Integrated multi-omic analysis of low-grade ovarian serous carcinoma collected from short and long-term survivors

Molecular Surrogate Subtypes of Ovarian and Peritoneal Low-grade Serous Carcinoma

Low-grade serous carcinoma (LGSC) is an uncommon histotype of ovarian carcinoma, accounting for ~3% of cases. There is evidence that survival of peritoneal LGSC (pLGSC) is longer than that of ovarian LGSC (oLGSC). Key molecular alterations of LGSC have been established, including loss of CDKN2A and PR expression, MAPK pathway alterations, and loss of USP9X expression. We hypothesized that LGSC could be subclassified into clinically applicable molecular subtypes by a few surrogate tests similar to endometrioid carcinomas using a hierarchical decision tree based on the strength of the prognostic associations of the individual alterations. Our study included 71 LGSCs. Immunohistochemistry for CDKN2A, ER, PR, NF1, and USP9X and sequencing for KRAS , NRAS , and BRAF were performed. Our data showed the co-occurrence of key molecular alterations, and despite suggestive trends, hierarchical molecular subtyping did not provide significantly different stratification of patients according to survival in this cohort. We confirmed that patients diagnosed with pLGSC have a longer survival than high-stage oLGSC, with the intriguing observation that normal CDKN2A and PR status were associated with excellent survival in pLGSC. Therefore, CDKN2A and PR status might aid in the classification of indeterminate implants, where abnormal findings favor pLGSC over noninvasive implants. Molecular subtypes should be further evaluated in larger cohorts for their prognostic and potentially predictive value.

Changes in the tumour microenvironment mark the transition from serous borderline tumour to low-grade serous carcinoma

Low-grade serous ovarian carcinoma (LGSC) is a rare and lethal subtype of ovarian cancer. LGSC is pathologically, biologically, and clinically distinct from the more common high-grade serous ovarian carcinoma (HGSC). LGSC arises from serous borderline ovarian tumours (SBTs). The mechanism of transformation for SBTs to LGSC remains poorly understood. To better understand the biology of LGSC, we performed whole proteome profiling of formalin-fixed, paraffin-embedded tissue blocks of LGSC (n = 11), HGSC (n = 19), and SBTs (n = 26). We identified that the whole proteome is able to distinguish between histotypes of the ovarian epithelial tumours. Proteins associated with the tumour microenvironment were differentially expressed between LGSC and SBTs. Fibroblast activation protein (FAP), a protein expressed in cancer-associated fibroblasts, is the most differentially abundant protein in LGSC compared with SBT. Multiplex immunohistochemistry (IHC) for immune markers (CD20, CD79a, CD3, CD8, and CD68) was performed to determine the presence of B cells, T cells, and macrophages. The LGSC FAP+ stroma was associated with greater abundance of Tregs and M2 macrophages, features not present in SBTs. Our proteomics cohort reveals that there are changes in the tumour microenvironment in LGSC compared with its putative precursor lesion, SBT. These changes suggest that the tumour microenvironment provides a supportive environment for LGSC tumourigenesis and progression. Thus, targeting the tumour microenvironment of LGSC may be a viable therapeutic strategy. © 2024 The Pathological Society of Great Britain and Ireland.

A new method for network bioinformatics identifies novel drug targets for mucinous ovarian carcinoma

Mucinous ovarian carcinoma (MOC) is a subtype of ovarian cancer that is distinct from all other ovarian cancer subtypes and currently has no targeted therapies. To identify novel therapeutic targets, we developed and applied a new method of differential network analysis comparing MOC to benign mucinous tumours (in the absence of a known normal tissue of origin). This method mapped the protein-protein network in MOC and then utilised structural bioinformatics to prioritise the proteins identified as upregulated in the MOC network for their likelihood of being successfully drugged. Using this protein-protein interaction modelling, we identified the strongest 5 candidates, CDK1, CDC20, PRC1, CCNA2 and TRIP13, as structurally tractable to therapeutic targeting by small molecules. siRNA knockdown of these candidates performed in MOC and control normal fibroblast cell lines identified CDK1, CCNA2, PRC1 and CDC20, as potential drug targets in MOC. Three targets (TRIP13, CDC20, CDK1) were validated using known small molecule inhibitors. Our findings demonstrate the utility of our pipeline for identifying new targets and highlight potential new therapeutic options for MOC patients.

A review: targeting UBR5 domains to mediate emerging roles and mechanisms - chance or necessity?

