Multiomics Characterization of Low-Grade Serous Ovarian Carcinoma Identifies Potential Biomarkers of MEK Inhibitor Sensitivity and Therapeutic Vulnerability

Nuclear Focal Adhesion Kinase Protects against Cisplatin Stress in Ovarian Carcinoma

SIGNIFICANCE

FAK inhibitors are in combinatorial clinical testing with agents that prevent Ras-Raf-MAPK pathway activation in various cancers. This study suggests that nuclear FAK limits ERK/MAPK activation in supporting HGSOC cell survival to cisplatin stress. Overall, it is likely that targets of FAK-mediated survival signaling may be tumor type- and context-dependent.

zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation

Isobaric labeling-based mass spectrometry (ILMS) has been widely used to quantify, on a proteome-wide scale, the relative protein abundance in different biological conditions. However, large-scale ILMS data sets typically involve multiple runs of mass spectrometry, bringing great computational difficulty to the integration of ILMS samples. We present zMAP, a toolset that makes ILMS intensities comparable across mass spectrometry runs by modeling the associated mean-variance dependence and accordingly applying a variance stabilizing z-transformation. The practical utility of zMAP is demonstrated in several case studies involving the dynamics of cell differentiation and the heterogeneity across cancer patients.

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.

High-throughput drug screening identifies novel therapeutics for Low Grade Serous Ovarian Carcinoma

Low grade serous carcinoma (LGSOC) is a rare epithelial ovarian cancer with unique molecular characteristics compared to the more common tubo-ovarian high-grade serous ovarian carcinoma. Pivotal clinical trials guiding the management of epithelial ovarian cancer lack sufficient cases of LGSOC for meaningful subgroup analysis, hence overall findings cannot be extrapolated to rarer chemo-resistant subtypes such as LGSOC. Furthermore, there is a need for more effective therapies for the treatment of relapsed disease, as treatment options are limited. To address this, we conducted the largest quantitative high-throughput drug screening effort (n = 3436 compounds) in 12 patient-derived LGSOC cell lines and one normal ovary cell line to identify unexplored therapeutic avenues. Using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines, our data set identified 60 high and 19 moderate confidence hits which induced cancer cell specific cytotoxicity at the lowest compound dose assessed (0.1 µM). We also revealed a series of known (mTOR/PI3K/AKT) and novel (EGFR and MDM2-p53) drug classes in which LGSOC cell lines showed demonstrable susceptibility to.

Proteomic landscape of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a deadly disease with limited diagnostic biomarkers and therapeutic targets. Here we conduct a comprehensive proteomic profiling of ovarian tissue and plasma samples from 813 patients with different histotypes and therapeutic regimens, covering the expression of 10,715 proteins. We identify eight proteins associated with tumor malignancy in the tissue specimens, which are further validated as potential circulating biomarkers in plasma. Targeted proteomics assays are developed for 12 tissue proteins and 7 blood proteins, and machine learning models are constructed to predict one-year recurrence, which are validated in an independent cohort. These findings contribute to the understanding of EOC pathogenesis and provide potential biomarkers for early detection and monitoring of the disease. Additionally, by integrating mutation analysis with proteomic data, we identify multiple proteins related to DNA damage in recurrent resistant tumors, shedding light on the molecular mechanisms underlying treatment resistance. This study provides a multi-histotype proteomic landscape of EOC, advancing our knowledge for improved diagnosis and treatment strategies.

Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current tumor-node-metastasis or Veterans Administration Lung Study Group staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent cohort, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

High throughput screening identifies dasatinib as synergistic with trametinib in low grade serous ovarian carcinoma

BACKGROUND

Low grade serous ovarian carcinoma (LGSOC) is a distinct histotype of ovarian cancer characterised high levels of intrinsic chemoresistance, highlighting the urgent need for new treatments. High throughput screening in clinically-informative cell-based models represents an attractive strategy for identifying candidate treatment options for prioritisation in clinical studies.

METHODS

We performed a high throughput drug screen of 1610 agents across a panel of 6 LGSOC cell lines (3 RAS/RAF-mutant, 3 RAS/RAF-wildtype) to identify novel candidate therapeutic approaches. Validation comprised dose-response analysis across 9 LGSOC models and 5 high grade serous comparator lines.

