Literature DB >> 33037172

Characterization of progression-related alternative splicing events in testicular germ cell tumors.

Chuan-Jie Zhang1, Zong-Tai Li2, Kan-Jie Shen3, Lu Chen1, Dan-Feng Xu1, Yi Gao1.   

Abstract

Accumulating evidence supports the significance of aberrant alternative splicing (AS) events in cancer; however, genome-wide profiling of progression-free survival (PFS)-related AS events in testicular germ cell tumors (TGCT) has not been reported. Here, we analyzed high-throughput RNA-sequencing data and percent-spliced-in values for 150 patients with TGCT. Using univariate and multivariate Cox regression analysis and a least absolute shrinkage and selection operator method, we identified the top 15 AS events most closely associated with disease progression. A risk-associated AS score (ASS) for the 15 AS events was calculated for each patient. ASS, pathological stage, and T stage were significantly associated with disease progression by univariate analysis, but only ASS and pathological stage remained significant by multivariate analysis. The ability of these variables to predict 5-year progression was assessed using receiver operating characteristic curve analysis. ASS had stronger predictive value than a combination of age, pathological stage, and T stage (area under the curve = 0.899 and 0.715, respectively). Furthermore, Kaplan-Meier analysis of patients with low and high ASS demonstrated that high ASS was associated with significantly worse PFS than low ASS (P = 1.46 × 10-7). We also analyzed the biological functions of the PFS-related AS-related genes and found enrichment in pathways associated with DNA repair and modification. Finally, we identified a regulatory network of splicing factors with expression levels that correlated significantly with AS events in TGCT. Collectively, this study identifies a novel method for risk stratification of patients and provides insight into the molecular events underlying TGCT.

Entities:  

Keywords:  alternative splicing events; network; progression-free survival-related model; testicular germ cell tumor

Mesh:

Year:  2021        PMID: 33037172      PMCID: PMC8152425          DOI: 10.4103/aja.aja_30_20

Source DB:  PubMed          Journal:  Asian J Androl        ISSN: 1008-682X            Impact factor:   3.285


INTRODUCTION

Testicular cancer (TC), in which malignant cells form in the tissues of one or both testicles, has an annual incidence of approximately 1% among all newly diagnosed cancers in males.1 The most common form of TC is testicular germ cell tumors (TGCT), accounting for >95% of cases, which consist of seminoma and nonseminoma subtypes.2 The overall mortality rate of TGCT remains high due to its propensity to recur and form metastases. Over the past few decades, the main treatment strategy for decreasing the risk of relapse of TGCT has been retroperitoneal lymph node dissection;3 however, in recent years an advanced multidisciplinary approach combining surgical intervention with adjuvant chemotherapy or radiotherapy has improved the prognosis of patients with TC significantly, resulting in a 5-year survival rate of >95%.45 Nevertheless, the overall incidence of TC is still increasing worldwide. Patients with a history of TC have a 2% increased risk of advanced tumor in the contralateral testis within 15 years of diagnosis.6 Other studies have identified a number of risk factors, including environmental, hormonal, and genetic factors, that contribute alone or in combination to the development or recurrence of TC.78 However, there is a pressing need to understand the underlying molecular basis of TGCT, not only to elucidate the potential carcinogenic mechanisms but also to identify effective biomarkers for monitoring the risk for TGCT or its progression and prognosis. In recent years, increasing attention has been paid to the influence of aberrant epigenetic regulation, which integrates both environmental and genetic factors, on the risk of cancer development and progression. More than 95% of human genes undergo alternative splicing (AS) as a normal physiological process to generate protein diversity.9 As a vital post-transcriptional regulatory process, AS has the potential to generate mRNA isoforms that could play a potential pathogenic role in many diseases, including cancer.10 Indeed, emerging evidence suggests a close relationship between dysregulation of AS and tumor progression and recurrence, treatment resistance, and other oncogenic mechanisms.11 Recently, Xing et al.12 identified an oncogenic role for the exonuclease DIS3L2, which contributed to the progression of liver cancer via regulation of heterogeneous nuclear ribonucleoprotein U (hnRNPU)-mediated AS. Moreover, the development of advanced high-throughput sequencing technology has allowed AS events to be profiled and successfully identified as PFS-related markers in many malignancies, including lung, ovarian, hepatocellular, and kidney cancer.13141516 Nevertheless, no genome-wide screening of progression-related AS events have been performed in TGCT, and little is known about the activity of potential TGCT-related splice variants. In this study, we reported the first genome-wide profiling of AS events in TGCT. Using a 150-patient dataset from The Cancer Genome Atlas (TCGA) and the TCGA SpliceSeq dataset, we systematically analyzed the association between TGCT-specific AS events and disease progression and survival outcomes. We identified a robust AS score (ASS) based on the top 15 significant progression-free survival (PFS)-related AS events, and demonstrated its ability to predict the risk of 5-year progression. We also performed gene enrichment analysis and established a TGCT-specific regulatory network of AS events and the associated splicing factors (SF). Thus, this study sheds light on the molecular events underlying TGCT and identifies several PFS-related AS events that play potentially important roles in the progression of TGCT.

MATERIALS AND METHODS

Data acquisition and preprocessing

We obtained a dataset for 150 TGCT patients with corresponding clinical data and transcriptome profiles from TCGA (https://portal.gdc.cancer.gov/). Since the whole sequencing data of patients was obtained from the TCGA dataset, and it was unnecessary to provide the relevant ethics profiles. The expression data were quantified and normalized using the edgeR package. The TCGA SpliceSeq tool, run on a Java platform, was used to provide a comprehensive view of AS profiles in the TGCT patient cohort.17 The percent-spliced-in (PSI) value were derived to quantify AS events in each patient sample and was calculated as: PSI = splice_in/(splice_in + splice_out), with a value range of 0 to 1. We defined the filter cutoff that the percentage of samples with PSI should be more than 75% and correctly calculated the seven types of AS events, including alternate acceptor site (AA), alternate donor site (AD), alternate promoter (AP), alternate terminator (AT), exon skip (ES), mutually exclusive exons (ME), and retained intron (RI). Each AS event was annotated using the gene symbol, the AS_id number in the SpliceSeq database, and the splicing category. The clinical data for 134 patients were extracted using Perl scripts and consisted of age, gender, pathological stage, and American Joint Committee on Cancer Tumor-Node-Metastasis stages.

Identification of PFS-related AS events and functional gene enrichment analysis

The PSI data from TGCT cohort were transformed into a single matrix and merged with the survival data. To comprehensively illustrate interactions between the seven AS types, we generated UpSet plots with UpSetR package (https://github.com/hms-dbmi/UpSetR) to display five or more interactive sets.18 The impute R package was then used to interpolate the missing values using the K-nearest neighbor (KNN) algorithm.19 We then designed a “for cycle” script based on the R survival package to conduct univariate Cox analysis for each AS event, with statistical significance defined as P < 0.01. Total PFS-related AS events were displayed in UpSet plots and Volcano plots created using the ggplot2 package (https://ggplot2.tidyverse.org/). A pie chart of AS event frequency for each AS category was constructed. The top 20 individual AS events in each category were presented as dot plots. The biological functions of the parent genes with progression-associated AS events were investigated using gene ontology (GO) analysis with the terms biological process, cellular component, and molecular function. Genes with a false discovery rate of <0.05 were considered to be significantly enriched. The network of enriched terms was constructed using the Metascape tool (https://metascape.org).20

Construction of progression-related AS signature for TGCT patients

The least absolute shrinkage and selection operator (LASSO) method was used to further screen the significant progression-related AS events using the glmnet and survival packages (https://www.rdocumentation.org/packages/glmnet/versions/3.0-2). The overall ASS was calculated using a multivariate Cox regression method: ASS = ∑(SPIi ×βi), where βi represents the coefficient of each of the 15 AS events. Receiver operating characteristic (ROC) curves were generated and the area under the curve (AUC) was calculated to assess the predictive value of the ASS for 5-year tumor progression. The ASS was calculated for each patient, and the median score was used to dichotomize the 150-patient cohort into high and low ASS groups. The PFS survival of the two groups was compared using Kaplan–Meier analysis with a log-rank test. The predictive significance of ASS was also compared with that of other clinical variables; namely, age, pathological stage, and T stage, using univariate and multivariate Cox regression analysis, and the predictive utility of a combination of age, pathological stage, and T stage was evaluated by ROC curve analysis. Because 75 and 15 patients were missing information on N and M stages, respectively, these variables were excluded from the analyses. Hazard ratios (HRs) with 95% confidence intervals were calculated.

