the presence of the glycosylphosphatidylinositol anchored proteins TEX101 and PRSS21 in basophils that may be coupled to the immune response preventing further development of TGCT precursor cells. The findings of this review indicate that members of the TEX101 interactome could be a part of the link between TGCT and male subfertility.

P–104 Assessment of sperm motility according to WHO classification using convolutional neural networks

Study question

How does convolutional neural network (CNN)-predicted sperm motility correlate with manual assessment according to the WHO guidelines.

Summary answer

CNN predicts sperm motility comparable to reference laboratories in the ESHRE-SIGA External Quality Assessment Programme for Semen Analysis.

What is known already

Manual sperm motility assessment according to WHO guidelines is regarded as the gold standard. To obtain reliable and reproducible results, comprehensive training is essential as well as running internal and external quality control. Prediction based on artificial intelligence can potentially transfer human-level performance into models that perform the task faster and can avoid human assessor variations. CNNs have been groundbreaking in image processing. To develop AI models with high predictive power, the data set used should be of high quality and sperm motility assessment based on WHO guidelines.

Study design, size, duration

Videos of 65 fresh semen samples obtained from the ESHRE-SIGA External Quality Assessment Programme for Semen Analysis (from the period 2006–2018) were used in the development of the model. One video was captured for each semen sample. Sperm motility data was obtained from manual assessment of the videos according to WHO criteria by reference laboratories in the programme. Rapid progressive motility was also included. Ten-fold cross-validation was used to compensate for the relatively small dataset.

Participants/materials, setting, methods

The mean values of the reference laboratories were used. Sparse optical flow of the sperm videos was generated from each second of each video and fed into a ResNet50 convolutional neural network. For training, Adam was used to optimize the weights and mean squared error (MSE) to measure loss. For baseline, ZeroR (pseudo regression) was performed. Results are reported as MAE. For correlation analysis, Pearson’s r was used.

Main results and the role of chance

Predicting sperm motility based on the optical flow generated from the videos, achieved an average MAE of 0.05 across progressive (0.06), non-progressive (0.04) and immotile sperm (0.05). The ZeroR baseline was 0.09, indicating that the method is able to capture the movement of the spermatozoa and predict motility with low error. Pearson’s correlation between manually and AI-predicted motility showed r of 0.88, p &lt; 0.001 for progressive, 0.59, p &lt; 0.001 for non-progressive and 0.89, p &lt; 0.001 for immotile sperm. When predicting rapid progressive motility, the average MAE was 0.07 across rapid progressive (0.11), slow progressive (0.09), non-progressive (0.04) and immotile sperm (0.05). Pearson’s correlation analysis between manually and AI-predicted motility showed r of 0.67, p &lt; 0.001 for rapid progressive, 0.41, p &lt; 0.001 for slow progressive, 0.51, p &lt; 0.001 for non-progressive and 0.88, p &lt; 0.001 for immotile sperm. The results show that differentiating between rapid progressive and slow progressive motility is difficult, but the model is still able to do this better than the ZeroR baseline, which was 0.15 for rapid progressive and 0.11 for slow progressive. This is interesting since rapid progressive motility has been regarded challenging to assess. The next step would be to compare the results of the algorithm to the human performance.

Limitations, reasons for caution

The sample size is small. The model is based on videos of high quality, and the performance may not transfer well to videos of lower quality. The performance for rapid progressive motility, which may have an important clinical value, has to be improved.

Wider implications of the findings: This CNN model has a potential to assess sperm motility according to WHO guidelines for progressive motility and immotility. The error values for the automatic predictions are low, and the model shows a good performance taking into account that only videos were used to perform the prediction.

Trial registration number

Not applicable

P–029 Identification of spermatozoa by unsupervised learning from video data

Study question

Can artificial intelligence (AI) algorithms identify spermatozoa in a semen sample without using training data annotated by professionals?

Summary answer

Unsupervised AI methods can discriminate the spermatozoon from other cells and debris. These unsupervised methods may have a potential for several applications in reproductive medicine.

What is known already

Identification of individual sperm is essential to assess a given sperm sample’s motility behaviour. Existing computer-aided systems need training data based on annotations by professionals, which is resource demanding. On the other hand, data analysed by unsupervised machine learning algorithms can improve supervised algorithms that are more stable for clinical applications. Therefore, unsupervised sperm identification can improve computer-aided sperm analysis systems predicting different aspects of sperm samples. Other possible applications are assessing kinematics and counting of spermatozoa.