RESULTS

16 hits of 1610 screened compounds were prioritised for validation based on >50% reduction in nuclei counts in over half of screened cell lines at 1000 nM concentration. 11 compounds passed validation, and the four agents of greatest interest (dasatinib, tyrosine kinase inhibitor; disulfiram, aldehyde dehydrogenase inhibitor; carfilzomib, proteasome inhibitor; romidepsin, histone deacetylase inhibitor) underwent synergy profiling with the recently approved MEK inhibitor trametinib. Disulfiram demonstrated excellent selectivity for LGSOC versus high grade serous ovarian carcinoma comparator lines (P = 0.003 for IC50 comparison), while the tyrosine kinase inhibitor dasatinib demonstrated favourable synergy with trametinib across multiple LGSOC models (maximum zero interaction potency synergy score 46.9). The novel, highly selective Src family kinase (SFK) inhibitor NXP900 demonstrated a similar trametinib synergy profile to dasatinib, suggesting that SFK inhibition is the likely driver of synergy.

CONCLUSION

Dasatinib and other SFK inhibitors represent novel candidate treatments for LGSOC and demonstrate synergy with trametinib. Disulfiram represents an additional treatment strategy worthy of investigation.

Comprehensive Genomic Characterization in Ovarian Low-Grade and Chemosensitive and Chemoresistant High-Grade Serous Carcinomas

INTRODUCTION

Genomic characterization of serous ovarian carcinoma (SOC), which includes low-grade serous carcinoma (LGSC) and high-grade serous carcinoma (HGSC), remains necessary to improve efficacy of platinum-based chemotherapy. The aim of this study was to investigate the genomic variations in these SOC groups, also in relation to chemoresponse.

METHODS

Forty-five samples of SOC were retrospectively analyzed by next-generation sequencing on DNA/RNA extracts from formalin-fixed, paraffin-embedded (FFPE) tumor samples obtained at diagnosis. HGSCs were classified as platinum-resistant and platinum-sensitive.

RESULTS

In the LGSC group, 44% of the carcinomas had mutually exclusive variants in the RAS/RAF pathway, while additional likely oncogenic variants in the CDKN2A, SMARCA4, and YAP1 genes were observed in the remaining LGSCs. Tumor mutation burden (TMB) was significantly lower in the intrinsically chemoresistant LGSC group than in the HGSC group. In the HGSC cohort, TP53 variants were found in 90% and homologous recombination repair (HRR) pathway variants in 41% of the neoplasms. HGSCs of the chemoresistant group without classic mutations in the HRR pathway were characterized by additional variants in FGFR2 and with an FGFR3::TACC3 fusion. In addition, HGSCs showed MYC, CCNE1, and AKT2 gains that were almost exclusively observed in the chemosensitive HGSC group.

CONCLUSION

These results suggest that very low TMB and MYC, CCNE1, and AKT2 gains in SOC patients may be biomarkers related to platinum treatment efficacy. Thorough genomic characterization of SOCs prior to treatment might lead to more specific platinum-based chemotherapy strategies.

Advances in precision therapy of low-grade serous ovarian cancer: A review

Low-grade serous ovarian carcinoma (LGSOC) is a rare subtype of ovarian cancer that accounts for approximately 6% to 10% of serous ovarian cancers. The clinical treatment of LGSOC is similar to that of high-grade serous ovarian carcinoma, however, its clinical and molecular characteristics are different from those of high-grade serous ovarian carcinoma. This article reviews the research on gene diagnosis, surgical treatment, chemotherapy, and biological therapy of LGSOC, providing reference for clinical diagnosis and treatment of LGSOC. Surgery is the cornerstone of LGSOC treatment and maximum effort must be made to achieve R0 removal. Although LGSOC is not sensitive to chemotherapy, postoperative platinum-based combination chemotherapy remains the first-line treatment option for LGSOC. Additional clinical trials are needed to confirm the clinical benefits of chemotherapy and explore new chemotherapy protocols. Hormone and targeted therapies may also play important roles. Some patients, particularly those with residual lesions after treatment, may benefit from hormone maintenance therapy after chemotherapy. Targeted therapies, such as MEKi, show good application prospects and are expected to change the treatment pattern of LGSOC. Continuing to further study the genomics of LGSOC, identify its specific gene changes, and combine traditional treatment methods with precision targeted therapy based on second-generation sequencing may be the direction for LGSOC to overcome the treatment bottleneck. In future clinical work, comprehensive genetic testing should be carried out for LGSOC patients to accumulate data for future scientific research, in order to find more effective methods and drugs for the treatment of LGSOC.