Generation of a potential splicing factors-alternative splicing (SF-AS) regulatory network

We downloaded the list of 404 human SF genes from the SpliceAid2 database (http://www.introni.it/splicing.html)21 and extracted the expression data for the SF genes from the 150-patient TGCT cohort dataset. We then evaluated Spearman's correlation coefficient for the expression of SF genes and the 15 PFS-related AS events. A significant correlation was defined as: Correlation >0.3 with adjusted P < 0.05, where Correlation >0.3 was considered to be positive regulation. The potential SF-AS regulatory network was constructed to illustrate significantly correlated SF-AS pairs using Cytoscape version 3.71 software (https://cytoscape.org/).

Statistical analyses

The Wilcoxon rank-sum test was used to compare ranked data with two categories. LASSO and Cox regression modeling were performed using glmnet and survival packages. Spearman's correlation analysis was conducted to estimate the correlation between AS events SF gene expression. All statistical analyses were conducted in RStudio version 3.6.1 (https://rstudio.com/), and P < 0.05 was considered statistically significant.

RESULTS

Genome-wide profiling of AS events in TGCT patients

The seven classes of AS are shown in . We obtained a total of 422 415 splicing events in 10 332 genes from 149 TGCT patients. The most frequent AS event was ES (15 879 events in 6443 genes), followed by AT (8721 events in 3813 genes), AP (8431 events in 3389 genes), AA (3441 events in 2441 genes), AD (2992 events in 2098 genes), RI (2790 events in 1858 genes), and ME (179 events in 176 genes), as shown in . All seven AS types occurred in some genes, highlighting the contribution of AS to transcriptome diversity. Illustration of AS types and identification of all AS events in TGCT. (a) The seven types of AS events are ES, AP, AT, AD, AA, ME, and RI. (b) UpSet graph showing gene intersections for the seven types of AS events (n = 422 415). Red lines indicate multiple AS events occurring in a single gene. AS: alternative splicing; TGCT: testicular germ cell tumors; ES: exon skip; AP: alternate promoter; AT: alternate terminator; AD: alternate donor site; AA: alternate acceptor site; ME: mutually exclusive exon; RI: retained intron. Of the 150-patient cohort, complete clinical information was available for 134 patients. As shown in , the majority of patients (81.3%) were in the 20- to 40-year age group, and the proportion of patients with pathological stages in situ, I, II, and III was 34.3%, 41.0%, 9.0%, and 10.5%, respectively. Clinical characteristics of 134 testicular germ cell tumors patients included in our study

Profiling of progression-related AS events and functional analysis of parent genes in TGCT patients

To determine the relationship between AS events and patient survival, the AS matrix and survival data were merged together. A total of 300 PFS-related AS events with P < 0.01 were screened by univariate Cox regression analysis. Among them, 229 AS events were adverse PFS-related events (HR <1, P < 0.01) and 72 were considered risk factors (HR <1, P < 0.01). Several genes, including serine/threonine-protein phosphatase 2A regulatory subunit 4 (PPP2R4), katanin catalytic subunit A1 like 2(KATNAL2), F-box protein 7 (FBXO7), and chromodomain helicase DNA-binding protein 6 (CHD6), were found to be processed by multiple progression-related AS events. Accordingly, we generated UpSet plots to demonstrate the subset of interacting AS events in the TGCT cohort. Not surprisingly, ES related events were the most frequent (). The distribution of the significance and the number of progression-related AS events are shown in the Volcano plot and pie charts, respectively, in (Figure and ). The top 20 most significant PFS-related events for each AS category are shown in ; notably, none of the top 300 PFS-related events was ME type. Profiling of progression-related AS events in TGCT. (a) UpSet plot showing gene intersections for the seven types of progression-related AS events in TGCT. (b) Volcano plot showing the distribution of significant and nonsignificant progression-related AS events (P < 0.001). (c) Pie chart showing the number of progression-related AS events in each category. ES: exon skip; AP: alternate promoter; AT: alternate terminator; AD: alternate donor site; AA: alternate acceptor site; ME: mutually exclusive exon; RI: retained intron; AS: alternative splicing; PFS: progression-free survival; TGCT: testicular germ cell tumors. Subgroup analysis of progression-associated AS events in TGCT. (a) The top 20 progression-related AS events for AA in TGCT. (b) The top 20 progression-related AS events for AD in TGCT. (c) The top 20 progression-related AS events for AP in TGCT. (d) The top 20 progression-related AS events for AT in TGCT. (e) The top 20 progression-related AS events for ES in TGCT. (f) The top 20 progression-related AS events for RI in TGCT. There were no significant PFS-related ME events among the top 300 events. The color of each circle indicates that the P value and the Z-score value are strongly correlated in PFS.. AS: alternative splicing; PFS: progression-free survival; TGCT: testicular germ cell tumors; ME: mutually exclusive exon; ES: exon skip; AP: alternate promoter; AT: alternate terminator; AD: alternate donor site; AA: alternate acceptor site; RI: retained intron. To understand the potential biological functions of the PFS-related AS events, we performed gene enrichment and GO analysis for the 268 parent genes associated with PFS-related AS events (). A total of 20 cellular component or molecular function GO terms were significantly enriched among the genes, including DNA repair, microtubule-based process, regulation of GTPase activity, and DNA modification (). Based on what we found, a network diagram was constructed, showing the crosstalk between the significantly enriched GO terms (). Functional enrichment of gene ontology items for 268 prognostic alternative splicing-related genes GO: gene ontology Functional analysis and network construction for parent genes associated with PFS-related AS events. (a) Enrichment analysis for the genes processed by the top significant progression-related AS events. (b) Functional nodes in the corresponding gene network of the most significant progression-related AS events. AS: alternative splicing; PFS: progression-free survival.