Study design, size, duration

Three sperm-like paint images were manipulated using a graphic design tool and used to train our AI system. Two paintings have an ash colour background and randomly distributed white colour circles, and one painting has a predefined pattern of circles. Selected semen sample videos from a public dataset with videos obtained from 85 participants were used to test our AI system.

Participants/materials, setting, methods

Generative adversarial networks (GANs) have become common AI methods to process data in an unsupervised way. Based on single image frames extracted from videos, a GAN (SinGAN) can be trained to determine and track locations of sperms by translating the real images into localization paintings. The resulting model showed the potential of identifying the presence of sperms without any prior knowledge about data.

Main results and the role of chance

Visual comparisons of localization paintings to real sperm images show that inverse training of SinGANs can track sperms. Converting colour frames into grayscale frames and using grayscale synthetic sperm-like frames showed the best visual quality of generated localization paintings of sperm frames. Feeding real sperm video frames to the SinGAN at different scaling factors, which is defining the resolution of the input image, showed different quality levels of generated sperm localization paintings. A sperm frame given to the algorithm with a scaling factor of one leads to random sperm tracking, while the scales two to four result in more accurate localization maps than scaling levels five to eight. In contrast, scales from six to eight result in an output close to the input frame. The proposed method is robust in terms of the number of spermatozoa, meaning that the detection works well for samples with a low or high sperm count. For visual comparisons, visit our Github page: https://vlbthambawita.github.io/singan-sperm/. The sperm tracking speed of our SinGAN using an NVIDIA 1080 graphic processing unit, is around 17 frames per second, which can be improved by using parallel video processing capabilities. This shows the capability of using this method for real-time analysis.

Limitations, reasons for caution

Unsupervised methods are hard to train, and the results need human verification. The proposed method will need quality control and must be standardized. Unsupervised sperm tracking SinGAN may identify blurry bright spots as non-existing sperm heads which may restrict the use of SinGAN sperm tracking for sperm counting.

Wider implications of the findings: Assessment of semen samples according to the WHO guidelines is subjective and resource-demanding. This unsupervised model might be used to develop new systems for less time-consuming and more accurate evaluation of semen samples. It may also be used for real-time analysis of prepared spermatozoa for use in assisted reproduction technology.

Trial registration number

N/A

Artificial intelligence in the fertility clinic: status, pitfalls and possibilities

In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively used in medical practice and may become a promising tool to improve success rates with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.

Identification of 22 susceptibility loci associated with testicular germ cell tumors

Testicular germ cell tumors (TGCT) are the most common tumor in young white men and have a high heritability. In this study, the international Testicular Cancer Consortium assemble 10,156 and 179,683 men with and without TGCT, respectively, for a genome-wide association study. This meta-analysis identifies 22 TGCT susceptibility loci, bringing the total to 78, which account for 44% of disease heritability. Men with a polygenic risk score (PRS) in the 95th percentile have a 6.8-fold increased risk of TGCT compared to men with median scores. Among men with independent TGCT risk factors such as cryptorchidism, the PRS may guide screening decisions with the goal of reducing treatment-related complications causing long-term morbidity in survivors. These findings emphasize the interconnected nature of two known pathways that promote TGCT susceptibility: male germ cell development within its somatic niche and regulation of chromosomal division and structure, and implicate an additional biological pathway, mRNA translation.

Serum RNA Profiling in the 10-Years Period Prior to Diagnosis of Testicular Germ Cell Tumor

Although testicular germ cell tumor (TGCT) overall is highly curable, patients may experience late effects after treatment. An increased understanding of the mechanisms behind the development of TGCT may pave the way for better outcome for patients. To elucidate molecular changes prior to TGCT diagnosis we sequenced small RNAs in serum from 69 patients who were later diagnosed with TGCT and 111 matched controls. The deep RNA profiles, with on average 18 million sequences per sample, comprised of nine classes of RNA, including microRNA. We found that circulating RNA signals differed significantly between cases and controls regardless of time to diagnosis. Different levels of TSIX related to X-chromosome inactivation and TEX101 involved in spermatozoa production are among the interesting findings. The RNA signals differed between seminoma and non-seminoma TGCT subtypes, with seminoma cases showing lower levels of RNAs and non-seminoma cases showing higher levels of RNAs, compared with controls. The differentially expressed RNAs were typically associated with cancer related pathways. Our results indicate that circulating RNA profiles change during TGCT development according to histology and may be useful for early detection of this tumor type.