Construction of an immune-related risk score signature for gastric cancer based on multi-omics data

Early identification of gastric cancer (GC) is associated with a superior survival rate compared to advanced GC. However, the poor specificity and sensitivity of traditional biomarkers suggest the importance of identifying more effective biomarkers. This study aimed to identify novel biomarkers for the prognosis of GC and construct a risk score (RS) signature based on these biomarkers, with to validation of its predictive performance. We used multi-omics data from The Cancer Genome Atlas to analyze the significance of differences in each omics data and combined the data using Fisher's method. Hub genes were subsequently subjected to univariate Cox and LASSO regression analyses and used to construct the RS signature. The RS of each patient was calculated, and the patients were divided into two subgroups according to the RS. The RS signature was validated in two independent datasets from the Gene Expression Omnibus and subsequent analyses were subsequently conducted. Five immune-related genes strongly linked to the prognosis of GC patients were obtained, namely CGB5, SLC10A2, THPO, PDGFRB, and APOD. The results revealed significant differences in overall survival between the two subgroups (p < 0.001) and indicated the high accuracy of the RS signature. When validated in two independent datasets, the results were consistent with those in the training dataset (p = 0.003 and p = 0.001). Subsequent analyses revealed that the RS signature is independent and has broad applicability among various GC subtypes. In conclusion, we used multi-omics data to obtain five immune-related genes comprising the RS signature, which can independently and effectively predict the prognosis of GC patients with high accuracy.

Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover hidden patterns from complex NGS data and to solve various PGx problems. In this review, we provide a comprehensive overview of the NGS approaches that can be employed and the different PGx studies implicating the use of NGS data. We also provide an excursus of the ML algorithms that can exert a role as fundamental strategies in the PGx field to improve personalized medicine in cancer.

Heterogeneity and treatment landscape of ovarian carcinoma

Ovarian carcinoma is characterized by heterogeneity at the molecular, cellular and anatomical levels, both spatially and temporally. This heterogeneity affects response to surgery and/or systemic therapy, and also facilitates inherent and acquired drug resistance. As a consequence, this tumour type is often aggressive and frequently lethal. Ovarian carcinoma is not a single disease entity and comprises various subtypes, each with distinct complex molecular landscapes that change during progression and therapy. The interactions of cancer and stromal cells within the tumour microenvironment further affects disease evolution and response to therapy. In past decades, researchers have characterized the cellular, molecular, microenvironmental and immunological heterogeneity of ovarian carcinoma. Traditional treatment approaches have considered ovarian carcinoma as a single entity. This landscape is slowly changing with the increasing appreciation of heterogeneity and the recognition that delivering ineffective therapies can delay the development of effective personalized approaches as well as potentially change the molecular and cellular characteristics of the tumour, which might lead to additional resistance to subsequent therapy. In this Review we discuss the heterogeneity of ovarian carcinoma, outline the current treatment landscape for this malignancy and highlight potentially effective therapeutic strategies in development.

Construction of a prognostic 6-gene signature for breast cancer based on multi-omics and single-cell data

BACKGROUND

Breast cancer (BC) is one of the females' most common malignant tumors there are large individual differences in its prognosis. We intended to uncover novel useful genetic biomarkers and a risk signature for BC to aid determining clinical strategies.

METHODS

A combined significance (p combined) was calculated for each gene by Fisher's method based on the RNA-seq, CNV, and DNA methylation data from TCGA-BRCA. Genes with a p combined< 0.01 were subjected to univariate cox and Lasso regression, whereby an RS signature was established. The predicted performance of the RS signature would be assessed in GSE7390 and GSE20685, and emphatically analyzed in triple-negative breast cancer (TNBC) patients, while the expression of immune checkpoints and drug sensitivity were also examined. GSE176078, a single-cell dataset, was used to validate the differences in cellular composition in tumors between TNBC patients with different RS.

RESULTS

The RS signature consisted of C15orf52, C1orf228, CEL, FUZ, PAK6, and SIRPG showed good performance. It could distinguish the prognosis of patients well, even stratified by disease stages or subtypes and also showed a stronger predictive ability than traditional clinical indicators. The down-regulated expressions of many immune checkpoints, while the decreased sensitivity of many antitumor drugs was observed in TNBC patients with higher RS. The overall cells and lymphocytes composition differed between patients with different RS, which could facilitate a more personalized treatment.