Derivation and assessment of a predictive ASS for TGCT patients

Having identified 300 PFS-related AS events, we used the LASSO regression method to further select a 15-event signature for disease progression in the TGCT patient cohort ( and ). We calculated the ASS for each patient from the results of the multivariate Cox regression analysis and used the median ASS as a cutoff to dichotomize the patients into high and low ASS groups. ROC curve analysis of the predictive value of ASS for 5-year progression gave an AUC of 0.899, indicating high predictive accuracy (). Indeed, patients with high ASS values had a significantly higher risk than the low ASS group of poor PFS according to Kaplan–Meier analysis (P = 1.462 × 10−7, log-rank test; and ). Univariate Cox regression analysis revealed that ASS, pathological stage, and T stage, but not age, were significant predictors of poor PFS, but only ASS and pathological stage remained significant in multivariate analysis (). Finally, we compared the predictive value of ASS with that of the other significant clinicopathological variables (age, pathological stage, and T stage) by ROC analysis. The combination of the three variables gave an AUC of 0.715, which indicates that these traditional clinical variables have poorer predictive power than ASS, which had an AUC of 0.899 ( and , respectively). Identification of pivotal progressionfree survivalrelated alternative splicing events in the cancer genome atlas from the least absolute shrinkage and selection operator regression model PFS: progressionfree survival; AS: alternative splicing; ES: exon skip; AA: alternate acceptor site; AD: alternate donor site Identification of 300 progression-free survival-related alternative splicing events with P<0.01 were screened by univariate Cox regression analysis HR: hazard ratio Identification of the 15-AS-event score for predicting TGCT progression. (a) The LASSO regression model was conducted to screen the pivotal hazard AS events and we illustrated the convergence curve, in which Log(Lambda) represented the horizontal axis, and coefficients represented the vertical axis. (b) Accordingly, the LASSO method selected 15 events from 300 potentially PFS-related AS events. (c) Receiver operating characteristic curve of the ability of the ASS to predict 5-year progression. (d) Kaplan–Meier analysis of PFS-related survival of TGCT patients according to the ASS. High and low ASS scores represent more than or less than the median ASS, respectively. P = 1.462 × 10−7 by log-rank test. AS: alternative splicing; ASS: AS score; PFS: progression-free survival; TGCT: testicular germ cell tumors; ROC: receiver operating characteristic; AUC: area under the curve; LASSO: least absolute shrinkage and selection operator.

Construction of a regulatory network of SFs and progression-related AS events

To determine whether expression of SFs correlated with specific PFS-related AS events in TGCT, we examined the transcriptome profiles of 404 splicing factors in the TGCT cohort dataset. Using a cutoff for significance with Spearman's correlation analysis of | Correlation | >0.3 and adjusted P < 0.05, we identified a total of 149 SFs that were significantly associated with PFS-related AS events in TGCT. The network of 431 potential SF-AF regulatory pairs generated from these correlations is shown in . Of the 431 pairs, 77 and 354 represented positive and negative regulatory processes, respectively. The selected AS events were also annotated with two colors, in which the pink in ellipses represented the risk AS events with HR >1 while the blue color represented the adverse correlation with PFS endpoints.

DISCUSSION

Although TGCT can be cured with combination therapy consisting of surgery, chemotherapy/radiotherapy, tumor progression and recurrence remain a concern.22 Currently, risk stratification of TGCT patients is mainly based on tumor size, pathological subtype, and serum biomarkers such as α-fetoprotein and lactate dehydrogenase.232425 However, these factors are of limited use for predicting progression of TGCT, highlighting the need for more accurate PFS-related biomarkers. Previous studies have indicated that AS plays a crucial role in the biology of tumors, which prompted us to focus on the potential PFS-related value of aberrant AS events in TGCT.26 Several studies have identified AS-related factors or other gene signatures, consisting of SF1, the histone variant macroH2A.1 histone (MacroH2A1), and RNA-binding protein of fox homologs(RBFOX)family genes, related to a progression in TGCT. However, these data were mostly derived from a limited number of tumor samples and used exon microarray analyses; in contrast, there have been no comprehensive or systematic assessments of the AS landscape in TGCT.272829 In the present study, we examined high-throughput RNA-seq data from 150 TGCT patients. We identified a total of 422 415 AS events in 10 332 genes encompassing all seven types of AS events. Of these, 300 events significantly associated with progression were identified, and we further analyzed the top 20 events in each AS type. Among the identified genes, several are known cancer drivers, such as tripartite motif containing 6 (TRIM6), TIR domain-containing adaptor protein(TIRAP), StAR related lipid transfer domain-containing 10(STARD10), and zinc finger protein 175(ZNF175).303132 One PFS-related AS event identified in our cohort was POLD1-51194-AA. Interestingly, Bonache et al.33 demonstrated that downregulation of POLD1 expression was involved in the modulation of the cell cycle and post-transcriptional modifications in testicular samples. Hirvonen-Santti et al.34 also showed that downregulation ofestrogen receptor beta(ER-β) and SNRPN upstream reading frame/ring finger protein 4 (SNURF/RNF4) complexes might play a role in testicular tumorigenesis; notably, RNF4-68572-ES was found to be significantly associated with PFS in our cohort. We also found that many of the AS events significantly associated with TGCT progression occurred in E3 ubiquitin ligase genes, including X-linked inhibitor of apoptosis(XIAP), ring finger protein 170(RNF170), Wolf-Hirschhorn syndrome candidate 1 (WHSC1), mouse double minute 2 homolog(MDM2), and pleckstrin homology domain-containing A5 (PLEKHA5). This finding suggests the possible involvement of aberrant protein ubiquitination in the development and/or progression of TGCT. Our functional analysis also uncovered enrichment of AS-related genes associated with DNA repair, microtubule-based process, regulation of GTPase activity, and DNA modification. A recent study by AlDubayan et al.35 highlighted a deficiency in DNA repair processes as a prominent mechanism driving susceptibility to TGCT, which provided new insight into potential management strategies for individuals at high risk for TGCT progression. We speculate that dysfunction of some of the DNA repair-related splice variants identified here may correlate with tumor progression. However, only a few of the PFS-related AS events here involved DNA repair genes, and further studies must be performed to validate the robustness of our results. Using the LASSO method, we obtained an ASS signature based on 15 key AS events (PEX1-80440-ES, RDX-18638-ES, NPLOC4-44135-ES, MBD1-45510-AA, CACNA2D2-65058-AA, ZNF669-10512-AD, AKAP2-87182-ES, TCEB1-84211-AD, SELENBP1-7618-ES, STARD10-17644-AP, RPL34-70298-AT, PPP4R1L-59958-ES, TGM2-59374-ES, SEC16A-88181-AA, and LIMK2-61838-ES). The ASS had good predictive value for 5-year progression and accurately stratified TGCT patients into high- and low-risk groups. Importantly, higher ASS values correlated significantly with poorer outcomes in this cohort. A comparison of the predictive value of ASS and a combination of traditional variables (age, pathological stage, and T stage) revealed that ASS had superior predictive power. These results suggest that the ASS identified here might have utility as a potential biomarker for predicting TGCT progression. Finally, we examined the correlation between AS events and the expression of SFs in TGCT, and we found that the majority of worse PFS-related AS events were associated with the expression levels of splicing factors positively, yet favorable prognosis AS events were in the opposite manner. This comprehensive AS-SF network could provide a better understanding of splicing patterns and their relationships with SFs in TGCT. One of the strengths of our study is the genome-wide identification of PFS-related AS events in TGCT and the successful demonstration of a strong predictive model, for risk of disease progression. However, several limitations also exist. First, the number of samples was relatively small, perhaps reflecting the relative rarity of this disease. Additional samples will need to be analyzed to provide external validation of the ASS model. Second, the 15 significant AS events identified here will need to be further analyzed to improve our understanding of the underlying mechanisms in tumor progression. Finally, whether integrating ASS and other clinical variables into a combined model could further improve the predictive accuracy remains unclear, but it would certainly have potential translational significance.

CONCLUSION

The results of this genome-wide profiling of AS events and association with SFs in TGCT add to our growing understanding of how aberrant AS affects cancer development and progression. Our results also provide new insights into the underlying mechanisms of TGCT progression and may help in the development of improved predictive biomarkers and therapeutic strategies for TGCT.