Cisplatin treatment of testicular cancer patients introduces long-term changes in the epigenome

BACKGROUND

Cisplatin-based chemotherapy (CBCT) is part of standard treatment of several cancers. In testicular cancer (TC) survivors, an increased risk of developing metabolic syndrome (MetS) is observed. In this epigenome-wide association study, we investigated if CBCT relates to epigenetic changes (DNA methylation) and if epigenetic changes render individuals susceptible for developing MetS later in life. We analyzed methylation profiles, using the MethylationEPIC BeadChip, in samples collected ~ 16 years after treatment from 279 Norwegian TC survivors with known MetS status. Among the CBCT treated (n = 176) and non-treated (n = 103), 61 and 34 developed MetS, respectively. We used two linear regression models to identify if (i) CBCT results in epigenetic changes and (ii) epigenetic changes play a role in development of MetS. Then we investigated if these changes in (i) and (ii) links to genes, functional networks, and pathways related to MetS symptoms.

RESULTS

We identified 35 sites that were differentially methylated when comparing CBCT treated and untreated TC survivors. The PTK6-RAS-MAPk pathway was significantly enriched with these sites and infers a gene network of 13 genes with CACNA1D (involved in insulin release) as a network hub. We found nominal MetS-associations and a functional gene network with ABCG1 and NCF2 as network hubs.

CONCLUSION

Our results suggest that CBCT has long-term effects on the epigenome. We could not directly link the CBCT effects to the risk of developing MetS. Nevertheless, since we identified differential methylation occurring in genes associated with conditions pertaining to MetS, we hypothesize that epigenomic changes may also play a role in the development of MetS in TC survivors. Further studies are needed to validate this hypothesis.

miRNA-302s may act as oncogenes in human testicular germ cell tumours

Testicular germ cell tumour (TGCT) represents the most common malignancy in young men in large parts of the world, but the aetiology is yet unclear. Multiple TGCT susceptibility loci have been identified, and we have shown that one of these, SPRY4, may act as a TGCT oncogene. Furthermore, many of the loci are in non-coding regions of the genome. miRNAs, a class of non-coding RNAs may play a crucial role in cell proliferation, differentiation, and apoptosis, and alteration in their expression may lead to oncogenesis. Differential expression of miRNAs in TGCT and normal testis has been reported in previous studies. In this study, we used qPCR to analyse, in normal and malignant testis tissue, the expression of the ten miRNAs that we had previously identified by sequencing to be the most upregulated in TGCT. We found high expression of these miRNAs also by qPCR analysis. The levels of miR-302a-3p, miR-302b-3p, and miR-302c-3p were downregulated after treatment of the TGCT cell lines NT2-D1 and 833 K with the chemotherapy drug cisplatin. By using miRNA inhibitor-mediated transient transfection, we inhibited the expression of the three members of miR-302 family (miR-302s). Inhibition of miR-302s resulted in a decreased cell proliferation in NT2-D1 cells, but not in 833 K cells. In both cell lines, inhibition of miR-302s resulted in decreased expression of SPRY4, which we have previously shown to regulate MAPK/ERK and PI3K/Akt signalling pathways in these cells. Inhibition of miR-302b-3p and miR-302c-3p decreased phosphorylation of ERK1/2, whereas inhibition of miR-302a-3p and miR-302b-3p led to decreased expression of the apoptosis inhibitor, survivin. Our findings suggest that miR-302s act as TGCT oncogenes by inducing the expression of SPRY4 and activating MAPK/ERK pathway while inhibiting apoptosis via increased survivin expression.

Association between semen parameters and chance of fatherhood - a long-term follow-up study

BACKGROUND

Evaluation of male fertility includes standard semen analysis; however, there is uncertainty about the value of sperm parameters in predicting fertility.

OBJECTIVE

To evaluate the association between semen parameters and fatherhood during a long-time period.