CONCLUSION

The six genes RS signature established based on multi-omics data exhibited well performance in predicting the prognosis of BC patients, regardless of disease stages or subtypes. Contributing to a more personalized treatment, our signature might benefit the outcome of BC patients.

Rare Epithelial Ovarian Cancers: Low Grade Serous and Mucinous Carcinomas

The ovarian epithelial cancer histotypes can be divided into common and rare types. Common types include high-grade serous ovarian carcinomas and the endometriosis-associated cancers, endometrioid and clear-cell carcinomas. The less common histotypes are mucinous and low-grade serous, each comprising less than 10% of all epithelial carcinomas. Although histologically and epidemiologically distinct from each other, these histotypes share some genetic and natural history features that distinguish them from the more common types. In this review, we will consider the similarities and differences of these rare histological types, and the clinical challenges they pose.

Establishment and validation of preclinical models of SMARCA4-inactivated and ARID1A/ARID1B co-inactivated dedifferentiated endometrial carcinoma

OBJECTIVE

Dedifferentiated endometrial cancer (DDEC) is an uncommon and clinically highly aggressive subtype of endometrial cancer characterized by genomic inactivation of SWItch/Sucrose Non-Fermentable (SWI/SNF) complex protein. It responds poorly to conventional systemic treatment and its rapidly progressive clinical course limits the therapeutic windows to trial additional lines of therapies. This underscores a pressing need for biologically accurate preclinical tumor models to accelerate therapeutic development.

METHODS

DDEC tumor from surgical samples were implanted into immunocompromised mice for patient-derived xenograft (PDX) and cell line development. The histologic, immunophenotypic, genetic and epigenetic features of the patient tumors and the established PDX models were characterized. The SMARCA4-deficienct DDEC model was evaluated for its sensitivity toward a KDM6A/B inhibitor (GSK-J4) that was previously reported to be effective therapy for other SMARCA4-deficient cancer types.

RESULTS

All three DDEC models exhibited rapid growth in vitro and in vivo, with two PDX models showing spontaneous development of metastases in vivo. The PDX tumors maintained the same undifferentiated histology and immunophenotype, and exhibited identical genomic and methylation profiles as seen in the respective parental tumors, including a mismatch repair (MMR)-deficient DDEC with genomic inactivation of SMARCA4, and two MMR-deficient DDECs with genomic inactivation of both ARID1A and ARID1B. Although the SMARCA4-deficient cell line showed low micromolecular sensitivity to GSK-J4, no significant tumor growth inhibition was observed in the corresponding PDX model.

CONCLUSIONS

These established patient tumor-derived models accurately depict DDEC and represent valuable preclinical tools to gain therapeutic insights into this aggressive tumor type.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Distinct histopathological features are associated with molecular subtypes and outcome in low grade serous ovarian carcinoma

Low grade serous ovarian carcinoma (LGSOC) demonstrates unique clinical and molecular features compared to other ovarian cancer types. The relationship between common histological features of LGSOC and molecular events, such as hormone receptor expression patterns and MAPK gene mutation status, remains poorly understood. Recent data suggest some of these molecular features may be biomarkers of response to recently introduced biologically-targeted therapies, namely endocrine therapy and MEK inhibitors. We utilize a cohort of 63 pathologically-confirmed LGSOC cases with whole exome sequencing and hormone receptor expression data to investigate these relationships. LGSOC cases demonstrated uniformly high oestrogen receptor (ER) expression, but variable progesterone receptor (PR) expression intensity. 60% and 37% of cases demonstrated micropapillary and macropapillary patterns of stromal invasion, respectively. 63% of cases demonstrated desmoplasia, which was significantly associated with advanced disease stage and visible residual disease after cytoreductive surgery. MAPK-mutant cases (KRAS, BRAF, NRAS) more frequently demonstrated macropapillary stromal invasion, while Chr1p loss was associated with desmoplasia and low PR expression. Presence of micropapillary stromal invasion and low PR expression were associated with significantly poorer survival after accounting for stage and residual disease status. Together, these data identify novel relationships between histopathological features and molecularly-defined subgroups in LGSOC.