AUTHOR CONTRIBUTIONS

CJZ and ZTL analyzed the data and drafted the manuscript. KJS and YG helped analyze the data. CJZ, ZTL, and KJS prepared all figures. ZTL, KJS, and YG edited all tables. LC and DFX conceived the idea and designed the study. All authors have read and approved the final manuscript and agreed with the order of presentation of the authors.

COMPETING INTERESTS

All authors declared no competing interests. (a) Distribution of ASS among TGCT patients. (b) Association with progression-free survival. ASS: alternative splicing score; TGCT: testicular germ cell tumors. Comparison of ASS and other clinicopathological variables in predicting the risk of TGCT progression. (a) Univariate and multivariate Cox analysis of the association between ASS, age, pathological stage, and T stage and risk of 5-year progression in TGCT patients. (b) Receiver operating characteristic curves of the ability of the combination of age, pathological stage, and T stage to predict 5-year progression. (c) The network consists of 149 splicing factors (green triangles) significantly associated with 431 AS events (ellipses), of which 77 were positive correlations (red lines) and 354 were negative correlations (blue lines). The selected AS events were also annotated with two colors, in which the pink in ellipses represented the risk AS events with HR >1 while the blue color represented the adverse correlation with PFS endpoints. AS: alternative splicing; ASS: AS score; TGCT: testicular germ cell tumors.
Supplementary Table 1

Clinical characteristics of 134 testicular germ cell tumors patients included in our study

ParameterCategoriesPatients, n (%)
Age (year)<205 (3.73)
20–40109 (81.34)
>4020 (14.93)
Pathological stageIn situ46 (34.33)
Stage I55 (41.04)
Stage II12 (8.96)
Stage III14 (10.45)
Unknown7 (5.22)
AJCCT stageT176 (56.72)
T251 (38.06)
T36 (4.48)
Unknown1 (0.74)
AJCCN stageN046 (34.33)
N111 (8.21)
N22 (1.49)
Unknown75 (55.97)
AJCCM stageM0115 (85.82)
M14 (2.99)
Unknown15 (11.19)
Overall survival (followup: 4.43±3.88 years)Alive130 (97.01)
Dead4 (2.99)
Progression events (followup: 4.24±4.84 years)Free99 (73.88)
Occurred35 (26.12)
Supplementary Table 2

Functional enrichment of gene ontology items for 268 prognostic alternative splicing-related genes

GODescriptionCount (%)Log10 (P)Log10 (q)
GO:0120031Plasma membrane bounded cell projection assembly20 (7.46)−4.96−0.98
GO:0006281DNA repair19 (7.09)−4.82−0.98
GO:0007017Microtubulebased process22 (8.21)−4.35−0.73
RHSA5653656Vesiclemediated transport20 (7.46)−4.16−0.62
GO:0043087Regulation of GTPase activity16 (5.97)−4.01−0.58
GO:0045786Negative regulation of cell cycle19 (7.09)−3.95−0.58
GO:0034332Adherens junction organization8 (2.99)−3.72−0.54
GO:0006304DNA modification7 (2.61)−3.52−0.48
GO:0032963Collagen metabolic process7 (2.61)−3.52−0.48
GO:0048013Ephrin receptor signaling pathway6 (2.24)−3.4−0.41
GO:0009314Response to radiation14 (5.22)−3.3−0.35
GO:0051961Negative regulation of nervous system development11 (4.1)−3.1−0.24
GO:0006298mismatch repair4 (1.49)−3.09−0.24
RHSA76009Platelet aggregation (plug formation)4 (1.49)−3.05−0.21
GO:0007030Golgi organization7 (2.61)−2.95−0.19
RHSA176407Conversion from APC/C:Cdc20 to APC/C:Cdh1 in late anaphase3 (1.12)−2.94−0.19
M180PID HIF1A PATHWAY3 (1.12)−2.94−0.19
GO:0046677Response to antibiotic11 (4.1)−2.91−0.19
CORUM:178Respiratory chain complex I (holoenzyme), mitochondrial4 (1.49)−2.85−0.16
GO:0006354DNAtemplated transcription, elongation6 (2.24)−2.82−0.16

GO: gene ontology

Supplementary Table 3

Identification of pivotal progressionfree survivalrelated alternative splicing events in the cancer genome atlas from the least absolute shrinkage and selection operator regression model

SymbolAS_IDSplicing typeExonsFrom_exonTo_exonP (PFS)
PEX180440ES0.127835648262.23517E05
RDX18638ES0.212547.12.28E05
NPLOC444135ES5466.57E05
MBD145510AA18.1:18.2:18.3:18.41718.59.54E05
CACNA2D265058AA32.13132.20.000106824
ZNF66910512AD2.22.130.000147184
AKAP287182ES108110.00014768
TCEB184211AD1.21.150.000209421
SELENBP17618ES0.254861111580.000233458
STARD1017644AP2NullNull0.000282934
RPL3470298AT7NullNull0.000322694
PPP4R1L59958ES5460.00037392
TGM259374ES3240.000395314
SEC16A88181AA23.1123.923.120.000503732
LIMK261838ES4:5:6:7:8290.00053831

PFS: progressionfree survival; AS: alternative splicing; ES: exon skip; AA: alternate acceptor site; AD: alternate donor site

Supplementary Table 4

Identification of 300 progression-free survival-related alternative splicing events with P<0.01 were screened by univariate Cox regression analysis