MATERIALS AND METHODS

Semen parameters (total sperm count, concentration, motility, and morphology) and sperm DNA fragmentation Index (DFI) assessed on samples collected from 195 Norwegian men from the general population in 2001/2002 were matched with information about fatherhood until 2015, obtained from the Medical Birth Register. The parameters were dichotomized as normal vs. abnormal according to the WHO reference values from 1999 and 2010. Cut-offs at 20% and 30% were used for DFI.

RESULTS

Among men who had no children before 2003, those with normal progressive sperm motility had more often become fathers (WHO 1999, cut-off ≥50%, adjusted OR 2.8, 95% CI 1.3-6.1 and WHO 2010, cut-off ≥32%; aOR 4.2, 95% CI 1.1-15). Based on the WHO 1999 reference value, men with normal sperm concentration (≥20 × 10⁶ /mL) had more often become fathers (aOR 3.1, 95% CI 1.1-8.6). Men with progressive sperm motility ≥50% and concentration ≥20 × 10⁶ /mL did more often achieve fatherhood (aOR 8.4, 95% CI 2.1-34). For DFI, there was a borderline significance at cut-off 20% in the group of men who had ever been fathers (OR 2.7, 95% CI 1.0-7.0 p < 0.05).

DISCUSSION

The results indicate that sperm progressive motility, sperm concentration, and DFI are associated with fatherhood during a longer time period, with sperm motility being most consistent. Although the sample size is relatively small and our results should be replicated in larger studies, they may be of clinical relevance.

CONCLUSION

Semen parameters may have a diagnostic value not only in a short time frame but also for predicting future fertility potential.

Abstract 4325: Cisplatin treatment of testicular cancer introduces long-term changes to the epigenome

Testicular cancer (TC) survival rates have increased substantially over the last decades, largely due to the introduction of cisplatin (CP) chemotherapy. This treatment is, however, associated with increased risk of developing metabolic syndrome (MetS), defined according to the National Cholesterol Education Program. We aimed to investigate if CP treatment were associated with epigenetic changes, and whether these changes render TC survivors susceptible for developing MetS later in life.

We included 279 Norwegian TC survivors with and without CP treatment and MetS, matched on age at blood sampling (Table 1). The TC survivors were re-examined on average 16 years after the orchiectomy, and for some patients, CP treatment. Whole genome DNA methylation profiles were measured with MethylationEPIC BeadChip and analyzed with the R package minfi. We used a linear regression model adjusting for smoking, age and cell type composition to identify CP differentially methylated CpG sites and logistic regression adjusting for smoking and age to identify differentially methylated CpG sites associated with MetS. Gene enrichment analyses were based on Fisher's exact test using KEGG and Reactome pathways.

32 and 15 differentially methylated CpG sites were associated with CP treatment after adjusting for multiple testing with False Discovery Rate (FDR) and Bonferroni correction, respectively. The PTK6-RAS-MAPk pathway was significantly enriched with the FDR significant CpGs (p-value &lt; 0.1). We could not identify FDR significant differentially methylated CpGs associated with MetS with our sample size.

In conclusion, our results suggest that CP treatment has long-term effects on the epigenome. Genes involved in double-strand break repair, consistent with the cytotoxicity of CP treatment, are among the differentially methylated CpGs. Our top list of differentially methylated CpGs associated with MetS (lowest unadjusted p-values), should be further explored in a larger sample set of TC survivors.

Table 1: Overview of sample characteristicsCP+ MetS+CP- MetS+CP+ MetS-CP- MetS-N613411569Mean age at surgery31312730Mean age at sample collection49484443Time between surgery and sample collection17181714

Citation Format: Trine B. Rounge, Cecilie Bucher-Johannessen, Christian M. Page, Trine B. Haugen, Sophie D. Fosså, Hege S. Haugnes, Tom Grotmol. Cisplatin treatment of testicular cancer introduces long-term changes to the epigenome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4325.