Ubiquitinases are known to catalyze ubiquitin chains on target proteins to regulate various physiological functions like cell proliferation, autophagy, apoptosis, and cell cycle progression. As a member of E3 ligase, ubiquitin protein ligase E3 component n-recognin 5 (UBR5) belongs to the HECT E3 ligase and has been reported to be correlated with various pathophysiological processes. In this review, the authors give a comprehensive insight into the structure and function of UBR5. The authors discuss the specific domains of UBR5 and explore their biological functions separately. Furthermore, the authors describe the involvement of UBR5 in different pathophysiological conditions, including immune response, virus infection, DNA damage response, and protein quality control. Moreover, the authors provide a thorough summary of the important roles and regulatory mechanisms of UBR5 in cancers and other diseases. On the whole, investigating the domains and functions of UBR5, elucidating the underlying mechanisms of UBR5 with various substrates in detail may provide new theoretical basis for the treatment of diseases, including cancers, which could improve future studies to construct novel UBR5-targeted therapy strategies.

The survival benefit associated with complete macroscopic resection in epithelial ovarian cancer is histotype specific

BACKGROUND

Complete macroscopic resection is a key factor associated with prolonged survival in ovarian cancer. However, most evidence derives from high-grade serous ovarian carcinoma, and the benefit of complete macroscopic resection in other histotypes is poorly characterized. We sought to determine which histotypes derive the greatest benefit from complete macroscopic resection to better inform future decisions on radical cytoreductive efforts.

METHODS

We performed multivariable analysis of disease-specific survival across 2 independent patient cohorts to determine the magnitude of benefit associated with complete macroscopic resection within each histotype.

RESULTS

Across both cohorts (Scottish: n = 1622; Surveillance, Epidemiology, and End Results [SEER]: n = 18 947), complete macroscopic resection was associated with prolonged disease-specific survival; this was more marked in the Scottish cohort (multivariable hazard ratio [HR] = 0.44, 95% confidence interval [CI] = 0.37 to 0.52 vs HR = 0.59, 95% CI = 0.57 to 0.62 in SEER). In both cohorts, clear cell ovarian carcinoma was among the histotypes to benefit most from complete macroscopic resection (multivariable HR = 0.23 and HR = 0.50 in Scottish and SEER cohorts, respectively); high-grade serous ovarian carcinoma patients demonstrated highly statistically significant and clinically meaningful survival benefit, but this was of lower magnitude than in clear cell ovarian carcinoma and endometrioid ovarian carcinoma across both cohorts. The benefit derived in low-grade serous ovarian carcinoma is also high (multivariable HR = 0.27 in Scottish cohort). Complete macroscopic resection was associated with prolonged survival in mucinous ovarian carcinoma patients in the SEER cohort (multivariable HR = 0.65), but the association failed to reach statistical significance in the Scottish cohort.

CONCLUSIONS

The overall ovarian cancer patient population demonstrates clinically significant survival benefit associated with complete macroscopic resection; however, the magnitude of benefit differs between histotypes.

Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning

Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can lead to dysregulation of immune responses and disease pathogenesis. However, systematic evaluation of NET-related genes (NETRGs) for the diagnosis of pediatric sepsis is still lacking. Three datasets were taken from the Gene Expression Omnibus (GEO) database: GSE13904, GSE26378, and GSE26440. After NETRGs and differentially expressed genes (DEGs) were identified in the GSE26378 dataset, crucial genes were identified by using LASSO regression analysis and random forest analysis on the genes that overlapped in both DEGs and NETRGs. These crucial genes were then employed to build a diagnostic model. The diagnostic model's effectiveness in identifying pediatric sepsis across the three datasets was confirmed through receiver operating characteristic curve (ROC) analysis. In addition, clinical pediatric sepsis samples were collected to measure the expression levels of important genes and evaluate the diagnostic model's performance using qRT-PCR in identifying pediatric sepsis in actual clinical samples. Next, using the CIBERSORT database, the relationship between invading immune cells and diagnostic markers was investigated in more detail. Lastly, to evaluate NET formation, we measured myeloperoxidase (MPO)-DNA complex levels using ELISA. A group of five important genes (MME, BST1, S100A12, FCAR, and ALPL) were found among the 13 DEGs associated with NET formation and used to create a diagnostic model for pediatric sepsis. Across all three cohorts, the sepsis group had consistently elevated expression levels of these five critical genes as compared to the normal group. Area under the curve (AUC) values of 1, 0.932, and 0.966 indicate that the diagnostic model performed exceptionally well in terms of diagnosis. Notably, when applied to the clinical samples, the diagnostic model also showed good diagnostic capacity with an AUC of 0.898, outperforming the effectiveness of traditional inflammatory markers such as PCT, CRP, WBC, and NEU%. Lastly, we discovered that children with high ratings for sepsis also had higher MPO-DNA complex levels. In conclusion, the creation and verification of a five-NETRGs diagnostic model for pediatric sepsis performs better than established markers of inflammation.