IdZHRHR.95LHR.95HP
PEX1|80440|ES−4.2400031452.78E182.14E263.63E102.24E05
RDX|18638|ES−4.2351019012.64E154.73E221.47E082.28E05
TOM1L2|39513|ES−4.1365282563.12E067.68E090.0012676643.53E05
NPLOC4|44135|ES−3.9912140675.87E182.03E261.70E096.57E05
MBD1|45510|AA−3.9021042131.46E061.72E090.0012477389.54E05
CACNA2D2|65058|AA−3.8745452290.0004278198.46E060.0216450650.000106824
ZNF669|10512|AD−3.7957727372.10E141.82E212.43E070.000147184
AKAP2|87182|ES−3.7949387258.02E056.15E070.010457940.00014768
PPARD|75912|ES−3.7827856971.09E088.17E130.0001455970.000155083
TCEB1|84211|AD3.707371895273.022423614.068942215298.283460.000209421
SELENBP1|7618|ES−3.6797556642.29E076.66E110.0007884970.000233458
STARD10|17644|AP3.63044363639.304815485.415691519285.25785010.000282934
RPL34|70298|AT−3.5963655430.0070287280.0004714740.1047842080.000322694
RPL34|70300|AT3.596353022142.27332329.543334932121.0298760.00032271
PPP4R1L|59958|ES−3.5578377170.0018810665.93E050.0596894320.00037392
TGM2|59374|ES−3.5431927465.28E247.02E373.97E110.000395314
C6orf89|75992|AP−3.522808350.002158637.10E050.065666770.000427
RNF4|68572|ES−3.479784888.08E124.56E181.43E050.000501817
SEC16A|88181|AA3.4787641348058.58044750.750547931279606.260.000503732
LIMK2|61838|ES−3.4609314341.88E162.34E251.51E070.00053831
FBXO7|61936|AA−3.4582675314.76E071.24E100.0018222780.000543661
ELOF1|47736|AA−3.405350850.0001172646.41E070.0214571910.000660791
UEVLD|14674|ES−3.3988543120.0001198386.57E070.021872040.000676688
AURKAIP1|148|RI−3.3840984230.004682090.0002095230.1046280630.000714124
NLN|72251|ES−3.3817484689.13E087.60E120.0010975530.000720261
MAST4|72283|AT3.372794232188.38097568.9740933823954.4264190.000744095
GAS2L1|61590|AA−3.3727087114.96E121.34E181.84E050.000744327
THAP8|49334|AD−3.3407752523.21E061.92E090.0053612270.000835448
RDH13|51998|AP3.32032839618.772996073.324885035105.99626090.000899116
R3HCC1L|12756|ES−3.2887508550.0004348664.31E060.0438289610.001006331
COPS7A|19945|ES−3.2863684280.0131446650.0009926280.1740653520.001014882
TAF1C|37838|ES−3.283905316.62E098.70E140.000504110.001023793
KIF23|31394|ES−3.2829313092.76E123.46E192.20E050.001027337
BMPER|79231|AT−3.2719067520.0068744150.000348080.1357663820.001068248
TMEM135|18210|ES−3.2713854040.0007156579.34E060.0548435190.00107022
EVA1C|60346|ES−3.269152744.78E063.08E090.0073990930.001078701
NTRK3|32368|AT−3.2679266380.0131448250.0009782810.1766224880.001083384
ARHGAP5|27130|ES−3.2603986110.0024802426.73E050.0913638180.001112557
PLEKHA5|20650|ES−3.2480988120.0099111240.0006122740.1604353540.001161789
BIN2|21845|ES−3.2404811345.40E101.34E150.0002176870.001193282
ANAPC4|68965|AD3.222334875605.443517512.299732129802.425770.001271504
MBD1|45513|ES−3.2165321120.0135725620.0009881360.1864262290.0012975
ALKBH2|24275|ES−3.2106053752.14E067.39E100.0061859540.001324557
ZNF175|51362|AA−3.2052669860.0036879760.0001199280.1134107060.001349373
WASH4P|499144|ES−3.1986511590.0001922281.02E060.0363828950.001380721
PMP22|39345|ES−3.1766743851.97E052.47E080.015776740.001489742
ZBP1|59940|AT3.171492609286.23833948.679292239439.9848230.001516577
ZNF7|85661|ES−3.1553303680.0015853132.89E050.0869542250.001603165
PTK2|85322|ES3.149452721174.13839217.0201030714319.620280.001635766
GNB2L1|190579|ES3.13282145194.734916715.4949108581633.2757120.001731347
ZNF195|13966|ES−3.1321154870.0032629649.07E050.1173554650.001735516
NDUFB1|28985|AP−3.1230412910.0002649641.51E060.0465510560.001789926
NDUFB1|28986|AP3.1230412913774.10417221.48178981663066.83130.001789926
RDH13|51997|AP−3.118467730.0608303120.0104697610.3534299360.00181794
SBDS|79905|AD3.114380819299323.7256107.1167983836420562.40.001843314
THTPA|26762|ES−3.1047187230.0214348740.001894880.2424711830.001904601
PIK3C3|45320|ES−3.1013717912.51E067.26E100.008688820.001926263
FAM98A|53191|ES−3.0999039262.20E181.51E293.21E070.001935834
ARHGEF7|26288|ES3.09988480222344.0217239.7481896412560453.970.001935959
GLYCTK|65211|ES3.0987777126.94213365.9303987212717.2380870.001943208
CENPH|72307|ES−3.0948562655.75E186.94E294.76E070.001969083
WDR91|81881|ES−3.0800454091.37E107.21E170.0002585820.00206969
KANSL1|42013|AA−3.0770624752.97E053.88E080.0227222560.002090515
CCNL2|161|ES−3.0739888820.0020146383.85E050.1054462280.002112173
FAM86B1|82698|ES−3.0694460390.03454090.0040271820.296255240.002144561
MBD1|45511|ES−3.0598120160.0019445973.57E050.1060403180.00221476
FKBP5|75916|AP−3.0551433491.27E074.76E120.0033688190.00224953
TJAP1|76273|AP−3.0504747225.37E168.30E263.48E060.002284799
PTPN18|55344|ES−3.0454099670.0223837280.0019408070.2581560980.002323633
BEST1|16319|ES−3.039831040.0006084465.14E060.072049290.002367109
MTHFSD|37920|ES3.0375173397.442361815.0757988381870.6442430.002385357
RGS5|8770|AP−3.0336480235.64E111.35E170.0002358750.002416161
RDM1|40359|AD−3.0329250420.0011511561.45E050.0912671190.002421958
DNM1L|21045|ES−3.0257463080.0058311540.0002082070.1633105360.002480203
ASPSCR1|44259|ES−3.0122243082.82E162.15E263.70E060.002593409
PABPC1L|59499|RI3.0071646591.03716E+181878244.9385.73E+290.002636969
EHBP1|53718|ES−3.0051369130.0148679090.0009553950.2313752170.002654613
ACSBG1|32056|AP3.004676625379054707894766.1465653.01465E+170.002658633
ZNF610|51443|AP−3.0000516690.000462463.06E060.0697934930.002699338
LARP4|21702|ES−2.998635193.39E072.00E110.0057402840.002711918
TBC1D7|75382|AD−2.9971273260.0092277550.0004308990.1976134230.002725369
CASP10|56811|ES−2.990937422.28E125.37E209.71E050.002781225
TRIM6|14052|AD2.98407150736.413058093.434076352386.10405340.002844403
ERCC1|50445|ES−2.9834900416.35E051.11E070.036318070.002849813
NCAPG|68861|AA−2.9788350657.67E141.80E223.27E050.002893465
PNPLA6|47109|AP2.9763304641898.35634913.16771783273681.20080.002917203
ZSCAN2|32292|RI−2.969951783.44E204.91E332.40E070.002978465
SYPL1|81326|AP−2.9655717068.25E063.60E090.0188865320.003021209
PHACTR2|77987|ES2.95846415212.936813522.37273195170.535208980.003091762
STARD10|17643|AP−2.9559413740.0427469340.005285840.345697280.003117163
FAM104A|43212|ES−2.9547996010.0026292585.11E050.1352999090.003128722
INTS3|7759|RI−2.9475276494.33E072.55E110.0073802790.003203261
CNBP|66705|AA−2.9448922131.35E091.69E150.0010805460.003230672
TMUB2|41812|ES−2.9370725570.046623740.0060275870.3606373710.003313266
MEF2BNBMEF2B|95081|ES2.93646691434167468.73320.07652773.6473E+120.003319742
RBFOX2|61985|ES−2.9358706450.0013052181.55E050.1099588580.00332613
AKIP1|14280|RI2.93507825919.113189622.664982495137.0793310.003334636
TRAPPC8|45017|AA−2.9332020172.72E131.09E216.77E050.003354855
ETV1|78834|ES−2.9314683451.64E062.23E100.0121051120.003373637
ZNF7|85662|ES−2.9305028850.0016883412.36E050.1207191340.003384139
RPS6KC1|9783|ES−2.9274736310.0001947536.39E070.0593882220.00341728
BBS9|79224|ES−2.9253677920.0003234541.48E060.0705016880.003440493