Knockdown of SPRY4 and SPRY4-IT1 inhibits cell growth and phosphorylation of Akt in human testicular germ cell tumours

Testicular germ cell tumour (TGCT) is the most common cancer in young men in large parts of the world, but the aetiology is mainly unknown. Genome-wide association studies have so far identified about 50 susceptibility loci associated with TGCT, including SPRY4. SPRY4 has shown tumour suppressor activity in several cancer cells, such as lung and prostate, while it was found to act as an oncogene in ovarian cancer. An intronic region within the SPRY4 gene produces a long non-coding RNA, SPRY4-IT1, which has been reported to act as an oncogene in melanoma, breast cancer, and colorectal cancer, and as a tumour suppressor in lung cancer. The roles of SPRY4 and SPRY4-IT1 in TGCT development are yet unknown. We found higher expression levels of SPRY4, both mRNA and protein, and of SPRY4-IT1 in human TGCT than in normal adult testis. Small-interfering RNA (siRNA)-mediated transient knockdown of SPRY4 and SPRY4-IT1 in two TGCT cell lines 833 K and NT2-D1 resulted in decreased cell growth, migration, and invasion. Knockdown of SPRY4 and SPRY4-IT1 also led to a significant reduction in the phosphorylation of Akt. Our findings indicate that SPRY4 and SPRY4-IT1 may act as oncogenes in TGCTs via activation of the PI3K / Akt signalling pathway.

Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor

Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Defective microtubule assembly and dysregulation of KIT-MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

Meta-analysis of five genome-wide association studies identifies multiple new loci associated with testicular germ cell tumor

The international Testicular Cancer Consortium (TECAC) combined five published genome-wide association studies of testicular germ cell tumor (TGCT; 3,558 cases and 13,970 controls) to identify new susceptibility loci. We conducted a fixed-effects meta-analysis, including, to our knowledge, the first analysis of the X chromosome. Eight new loci mapping to 2q14.2, 3q26.2, 4q35.2, 7q36.3, 10q26.13, 15q21.3, 15q22.31, and Xq28 achieved genome-wide significance (P < 5 × 10-8). Most loci harbor biologically plausible candidate genes. We refined previously reported associations at 9p24.3 and 19p12 by identifying one and three additional independent SNPs, respectively. In aggregate, the 39 independent markers identified to date explain 37% of father-to-son familial risk, 8% of which can be attributed to the 12 new signals reported here. Our findings substantially increase the number of known TGCT susceptibility alleles, move the field closer to a comprehensive understanding of the underlying genetic architecture of TGCT, and provide further clues to the etiology of TGCT.

Seasonal fluctuation in the secretion of the antioxidant melatonin is not associated with alterations in sperm DNA damage

A high sperm DNA fragmentation index (DFI) is associated with reduced fertility. DFI is influenced by the balance between reactive oxygen species and antioxidants. A circannual variation in melatonin, an antioxidant and free radical scavenger, could thus impact semen quality and fertility. The association between the major melatonin metabolite, urine 6-sulfatoxymelatonin (aMT6s), and DFI was analyzed in 110 Oslo men (south of the Arctic Circle) and 86 Tromsoe men (north of the Arctic Circle). Two semen analyses, summer and winter, and four urine samples (early/late summer; early/late winter), were analyzed. The associations between aMT6s in urine and DFI were characterized in a cross-sectional and longitudinal manner using correlation analysis and linear regression. Regardless of season and location, no significant correlations between aMT6s and DFI were observed. The correlation coefficients for associations between changes over time (early winter–early summer) in aMT6s and DFI were for the total cohort: rho = −0.08 (P = 0.322), for the Oslo cohort: rho = −0.07 (P = 0.485), and for the Tromsoe cohort: rho = −0.14 (P = 0.273), respectively. Similar results were seen when comparing late winter and late summer. There was no any statistically significant correlation between changes over time in aMT6s and DFI for men with DFI below and above the median value (10%), respectively. The seasonal variation in melatonin excretion seems not to have any impact on DFI.

Fatty acid composition of spermatozoa is associated with BMI and with semen quality