Exploring novel approaches in the systemic therapy of low-grade serous carcinoma of the ovary: a literature review

By presenting a comprehensive analysis of low-grade serous carcinomas (LGSCs), a subset of epithelial ovarian cancers, this review delves into their distinct molecular characteristics, clinicopathological features and systemic therapy options, emphasizing their differences from high-grade serous carcinomas (HGSCs). Notably, LGSCs exhibit prevalent RAS/RAF/MEK/MAPK pathway activation, KRAS and BRAF mutations, and infrequent p53 mutations. While chemotherapy is commonly employed, LGSCs display lower responsiveness compared to HGSCs. Hormone therapy, particularly endocrine maintenance therapy, is explored due to the higher estrogen receptor expression. Novel therapeutic approaches involving CDK4/6 inhibitors, MEK inhibitors, and antiangiogenic agents like bevacizumab are also investigated. Ongoing clinical trials are striving to enhance LGSC treatment strategies, offering valuable insights for future therapeutic advancements in this challenging ovarian cancer subtype.

The role of UBR5 in tumor proliferation and oncotherapy

Ubiquitin (Ub) protein ligase E3 component n-recognin 5 (UBR5), as a crucial Ub ligase, plays a pivotal role in the field of cell biology, attracting significant attention for its functions in regulating protein degradation and signaling pathways. This review delves into the fundamental characteristics and structure of UBR5. UBR5, through ubiquitination, regulates various key proteins, directly or indirectly participating in cell cycle control, thereby exerting a direct impact on the proliferation of tumor cells. Meanwhile, we comprehensively review the expression levels of UBR5 in different types of tumors and its relationship with tumor development, providing key clues for the role of UBR5 in cancer. Furthermore, we summarize the current research status of UBR5 in cancer treatment. Through literature review, we find that UBR5 may play a crucial role in the sensitivity of tumor cells to radiotherapy chemotherapy, and other anti-tumor treatment, providing new insights for optimizing cancer treatment strategies. Finally, we discuss the challenges faced by UBR5 in cancer treatment, and looks forward to the future research directions. With the continuous breakthroughs in technology and in-depth research, we hope to further study the biological functions of UBR5 and lay the foundation for its anti-tumor treatment.

The prognostic value of MEK pathway-associated estrogen receptor signaling activity for female cancers

BACKGROUND

Other than for breast cancer, endocrine therapy has not been highly effective for gynecologic cancers. Endocrine therapy resistance in estrogen receptor positive gynecologic cancers is still poorly understood. In this retrospective study, we examined the estrogen receptor (ER) signaling pathway activities of breast, ovarian, endometrial, and cervical cancers to identify those that may predict endocrine therapy responsiveness.

METHODS

Clinical and genomic data of women with breast and gynecological cancers were downloaded from cBioPortal for Cancer Genomics. Estrogen receptor alpha (ESR1) expression level and sample-level pathway enrichment scores (EERES) were calculated to classify patients into four groups (low/high ESR1 and low/high EERES). Correlation between ESR1/EERES score and survival was further validated with RNAseq data from low-grade serous ovarian cancer. Pathway analyses were performed among different ESR1/EERES groups to identify genes that correlate with endocrine resistance, which are validated using Cancer Cell Line Encyclopedia gene expression and Genomics of Drug Sensitivity in Cancer data.

RESULTS

We identified a novel combined prognostic value of ESR1 expression and the corresponding estrogen response signaling (EERES score) for breast cancer. The combined prognostic value (ESR1/EERES) may be applicable to other gynecologic cancers. More importantly, we discovered that ER signaling can cross-regulate MEK pathway activation. We identified downstream genes in the MEK pathway (EPHA2, INAVA, MALL, MPZL2, PCDH1, and TNFRSF21) that are potential endocrine therapy response biomarkers.

CONCLUSION

This study demonstrated that targeting both the ER and the ER signaling activity related MEK pathway may aid the development of endocrine therapy strategies for personalized medicine.