CHRD|67960|ES−2.9228290097.72E076.16E110.0096935370.003468669
ENY2|84888|AA2.9224425261.31732E+17434717.20953.99E+280.003472977
CIZ1|87711|AP−2.9210878130.0002210957.80E070.0626987260.003488115
GAS8|38203|ES−2.9190275260.0037272538.72E050.1592449330.003511252
MAPK12|62811|ES−2.9181898215.48E073.41E110.0087887070.0035207
RFX5|7602|AP2.91474117932.105728043.115364545330.86907110.003559836
COL16A1|1493|ES2.913396569116.75994064.7483052832871.1051440.003575203
D2HGDH|58424|AA2.909716218192.3290645.5658133176646.0132130.003617571
B9D2|50061|ES−2.9056132373.50E067.30E100.0167577880.003665342
GINS3|36635|ES−2.9040547640.0135500760.0007433240.2470048390.003683637
TUBD1|42819|ES−2.9001869232.88E052.46E080.0337323420.003729402
DMD|132972|ES−2.8990717868.50E051.50E070.048010880.003742692
ANKRD42|18054|ES−2.8962279060.0048323160.0001309040.1783843020.00377678
TBC1D14|68730|AP−2.8957825780.0545063770.0076073250.3905374450.003782143
PLD3|49899|AD2.894420013112.54228984.5947511262756.5730190.003798597
FAM86C1|17443|ES−2.893824160.060599510.0090749690.4046625880.003805812
CCL4L1|40399|RI−2.8937595970.013951820.0007726380.2519333140.003806595
MDFI|76117|ES−2.8921805971.23E174.28E293.54E060.00382578
HIF1A|27801|AP−2.89165161.13E131.89E226.73E050.003832227
PCBP2|22052|ES−2.8852158710.0016017652.02E050.1269259880.003911454
TIRAP|19384|AT2.8800893615711.31051315.856037942057201.6730.003975625
CNTNAP3|86465|AT2.87708030555.976437863.607490658868.5709520.004013734
DLGAP4|59282|AP−2.8762220993.74E096.75E150.0020666510.004024664
CDH6|71623|AT2.87112308510.512934472.10982780852.384270790.004090162
CDH6|71624|AT−2.8710719110.0951251960.0190905970.4739926590.004090825
ARHGAP5|27131|ES−2.869903740.0127671840.0006496460.2509072370.004105968
OSGEPL1|56530|AA−2.8694925440.0002358217.85E070.0708330140.00411131
TSC2|33199|ES−2.8674984759.35E077.08E110.0123564370.004137308
TNC|87351|ES2.8585459966.7058185041.8188402924.723447160.004255874
NDUFA2|73706|AA−2.85231352.59E111.38E180.0004876670.004340227
CD47|66014|ES−2.8520560140.004572220.0001127560.185401510.004343745
TDRD1|13191|AT−2.8497889730.0034357536.94E050.1700754180.004374824
HDGFRP2|46805|AA−2.8490811121.18E054.83E090.0290020790.00438457
DYNC1I2|55943|ES−2.848672587.00E059.69E080.0505537480.004390204
RTCA|3878|ES−2.8482281531.42E061.35E100.0150221360.004396339
PRDM4|24200|AD−2.8465603425.61E085.71E130.0055152480.004419435
ZMYND8|59714|AD−2.8435037470.0045668840.0001112880.1874096550.004462048
TDRD1|13192|AT2.841141009283.42163815.76261530213939.473790.004495243
SS18|44912|ES−2.8407443770.0328473230.0031114520.3467662740.004500837
HCFC1R1|33353|AA−2.8338092070.0039191698.48E050.1810619730.004599679
BANP|37990|AA2.83072333382.387435023.8845289721747.3648670.004644287
CTAGE5|27380|AD−2.8272314480.0010707919.34E060.1227006910.004695238
SERINC3|59470|AT−2.8252539651.68E073.36E120.008418830.004724315
ZNF426|47358|RI2.82186880527.163747422.741538567269.14418890.00477447
MSH6|53505|ES−2.8198972192.89E181.87E304.48E060.004803903
NIF3L1|56773|ES2.81480105522.502627382.574332144196.69887590.004880744
LTA4H|23822|ES−2.8141109770.002590524.09E050.1640226510.004891234
INTS7|9722|AA−2.8117057413.81E141.69E238.61E050.004927956
NUCB2|14523|AT−2.8105919521.58E085.72E140.0043527290.004945046
TARBP2|22075|ES−2.8096160330.1253520360.0294439190.5336631040.004960064
COL1A1|430774|ES2.8083419138837.3658415.56513835017561.2620.004979732
RAD51C|42716|ES−2.8079019670.0006915464.30E060.1110914090.00498654
MAP3K4|78358|AD2.80629178577.90361626.80654273349066.406070.005011529
AASDH|69344|ES−2.7926834620.0011838091.05E050.1340646080.005227282
C19orf82|47381|ES−2.7921173620.1438724620.0368900190.5611080060.005236436
ARPC4|63188|AD−2.790330124.34E067.43E100.0253638770.005265432
ELOF1|47735|RI−2.7857279045.02E054.75E080.0531695710.005340768
IFI27L1|29060|ES−2.7857148220.0252598160.0018985290.3360802940.005340984
SPEG|57695|AP−2.7838061150.0773549330.0127619750.4688761310.005372514
AGPAT4|78370|RI−2.7837044970.0304041340.0025988940.355694120.005374197
ENDOV|44075|RI−2.7835451520.0391663740.0040008140.3834231850.005376838
POLD1|51194|AA−2.783164164.64E071.61E110.0133876440.005383156
MRPL55|10121|ES2.782293883135.86719714.2703120634322.8445530.005397614
SLC8B1|24641|AD−2.781983550.0043024419.26E050.199899120.005402778
USP7|33959|AP−2.780792030.0069767130.000210770.2309370580.005422646
TIMM10B|14146|RI−2.7797713980.0005558072.82E060.1096519180.005439718
SHH|82445|AA−2.7793862253.18E052.14E080.0472110580.005446173
GTPBP3|48288|AA−2.7793405070.0002235475.96E070.0838993940.005446939
C19orf40|48918|ES−2.7767544170.0023883453.37E050.1693400180.005490465
EHBP1|53715|AP−2.7754721170.0184863410.0011039450.3095667730.005512163
ACOT7|389|AP2.76810001810.030815971.96036178251.325867440.005638415
ARFIP2|14135|ES−2.7674618640.0101199790.0003912130.2617855370.005649465
ZNF345|49427|AT−2.7671522430.0135326230.0006424610.2850476140.005654834
ZNF345|49426|AT2.76696113373.878680153.5072145821556.237650.00565815
PPP2R4|87840|AA−2.766714640.0283408860.0022703360.3537828750.00566243
LHX6|87460|ES−2.7645670730.0295692330.0024362890.358881740.005699839
FBXO5|78211|AP2.764004797172.8247184.476235426672.65690.00570967
TRAPPC2L|38050|ES−2.7625755381.91E129.23E210.0003935360.005734729
ZNF133|58789|ES−2.7620930490.0520846550.0063987490.4239596380.005743211
BLVRB|49903|ES−2.7612540960.1478879420.0380840630.5742780970.005757986
TENC1|21930|RI−2.7589290791.95E091.27E150.0030042590.005799112
NOMO2|34243|RI−2.7539102824.62E101.05E160.0020347580.005888791
SLC26A6|64727|ES−2.752611642.69E062.90E100.0248795360.005912198
N6AMT1|60296|ES−2.7523026420.0045251369.69E050.2113967540.00591778
INPP4B|70691|AT−2.7517502940.0383086610.0037517580.3911641680.00592777
RCE1|17130|AP−2.7492422960.0005264812.42E060.1144837440.005973321
TARBP2|22078|AD−2.7487177310.0010828.31E060.140916410.005982888
DIXDC1|18708|AP2.74840559110.928889581.98581488760.146909070.005988588
PIDD|13769|AA−2.7456723360.0159511220.0008315270.3059893580.006038704
ABHD17A|46556|ES−2.7435778061.59E101.59E170.001589340.006077364
XIAP|90027|AP2.74104794229.766723552.629975319336.907280.006124357
OGG1|63171|ES−2.740929810.0523604080.0063532670.4315279660.006126559
ARMC4|11085|ES−2.7382662140.0032515845.39E050.1962720070.006176406
FBXO7|61934|ES−2.7375585391.25E181.89E318.21E060.00618971
GOLGA8M|29753|AT2.73683960586.893655883.551391522126.070130.006203253
UBE2C|59609|RI−2.7342158630.0384441640.0037187460.3974334120.006252904
TNC|87357|ES2.7330215947.7059230231.78174538333.327573180.006275622
B9D1|39715|RI−2.7325407150.0028400164.23E050.1905339040.00628479
RCE1|17131|AP2.7316546461922.3217188.466009086436489.11190.006301716