High body mass index (BMI) is negatively associated with semen quality. In addition, the composition of fatty acids of spermatozoa has been shown to be important for their function. The aim of the study was to examine the association between BMI and the composition of spermatozoa fatty acids in men spanning a broad BMI range. We also analysed the relation between fatty acid composition of spermatozoa and semen characteristics, and the relationship between serum fatty acids and spermatozoa fatty acids. One hundred forty-four men with unknown fertility status were recruited from the general population, from couples with identified female infertility and from morbid obesity centres. Standard semen analysis (WHO) and sperm DNA integrity (DFI) analysis were performed. Fatty acid compositions were assessed by gas chromatography. When adjusted for possible confounders, BMI was negatively associated with levels of sperm docosahexaenoic acid (DHA) (p < 0.001) and palmitic acid (p < 0.001). The amount of sperm DHA correlated positively with total sperm count (r = 0.482), sperm concentration (r = 0.469), sperm vitality (r = 0.354), progressive sperm motility (r = 0.431) and normal sperm morphology (r = 0.265). A negative association was seen between DHA levels and DNA fragmentation index (r = -0.247). Levels of spermatozoa palmitic acid correlated positively with total sperm count (r = 0.227), while levels of linoleic acid correlated negatively (r = -0.254). When adjusted for possible confounders, only the levels of arachidonic acid showed positive correlation between spermatozoa and serum phospholipids (r = 0.262). Changes in the fatty acid composition of spermatozoa could be one of the mechanisms underlying the negative association between BMI and semen quality. The relationship between fatty acids of spermatozoa and serum phospholipids was minor, which indicates that BMI affects fatty acid composition of spermatozoa through regulation of fatty acid metabolism in the testis. The role of dietary intake of fatty acids on the spermatozoa fatty acid composition remains to be elucidated.

Identification of Endogenous Controls for Use in miRNA Quantification in Human Cancer Cell Lines

BACKGROUND

miRNAs play important roles in multiple biological processes, and deregulation has been linked to several human diseases, including cancer. Studying changes in miRNA expression in cancer development is commonly performed in vitro in human cancer cell lines using quantitative polymerase chain reaction (qPCR), a method requiring the use of a robust reference gene that displays stable expression across all samples.

MATERIALS AND METHODS

Using the NormFinder software, a selection of commonly used endogeneous controls and miRNAs were tested in six human cancer cell lines to identify for the most suitable gene for use as a reference.

RESULTS

The frequently used endogenous control U6B small nuclear RNA (RNU6B) was found to be an unsuitable reference for normalization. The most suitable single endogeneous control identified was miR-25-3p, whereas the best combination of two endogeneous controls was miR-25-3p and miR-93-5p.

CONCLUSION

We identified a single and a pair of miRNAs suitable for use as endogenous controls when performing qPCR-based miRNA expression analyses in human cancer cell lines.

Profiling of the small RNA populations in human testicular germ cell tumors shows global loss of piRNAs

Background

Small non-coding RNAs play essential roles in gene regulation, however, the interplay between RNA groups, their expression levels and deregulations in tumorigenesis requires additional exploration. In particular, a comprehensive analysis of microRNA (miRNA), PIWI-interacting RNAs (piRNAs), and tRNA-derived small RNAs in human testis and testicular germ cell tumor (TGCT) is lacking.

Results

We performed small RNA sequencing on 22 human TGCT samples from 5 histological subtypes, 3 carcinoma in situ, and 12 normal testis samples. miRNA was the most common group among the sequences 18–24 nt in length and showed histology-specific expression. In normal samples, most sequences 25–31 nucleotides in length displayed piRNA characteristics, whereas a large proportion of the sequences 32–36 nt length was derived from tRNAs. Expression analyses of the piRNA population demonstrated global loss in all TGCT subtypes compared to normal testis. In addition, three 5′ small tRNA fragments and 23 miRNAs showed significant (p < 10⁻⁶) differential expression in cancer vs normal samples.

Conclusions

We have documented significant changes in the small RNA populations in normal adult testicular tissue and TGCT samples. Although components of the same pathways might be involved in miRNA, piRNA and tRNA-derived small RNA biogenesis, our results showed that the response to the carcinogenic process differs between these pathways, suggesting independent regulation of their biogenesis. Overall, the small RNA deregulation in TGCT provides new insight into the small RNA interplay.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-015-0411-4) contains supplementary material, which is available to authorized users.

