Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer

Identification of CXCL13 as a Promising Biomarker for Immune Checkpoint Blockade Therapy and PARP Inhibitor Therapy in Ovarian Cancer

Ovarian cancer has poor response rates to immune checkpoint blockade (ICB) therapy, despite the use of genomic sequencing to identify molecular targets. Homologous recombination deficiency (HRD) is a conventional indicator of genomic instability (GI) and has been used as a marker for targeted therapies. Indicators reflecting HRD status have shown potential in predicting the efficacy of ICB treatment. Public databases, including TCGA, ICGC, and GEO, were used to obtain data. HRD scores, neoantigen load, and TMB were obtained from the TCGA cohort. Candidate biomarkers were validated in multiple databases, such as the Imvigor210 immunotherapy cohort and the open-source single-cell sequencing database. Immunohistochemistry was performed to further validate the results in independent cohorts. CXCL10, CXCL11, and CXCL13 were found to be significantly upregulated in HRD tumors and exhibited prognostic value. A comprehensive analysis of the tumor immune microenvironment (TIME) revealed that CXCL13 expression positively correlated with neoantigen load and immune cell infiltration. In addition, single-cell sequencing data and clinical trial results supported the utility of CXCL13 as a biomarker for ICB therapy. Not only does CXCL13 serve as a biomarker reflecting HRD status, but it also introduces a potentially novel perspective on prognostic biomarkers for ICB in ovarian cancer.

Column chart prediction model for ovarian cancer based on serum ovarian tumor related biomarkers and validation

PURPOSE

The aim was to study the predictive model and validate serum ovarian tumor-related biomarkers for ovarian cancer histograms.

METHOD

We randomly selected 181 patients with ovarian tumors and 80 healthy individuals who underwent physical examinations from the hospital's medical record information system as the study participants. Clinical data and detection results of ovarian tumor-related markers such as serum carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9), and human epididymal protein (HE4) were collected from all study participants for analysis.

RESULT

Significant differences were found in serum CEA, CA125, CA19-9, and HE4 levels between healthy controls, benign ovarian tumors, and ovarian cancer (P ​< ​0.05). Dysmenorrhea (present), family history (present), age at menarche, menstrual period, number of pregnancies, natural abortion frequency, number of induced abortions, CEA, CA125, CA19-9, HE4 were all influencing factors for the incidence of ovarian cancer (P ​< ​0.05). The number of induced abortions, CEA, CA125, CA19-9, and HE4 were all independent risk factors for ovarian cancer, while the natural abortion frequency was a protective factor for ovarian cancer (P ​< ​0.05). The constructed column chart prediction model had good discrimination and prediction accuracy for ovarian cancer, good clinical utility, and higher predictive performance for ovarian cancer than traditional ROMA models.

CONCLUSION

The ovarian cancer column chart prediction model based on serum ovarian tumor related markers has good discrimination and prediction accuracy for ovarian cancer, with high clinical utility. Future research may need to incorporate more serum markers related to ovarian cancer to further improve the performance of predictive models.

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors continues to pose significant challenges due to variability in image performance, resulting in a lack of objectivity that relies heavily on the expertise of medical professionals. This challenge can be addressed through the emergence and advancement of radiomics, which enables high-throughput extraction of valuable information from conventional medical images. Furthermore, radiomics can integrate with genomics, a novel approach termed radiogenomics, which allows for a more comprehensive, precise, and personalized assessment of tumor biological features. In this review, we present an extensive overview of the application of radiomics and radiogenomics in diagnosing and predicting ovarian tumors. The findings indicate that artificial intelligence methods based on imaging can accurately differentiate between benign and malignant ovarian tumors, as well as classify their subtypes. Moreover, these methods are effective in forecasting survival rates, treatment outcomes, metastasis risk, and recurrence for patients with OC. It is anticipated that these advancements will function as decision-support tools for managing OC while contributing to the advancement of precision medicine.

Gynecological Insights into Lynch Syndrome-A Comprehensive Review of Cancer Screening and Prevention

Lynch syndrome, one of the most common genetic syndromes predisposing to cancer, is associated with a series of malignant conditions, among which the most frequent is colorectal cancer, but gynecologic cancers (especially endometrial) are also quite common. Despite the significant progress made in understanding this condition over time, there are still aspects in managing this condition that have not demonstrated clear benefits. This article aims to summarize the recommendations of international societies and present the latest developments in managing Lynch syndrome, focusing on gynecologic cancer screening and possible prevention strategies. Advances in genetic testing procedures and discoveries related to the association between oncological pathology frequency and the affected pathogenic variant type will probably lead to personalized medicine focused on the individual patient in the coming years. Although various screening methods for gynecological cancers in patients with Lynch syndrome have been used over time, they have not shown significant survival benefits. This highlights the need for studying and implementing new screening and diagnostic methods, which have been under investigation in recent years and are mentioned in this article.