IL6|78936|ES−2.7292816613.74E079.07E120.0154319550.006347247
SLC6A11|63375|AT2.72889863912.834500892.05264185280.249953410.006354623
SLC6A11|63374|AT−2.7288986390.0779149890.0124610660.4871770490.006354623
SNX11|42178|ES−2.7266444020.0095659760.0003382510.2705325810.006398195
RASGRP1|29923|ES−2.7260051720.0005959972.86E060.1241091130.006410599
CDH8|36695|RI−2.7239805540.0499317020.0057786910.4314428040.00645003
TBC1D14|68726|AP2.72380630187.923178663.5090431212203.0180530.006453434
ASTE1|66777|AD−2.7220839430.0005766772.68E060.1239187010.006487166
GEMIN7|50400|AD2.719700421216.19499094.48981999910410.277940.006534108
L3HYPDH|27739|AP2.718631696133.85544283.9216065514568.8621070.006555255
L3HYPDH|27738|AP−2.7186169010.0074707670.000218870.255002630.006555549
R3HDM2|22578|ES−2.7183936030.00018153.64E070.0904127960.006559975
LPHN2|3565|ES−2.7178638130.0221028750.0014143680.3454102530.006570488
GINS3|36634|ES−2.7169681850.000276877.51E070.102033710.006588294
IDUA|68443|ES−2.7137009741.27E053.69E090.043642780.00665362
ARMCX5|89700|RI−2.7071724070.0199523690.0011727590.3394535590.006785901
MEF2B|48596|ES2.7065354389859.30821812.637572577691821.9870.006798933
C1orf43|7800|ES−2.7025115322.19E059.16E090.0524608280.00688178
SLC39A13|15743|RI−2.7022343710.0790865580.0125569140.4981067450.006887519
GOLGA8M|29752|AT−2.6993686010.0118666810.0004743880.2968416660.006947118
RAP1GAP|990|AA−2.6993399340.000409061.42E060.1180143860.006947717
BAZ2A|22473|RI−2.6989932370.0003784731.24E060.115613610.006954959
FRMPD1|86421|AT2.69894810235.417024452.655713529472.3271570.006955902
FRMPD1|86420|AT−2.6985642430.0282503860.0021183870.3767415510.00696393
PLEKHA7|14511|ES−2.6975038243.91E371.37E631.11E100.006986148
LARP1B|70568|ES−2.6959910820.0040626157.42E050.2224256390.007017955
POFUT2|60872|AD−2.6959881570.0045553899.04E050.229488320.007018016
COPS3|39473|ES−2.6948073770.0500270410.005663980.4418632810.007042933
ZBP1|59942|AT−2.6939703988.28E073.11E110.0220224080.007060644
RNF170|83745|ES−2.6927389140.0002430395.69E070.1038566120.007086774
FAM104A|43214|ES−2.6917434924.24E065.19E100.0346252820.007107959
MAP3K13|68008|AA−2.6913932990.0001425122.25E070.0901047650.007115426
NMRAL1|33737|AD−2.690156140.0384030020.0035725450.4128122930.007141859
APH 1B|31024|ES−2.6880275480.0017956691.79E050.1804245630.007187547
YAF2|21209|ES−2.680461315.05E082.33E130.0109287380.007352076
IP6K2|64772|AA2.6792294853121.5149268.6715504741123657.8120.00737918
CYB561|42926|AP−2.6738675677.02E056.33E080.0778008020.007498206
NDUFA7|47218|ES−2.6718977980.0009571655.84E060.1568832150.007542362
SLC20A2|83729|AP2.6713639961635.629277.175022452372860.59070.007554368
TMEM175|68433|ES−2.6710185610.0553998920.006629940.4629224320.007562147
MYO1B|56610|AD−2.6694698620.006261460.0001509950.2596502450.007597109
TRAPPC2L|38047|ES−2.6594926730.0459212840.0047419790.4447012760.007825843
IQCG|68332|AT−2.6564944029.11E059.52E080.0872188270.007895776
NT5DC2|65225|AP2.653240321656.9307085.44755409979220.499190.007972309
NT5DC2|65224|AP−2.6532403210.0015222311.26E050.1835686220.007972309
CYB561A3|16163|RI−2.6517322890.0712320730.0101078410.5019873370.008008001
PPP2R4|87857|ES−2.6511256854.51E052.76E080.0736207050.008022398
EPN2|39705|ES−2.648780347.77E112.57E180.0023498510.008078282
AMACR|71697|AT−2.6480137540.0010097456.12E060.1665657840.008096623
HBP1|81336|AD2.64659530235.53589662.525249635500.06935150.008130659
KCNRG|25923|ES−2.6455286180.0024622432.88E050.2108565840.008156339
NDUFC1|70623|AD−2.6450932834.09E052.30E080.0730256180.00816684
ICOSLG|60809|RI−2.6440794190.0005105041.85E060.1406840040.008191343
NQO2|75157|ES−2.6438253690.0004543761.51E060.1365824810.008197494
TP53I11|15489|ES−2.6437952929.26E101.86E160.0046073570.008198222
TMEM5|22853|AD−2.6432921390.0134961850.0005543560.3285740620.008210416
PIEZO1|38024|ES−2.642933240.060829530.0076283390.4850638780.008219124
KATNAL2|45430|AT2.64287562454.322890682.8074672691051.1169570.008220523
DNM1L|21043|ES−2.6417946980.0166959450.0008015950.347749890.008246803
KATNAL2|45429|AT−2.6402316050.0184611580.0009532880.3575145890.008284939
EML2|50500|ES2.63959622524.776046912.285228102268.61760540.008300486
CACNB3|21480|ES−2.6351739145.51E053.75E080.0810560640.008409418
SOGA3|77484|AT−2.6339851820.0035568625.36E050.2362286420.008438917
DNAJC17|30040|AA−2.6336792563.50E063.05E100.0402169640.008446524
SMIM5|43471|AP2.63320118238.985197772.551228487595.7309010.008458423
SMIM5|43470|AP−2.6332011820.0256507610.001678610.3919680280.008458423
SYNE4|49323|ES−2.6310549810.0006234312.55E060.1522164110.008512026
KIFAP3|8962|AP−2.630539914.08E077.08E120.0235063490.008524936
TRAPPC2|88518|ES−2.6282310530.0561651150.0065599440.4808760930.00858302
WHSC1|68534|RI2.62589590813.734005841.94333388297.06150760.008642124
COL1A2|306247|ES2.6252834337483.7956239.5898026315840286.7180.008657687
LSM5|79195|AD2.62495928713.118398141.91954749989.652571730.008665933
FLAD1|7863|AT2.624909191116109.052619.18836939702577265.30.008667208
CNEP1R1|36357|AP−2.6237893010.0903389490.0149939590.5442942520.008695756
C16orf93|36182|AT−2.623299635.29E066.05E100.0463232820.008708265
RAB43|66696|RI2.62247537330793.3279213.6116566269663015.360.008729358
E2F6|52689|ES−2.620409860.0137636960.0005579330.3395379840.008782414
RGS19|60191|AP2.61494795588.47867353.073534082547.0599830.008924105
ADCY6|21466|ES−2.6099832221.49E071.11E120.0199287860.009054666
SDR39U1|100871|ES−2.6096244240.0201617610.0010743380.3783693730.009064168
MLH3|28468|ES−2.6070619370.0363784330.0030123150.4393266780.009132284
EZH2|82157|ES−2.6059090570.0029375323.66E050.235706180.009163079
MED12L|67297|ES−2.6039202914.87E052.77E080.0858178740.009216419
PLEC|85513|AP2.603885071318.905615.910241874294321.62740.009217366
PRKCSH|47708|AP2.60132973526.652331232.246566849316.19213130.009286315
TMEM229B|28062|AT2.6009051592.58E+42282903040672.36E+740.009297815
MDM2|22972|ES−2.5991406581.20E103.94E180.0036297520.009345747
MAP4K4|54753|AD2.595795419956.68029225.371912101170374.56390.009437224
PPP1R32|16238|AP2.5934684029.8169372691.74706544855.162362390.009501327
CDC14A|3883|AT−2.5927393340.0215739160.0011870630.3920886220.009521491
IGHMBP2|17354|ES−2.5906898631.78E067.92E110.0398033570.009578377
FOXM1|19720|ES−2.5882971480.0005103861.64E060.1587858610.009645174
RGS19|60190|AP−2.587834350.011737020.000405030.3401172540.009658141
POC5|72542|ES−2.5849338242.03E095.21E160.0079151210.009739769
NOTCH2|4401|AT2.5841762516542178646234.9658851.82155E+170.00976119
PNKP|51102|AP2.583872364108.43652973.1004067153792.5608020.009769794
CEP250|59168|ES−2.5808625195.61E071.01E110.0313474670.009855382
ABCA4|3802|AT−2.5796570116.72E054.54E080.0994493270.009889849
ATF2|56069|ES−2.5768774188.90E096.70E150.0118216680.00996973