Targeting receptor tyrosine kinases in ovarian cancer: Genomic dysregulation, clinical evaluation of inhibitors, and potential for combinatorial therapies

Epithelial ovarian cancer (EOC) remains one of the leading causes of cancer-related deaths among women worldwide. Receptor tyrosine kinases (RTKs) have long been sought as therapeutic targets for EOC, as they are frequently hyperactivated in primary tumors and drive disease relapse, progression, and metastasis. More recently, these oncogenic drivers have been implicated in EOC response to poly(ADP-ribose) polymerase (PARP) inhibitors and epigenome-interfering agents. This evidence revives RTKs as promising targets for therapeutic intervention of EOC. This review summarizes recent studies on the role of RTKs in EOC malignancy and the use of their inhibitors for clinical treatment. Our focus is on the ERBB family, c-Met, and VEGFR, as they are linked to drug resistance and targetable using commercially available drugs. The importance of these RTKs and their inhibitors is highlighted by their impact on signal transduction and intratumoral heterogeneity in EOC and successful use as maintenance therapy in the clinic through suppression of the VEGF/VEGFR axis. Finally, the therapeutic potential of RTK inhibitors is discussed in the context of combinatorial targeting via co-inhibiting proliferative and anti-apoptotic pathways, epigenomic/transcriptional programs, and harnessing the efficacy of PARP inhibitors and programmed cell death 1/ligand 1 immune checkpoint therapies.

Efficacy of immune checkpoint inhibitor monotherapy or combined with other small molecule-targeted agents in ovarian cancer

Ovarian cancer is the most lethal female reproductive system tumour. Despite the great advances in surgery and systemic chemotherapy over the past two decades, almost all patients in stages III and IV relapse and develop resistance to chemotherapy after first-line treatment. Ovarian cancer has an extraordinarily complex immunosuppressive tumour microenvironment in which immune checkpoints negatively regulate T cells activation and weaken antitumour immune responses by delivering immunosuppressive signals. Therefore, inhibition of immune checkpoints can break down the state of immunosuppression. Indeed, Immune checkpoint inhibitors (ICIs) have revolutionised the therapeutic landscape of many solid tumours. However, ICIs have yielded modest benefits in ovarian cancer. Therefore, a more comprehensive understanding of the mechanistic basis of the immune checkpoints is needed to improve the efficacy of ICIs in ovarian cancer. In this review, we systematically introduce the mechanisms and expression of immune checkpoints in ovarian cancer. Moreover, this review summarises recent updates regarding ICI monotherapy or combined with other small-molecule-targeted agents in ovarian cancer.

CORUM: the comprehensive resource of mammalian protein complexes-2022

The CORUM database has been providing comprehensive reference information about experimentally characterized, mammalian protein complexes and their associated biological and biomedical properties since 2007. Given that most catalytic and regulatory functions of the cell are carried out by protein complexes, their composition and characterization is of greatest importance in basic and disease biology. The new CORUM 4.0 release encompasses 5204 protein complexes offering the largest and most comprehensive publicly available dataset of manually curated mammalian protein complexes. The CORUM dataset is built from 5299 different genes, representing 26% of the protein coding genes in humans. Complex information from 3354 scientific articles is mainly obtained from human (70%), mouse (16%) and rat (9%) cells and tissues. Recent curation work includes sets of protein complexes, Functional Complex Groups, that offer comprehensive collections of published data in specific biological processes and molecular functions. In addition, a new graphical analysis tool was implemented that displays co-expression data from the subunits of protein complexes. CORUM is freely accessible at http://mips.helmholtz-muenchen.de/corum/.

Systematic analysis of MCM3 in pediatric medulloblastoma via multi-omics analysis

Minichromosome maintenance proteins are DNA-dependent ATPases that bind to replication origins and allow a single round of DNA replication. One member of this family, MCM3, is reportedly active in most cancers. To systematically elucidate the mechanisms affected by aberrant MCM3 expression and evaluate its clinical significance, we analyzed multi-omics data from the GEO database and validated them in cell lines and tumor samples. First, we showed the upregulation of MCM3 in medulloblastoma (MB) at bulk and single-cell RNA sequence levels and revealed the potential role of MCM3 via DNA replication. Then we found the dysregulation of MCM3 might result from abnormal methylation of MCM3. Moreover, we discovered that MCM3 might affect varied biological processes such as apoptosis, autophagy, and ferroptosis and that MCM3 was correlated with immune components such as fibroblast and neutrophils, which were associated with overall survival in different medulloblastoma subtypes. Furthermore, we found that MCM3 expression was correlated with the IC₅₀ values of cisplatin and etoposide. The nomogram of MCM3-related genes showed the reliable and better prediction of 1- and 5-year survival compared to current histological and molecular classifications. Overall, the results of our study demonstrated that MCM3 might serve as a potential biomarker with clinical significance and better guidance than current histological and molecular classifications for clinical decision-making.