Abstract 842: Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor

Genome-wide association (GWA) studies have reported 19 distinct susceptibility loci for testicular germ cell tumor (TGCT). The aim of the present study was to identify additional loci and gene sets associated with susceptibility to TGCT. A GWA study for TGCT was performed by genotyping 610,240 single nucleotide polymorphisms (SNPs) in 1,326 cases and 6,687 controls from Sweden and Norway. We put forward 34 SNPs from 17 novel regions and 11 SNPs previously reported, for replication in 710 case-parent triads and 289 cases and 290 controls. Predefined biological pathways and processes, in addition to a custom-built sex determination gene set, were subject to enrichment analyses using Meta-Analysis Gene Set Enrichment of Variant Associations (M) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (I). In the combined meta-analysis, we observed genome-wide significant association for rs7501939 on chromosome 17q12 (OR = 1.29, 95% CI = 1.19-1.40, P = 1.1 × 10-9) and rs2195987 on chromosome 19p12 (OR = 1.31, 95% CI: 1.19-1.45, P = 3.2 × 10-8). The marker rs7501939 on chromosome 17q12 is located in an intron of the HNF1B gene, encoding a member of the homeodomain-containing superfamily of transcription factors. The sex determination gene set (FDRM &lt; 0.001, FDRI &lt; 0.001) and pathways related to NF-κB, glycerophospholipid and ether lipid metabolism, as well as cancer and apoptosis, was associated with TGCT (FDR &lt; 0.1). In addition to revealing two new TGCT susceptibility loci, our results support the notion that genes governing normal germ cell development in utero are implicated in the development of TGCT.

Citation Format: Tom Grotmol, Wenche Kristiansen, Robert Karlsson, Trine B. Rounge, Thomas Whitington, Bettina K. Andreassen, Patrik KE Magnusson, Hans-Olov Adami, Clare Turnbull, Trine B. Haugen, Fredrik Wiklund. Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 842. doi:10.1158/1538-7445.AM2015-842

Abstract 843: Imputation and meta-analysis of five genome-wide association studies identify multiple new loci associated with testicular germ cell tumor

Genome-wide association studies (GWAS) have already identified 21 genetic loci associated with testicular germ cell tumor (TGCT). Many of the loci contain biologically plausible genes that function in male germ cell maturation and differentiation, as well as KIT-MAPK signaling and chromosomal segregation. We recently formed the international TEsticular CAncer Consortium (TECAC), and pooled data from the three published and one unpublished GWAS (3,556 TGCT cases and 13,969 controls) to identify additional novel susceptibility loci. We imputed across the data set using the 1,000 Genomes Project version 3 and conducted a fixed effects meta-analysis, including the first analysis of the X chromosome. Eleven new loci achieved genome-wide significance level (p&lt;5e-8), mapping to the following regions: 2q14.2, 3q26.2, 4q35.2, 7q36.3, 10q26.13, 15q21.3, 15q22.31, 16q24.2, 17q12, 19p12 and Xq28, most of which harbor biologically plausible genes. The per allele odds ratios associated with these SNPs continue to be higher than those associated with other cancer types, ranging from 1.2 to 1.6. The signal at 17q12 maps to a region which includes HNF1B, a locus already associated with risk of endometrial and prostate cancer. Two of the signals are in the introns of genes known to be involved in embryonal stem cell pluripotency (TFCLP1 - 2q14.2 and ZFPA2/REX1 - 4q35.2), one in the intron of a chromosomal segregation gene (NCAPG - 27q36.3), and one proximate to MEK1 (MAP2K1 - 15q22.31). The identification of these loci provides additional evidence of the importance of the previously implicated biological pathways. Heritability analysis indicated that these eleven new loci explain approximately 7% more familial (father-to-son) risk in addition to ∼26% explained by previously established 21 loci. Our new findings substantially increase the number of known TGCT susceptibility alleles, thus moving the field closer to a comprehensive understanding of the underlying genetic architecture of TGCT, and providing further clues into the biological etiology of TGCT.

Citation Format: Zhaoming Wang, Peter A. Kanetsky, Katherine A. McGlynn, D. Timothy Bishop, Charles C. Chung, Marlene D. Dalgaard, Tom Grotmol, Mark H. Greene, Ramneek Gupta, Trine B. Haugen, Kevin Litchfield, Jennifer T. Loud, Nandita Mitra, Kasper Nielsen, Clare Turnbull, Ewa Rajpert-DeMeyts, Saran Vardhanabhuti, Fredrik Wiklund, Stephen Schwartz, Stephen J. Chanock, Katherine L. Nathanson, TECAC consortium. Imputation and meta-analysis of five genome-wide association studies identify multiple new loci associated with testicular germ cell tumor. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 843. doi:10.1158/1538-7445.AM2015-843