HR: hazard ratio

  35 in total

1.  Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data.

Authors:  Gui-Qi Zhu; Yu-Jie Zhou; Li-Xin Qiu; Biao Wang; Yi Yang; Wei-Ting Liao; Yi-Hong Luo; Ying-Hong Shi; Jian Zhou; Jia Fan; Zhi Dai
Journal:  Carcinogenesis       Date:  2019-09-18       Impact factor: 4.944

2.  Altered gene expression signature of early stages of the germ line supports the pre-meiotic origin of human spermatogenic failure.

Authors:  S Bonache; F Algaba; E Franco; L Bassas; S Larriba
Journal:  Andrology       Date:  2014-05-07       Impact factor: 3.842

Review 3.  Alternative splicing as a regulator of development and tissue identity.

Authors:  Francisco E Baralle; Jimena Giudice
Journal:  Nat Rev Mol Cell Biol       Date:  2017-05-10       Impact factor: 94.444

4.  Intravenous but not intrathecal central nervous system-directed chemotherapy improves survival in patients with testicular diffuse large B-cell lymphoma.

Authors:  S Mannisto; P Vähämurto; M Pollari; M R Clausen; S Jyrkkiö; P-L Kellokumpu-Lehtinen; P Kovanen; M-L Karjalainen-Lindsberg; F d'Amore; S Leppä
Journal:  Eur J Cancer       Date:  2019-05-10       Impact factor: 9.162

5.  DIS3L2 Promotes Progression of Hepatocellular Carcinoma via hnRNP U-Mediated Alternative Splicing.

Authors:  Songge Xing; Zhaoyong Li; Wenhao Ma; Xiaoping He; Shengqi Shen; Haoran Wei; Shi-Ting Li; Ying Shu; Linchong Sun; Xiuying Zhong; Yuhao Huangfu; Lanhong Su; Junru Feng; Xiaozhang Zhang; Ping Gao; Wei-Dong Jia; Huafeng Zhang
Journal:  Cancer Res       Date:  2019-07-22       Impact factor: 12.701

Review 6.  Management of stage I testicular germ cell tumours.

Authors:  Michal Chovanec; Nasser Hanna; K Clint Cary; Lawrence Einhorn; Costantine Albany
Journal:  Nat Rev Urol       Date:  2016-09-13       Impact factor: 14.432

7.  Small nuclear RING finger protein expression during gonad development: regulation by gonadotropins and estrogen in the postnatal ovary.

Authors:  Sirpa J Hirvonen-Santti; Venkataraman Sriraman; Mikko Anttonen; Saija Savolainen; Jorma J Palvimo; Markku Heikinheimo; Joanne S Richards; Olli A Jänne
Journal:  Endocrinology       Date:  2004-01-28       Impact factor: 4.736

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

Authors:  Kevin Litchfield; Max Levy; Giulia Orlando; Chey Loveday; Philip J Law; Gabriele Migliorini; Amy Holroyd; Peter Broderick; Robert Karlsson; Trine B Haugen; Wenche Kristiansen; Jérémie Nsengimana; Kerry Fenwick; Ioannis Assiotis; ZSofia Kote-Jarai; Alison M Dunning; Kenneth Muir; Julian Peto; Rosalind Eeles; Douglas F Easton; Darshna Dudakia; Nick Orr; Nora Pashayan; D Timothy Bishop; Alison Reid; Robert A Huddart; Janet Shipley; Tom Grotmol; Fredrik Wiklund; Richard S Houlston; Clare Turnbull
Journal:  Nat Genet       Date:  2017-06-12       Impact factor: 38.330

9.  Association of Inherited Pathogenic Variants in Checkpoint Kinase 2 (CHEK2) With Susceptibility to Testicular Germ Cell Tumors.

Authors:  Saud H AlDubayan; Louise C Pyle; Marija Gamulin; Tomislav Kulis; Nathanael D Moore; Amaro Taylor-Weiner; Anis A Hamid; Brendan Reardon; Bradley Wubbenhorst; Rama Godse; David J Vaughn; Linda A Jacobs; Stefanie Meien; Mislav Grgic; Zeljko Kastelan; Sarah C Markt; Scott M Damrauer; Daniel J Rader; Rachel L Kember; Jennifer T Loud; Peter A Kanetsky; Mark H Greene; Christopher J Sweeney; Christian Kubisch; Katherine L Nathanson; Eliezer M Van Allen; Douglas R Stewart; Davor Lessel
Journal:  JAMA Oncol       Date:  2019-04-01       Impact factor: 33.006

10.  Subphenotype meta-analysis of testicular cancer genome-wide association study data suggests a role for RBFOX family genes in cryptorchidism susceptibility.

Authors:  Yanping Wang; Dione R Gray; Alan K Robbins; Erin L Crowgey; Stephen J Chanock; Mark H Greene; Katherine A McGlynn; Katherine Nathanson; Clare Turnbull; Zhaoming Wang; Marcella Devoto; Julia Spencer Barthold
Journal:  Hum Reprod       Date:  2018-05-01       Impact factor: 6.918

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