Chemoresistant Cancer Cell Lines Are Characterized by Migratory, Amino Acid Metabolism, Protein Catabolism and IFN1 Signalling Perturbations

Simple Summary

While chemoresistance remains a major barrier to improving the outcomes for patients with ovarian cancer, the molecular features, and associated biological functions, which underpin chemoresistance in ovarian cancer remain poorly understood. In this study we aimed to provide insight into the proteins and metabolites, and their associated biological pathways, which play a role in conferring chemoresistance to ovarian cancer. Through mass spectrometry analysis comparing the proteome and metabolome of chemosensitive vs chemoresistant ovarian cancer cell lines we revealed numerous perturbations in signalling and metabolic pathways in chemoresistant cells. Further comparison to primary cells taken from patients with chemoresistant or chemosensitive disease identified a shared dysregulation in cytokine and type 1 interferon signalling. Our research sets the foundation for a deeper understanding of the proteomic and metabolomic features of chemoresistance and identifies type 1 interferon signalling as a common feature of chemoresistance.

Abstract

Chemoresistance remains the major barrier to effective ovarian cancer treatment. The molecular features and associated biological functions of this phenotype remain poorly understood. We developed carboplatin-resistant cell line models using OVCAR5 and CaOV3 cell lines with the aim of identifying chemoresistance-specific molecular features. Chemotaxis and CAM invasion assays revealed enhanced migratory and invasive potential in OVCAR5-resistant, compared to parental cell lines. Mass spectrometry analysis was used to analyse the metabolome and proteome of these cell lines, and was able to separate these populations based on their molecular features. It revealed signalling and metabolic perturbations in the chemoresistant cell lines. A comparison with the proteome of patient-derived primary ovarian cancer cells grown in culture showed a shared dysregulation of cytokine and type 1 interferon signalling, potentially revealing a common molecular feature of chemoresistance. A comprehensive analysis of a larger patient cohort, including advanced in vitro and in vivo models, promises to assist with better understanding the molecular mechanisms of chemoresistance and the associated enhancement of migration and invasion.

Investigating a clinically actionable BRAF mutation for monitoring low-grade serous ovarian cancer: A case report

Low-grade serous ovarian cancer (LGSOC) poses a specific clinical challenge due to advanced presentation at diagnosis and the lack of effective systemic treatments. The aim of this study was to use a precision medicine approach to identify clinically actionable mutations in a patient with recurrent LGSOC. Primary, metastatic and recurrence tissue, and blood samples were collected from a stage IV LGSOC patient. Single-gene testing for clinically actionable mutations (BRAF V600, KRAS and NRAS) and subsequent whole-exome sequencing (WES) were performed. Droplet digital PCR was used to evaluate the presence of an identified BRAF D594G mutation in the matched plasma cell-free DNA (cfDNA). No clinically actionable mutations were identified using single-gene testing. WES identified a BRAF D594G mutation in six of seven tumor samples. The patient was commenced on a MEK inhibitor, trametinib, but with minimal clinical response. A newly designed ddPCR assay detected the BRAF alteration in the matched tissues and liquid biopsy cfDNA. The identification and sensitive plasma detection of a common “druggable” target emphasises the impact of precision medicine on the management of rare tumors and its potential contribution to novel monitoring regimens in this field.

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First report of BRAF D594G mutation in multiple samples of a recurrent LGSOC patient.

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Discovery of a BRAF actionable mutation expands the range of LGSOC therapeutic options.

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ddPCR assay allows sensitive detection of the mutation in tissue and plasma samples.

NCAPH promotes cell proliferation and inhibits cell apoptosis of bladder cancer cells through MEK/ERK signaling pathway

Bladder cancer (BC) is one of the most common cancers world-wide with a poor prognosis. Non-SMC (Structural Maintenance of Chromosomes)-condensin I complex subunit H (NCAPH) is a regulatory subunit of the condensin I complex and plays an important role in tumorigenesis and progression in several types of cancers. However, the role of NCAPH in BC remains unknown. In this study, we tried to reveal the biological functions of NCAPH in BC. We detected the expressions of NCAPH in BC and adjacent tissues, and BC cells lines. Subsequently, the gain- and loss-of-function experiments were performed to determine the effects of NCAPH on BC cell proliferation, apoptosis, and activation of the MEK/ERK signaling pathway in vitro. Moreover, we used BALB/c nude mice and established a xenograft model to investigate whether silence NCAPH using shRNA targeting NCAPH (shNCAPH) can inhibit BC tumor growth in vivo. The results showed NCAPH was overexpressed in BC tissues compared to adjacent tissues and highly expressed in BC cell lines. Additionally, overexpression of NCAPH promoted cell proliferation and inhibited apoptosis in SW780 cells. Conversely, knockdown of NCAPH reduced cell proliferation and enhanced apoptosis in UMUC3 cells. Furthermore, we found that the NCAPH activated the MEK/ERK signaling pathway in BC cells. MEK1/2 inhibitor U0126 blocked the increase of cell proliferation regulated by NCAPH overexpression. Knockdown of NCAPH significantly inhibited tumor growth in mice. Our results suggest that NCAPH might play an important role in BC progression and provide the potential marker in the diagnosis of BC.

The Evolution of Ovarian Carcinoma Subclassification

Simple Summary

Historically, cancers presenting with their main tumor mass in the ovary have been classified as ovarian carcinomas (a concise term for epithelial ovarian cancer) and treated with a one-size-fits-all approach. Over the last two decades, a growing molecular understanding established that ovarian carcinomas consist of several distinct histologic types, which practically represent different diseases. Further research is now delineating several molecular subtypes within each histotype. This histotype/molecular subtype subclassification provides a framework of grouping tumors based on molecular similarities for research, clinical trial inclusion and future patient management.

Abstract

The phenotypically informed histotype classification remains the mainstay of ovarian carcinoma subclassification. Histotypes of ovarian epithelial neoplasms have evolved with each edition of the WHO Classification of Female Genital Tumours. The current fifth edition (2020) lists five principal histotypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), mucinous carcinoma (MC), endometrioid carcinoma (EC) and clear cell carcinoma (CCC). Since histotypes arise from different cells of origin, cell lineage-specific diagnostic immunohistochemical markers and histotype-specific oncogenic alterations can confirm the morphological diagnosis. A four-marker immunohistochemical panel (WT1/p53/napsin A/PR) can distinguish the five principal histotypes with high accuracy, and additional immunohistochemical markers can be used depending on the diagnostic considerations. Histotypes are further stratified into molecular subtypes and assessed with predictive biomarker tests. HGSCs have recently been subclassified based on mechanisms of chromosomal instability, mRNA expression profiles or individual candidate biomarkers. ECs are composed of the same molecular subtypes (POLE-mutated/mismatch repair-deficient/no specific molecular profile/p53-abnormal) with the same prognostic stratification as their endometrial counterparts. Although methylation analyses and gene expression and sequencing showed at least two clusters, the molecular subtypes of CCCs remain largely elusive to date. Mutational and immunohistochemical data on LGSC have suggested five molecular subtypes with prognostic differences. While our understanding of the molecular composition of ovarian carcinomas has significantly advanced and continues to evolve, the need for treatment options suitable for these alterations is becoming more obvious. Further preclinical studies using histotype-defined and molecular subtype-characterized model systems are needed to expand the therapeutic spectrum for women diagnosed with ovarian carcinomas.

Systemic Analysis of the DNA Replication Regulator MCM Complex in Ovarian Cancer and Its Prognostic Value

Microliposome maintenance (MCM) 2, MCM3, MCM4, MCM5, MCM6, and MCM7 are DNA replication regulators and are involved in the progression of multiple cancer types, but their role in ovarian cancer is still unclear. The purpose of this study is to clarify the biological function and prognostic value of the MCM complex in ovarian cancer (OS) progression. We analyzed DNA alterations, mRNA and protein levels, protein structure, PPI network, functional enrichment, and prognostic value in OC based on the Oncomine, cBioPortal, TCGA, CPTAC, PDB, GeneMANIA, DAVID, KEGG, and GSCALite databases. The results indicated that the protein levels of these DNA replication regulators were increased significantly. Moreover, survival analysis showed a prognostic signature based on the MCM complex, which performed moderately well in terms of OS prognostic prediction. Additionally, protein structure, functional enrichment, and PPI network analyses indicated that the MCM complex synergistically promoted OC progression by accelerating DNA replication and the cell cycle. In conclusion, our study suggested that the MCM complex might be a potential target and prognostic marker for OC patients.