Immune escape between endoplasmic reticulum stress-related cancer cells and exhausted CD8+T cells leads to neoadjuvant chemotherapy resistance in ovarian cancer

Our study aims to explore the effects of neoadjuvant chemotherapy (NACT) on tumour cells and immune cells in the immune microenvironment of patients with high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing data of paired ovarian cancer tissues were analysed before and after NACT in 11 patients with HGSOC. The effect of NACT on two major cell components of the tumour microenvironment, epithelial cells and CD8+T cells, was investigated. The mechanisms of epithelial cell evasion by NACT and immune killing were explored from the perspectives of gene expression, functional characteristics, transcriptional regulation, and cell communication. Key targets for reversing NACT resistance were identified and possible therapeutic strategies proposed. While NACT improved the de novo differentiation of anti-tumour CD8+T cells, enhancing their anti-tumour function, it increased the proportion of cancer cells with high HSP90B1 expression. Thus, the potential reasons for NACT resistance were identified as: 1) high levels of endoplasmic reticulum stress (ERS) characteristics, 2) high expression of the MDK-NCL ligand-receptor pair between them and exhausted CD8+T cells before NACT, and 3) high expression of the NECTIN2-TIGIT immune ligand-receptor pair between them and exhausted CD8+T cells after NACT. Thus, our study reveals the mechanisms underlying NACT resistance in patients with HGSOC from the perspective of the independent and interactive roles of cancer cells and CD8+T cells. We propose therapeutic strategies targeting the ERS marker HSP90B1 and the immune escape marker MDK before or during NACT, while targeting NECTIN2 blockade after NACT. This approach may offer new insights into combination treatments for patients with HGSOC displaying NACT resistance.

Serum miRNA improves the accuracy of a multivariate index assay for triage of an adnexal mass

OBJECTIVE

To determine whether a multimodal assay combining serum microRNA with protein biomarkers and metadata improves triage assessment of an adnexal mass.

METHODS

Serum samples from 468 training subjects (191 cancer cases and 277 benign adnexal mass controls or healthy controls) were analyzed for seven protein biomarkers and 180 miRNA. Circulating analyte data were combined with age and menopausal status (metadata) into a neural network model to classify samples as cases or controls. Forward regression with ten-fold cross-validation minimized the dimensionality of the model while maximizing linear separation between cases and controls. Model validation proceeded using both internal (44 cases and 56 controls) and external validation sets (51 cases and 59 controls).

RESULTS

The total study population comprised 678 subjects, including 286 cases and 392 controls. Overall, 290 (43%) of the subjects were premenopausal. A panel of 10 miRNA delivered optimal performance when combined with protein and metadata features. The combined model improved the Receiver Operator Characteristic Area Under the Curve (ROC AUC) on the internal (AUC = 0.9; 95% CI 0.81-0.95) and external validation sets (AUC = 0.95; 95% CI 0.90-0.98) compared to miRNA alone or proteins plus metadata (without miRNA). On external validation, the combined model offered 92% sensitivity at 80% specificity overall, with 80% and 100% sensitivity for early and late-stage cancers, respectively, including 78% sensitivity for early-stage, serous ovarian cancers and 82% sensitivity for early-stage, non-serous cancers.

CONCLUSIONS

A multimodal assay combining miRNA with protein biomarkers, age, and menopausal status improves surgical triage of an adnexal mass.

Utilization of miRNAs as Biomarkers for the Diagnosis, Prognosis, and Metastasis in Gynecological Malignancies

Gynecological cancer is a term referring to malignancies that typically involve ovarian, cervical, uterine, vaginal, and vulvar cancer. Combined, these cancers represent major causes of morbidity and mortality in women with a heavy socioeconomic impact. MiRNAs are small non-coding RNAs that are intensively studied in the field of cancer and changes in them have been linked to a variety of processes involved in cancer that range from tumorigenesis to prognosis and metastatic potential. This review aims to summarize the existing literature that has linked miRNAs with each of the female malignancies as potential biomarkers in diagnosis (circulating miRNAs), in tumor histology and prognosis (as tissue biomarkers), and for local (lymph node) and distant metastatic disease.

Biomarkers From Discovery to Clinical Application: In Silico Pre-Clinical Validation Approach in the Face of Lung Cancer

Background

Clinical biomarkers, allow better classification of patients according to their disease risk, prognosis, and/or response to treatment. Although affordable omics-based approaches have paved the way for quicker identification of putative biomarkers, validation of biomarkers is necessary for translation of discoveries into clinical application.

Objective

Accordingly, in this study, we emphasize the potential of in silico approaches and have proposed and applied 3 novel sequential in silico pre-clinical validation steps to better identify the biomarkers that are truly desirable for clinical investment.

Design

As protein biomarkers are becoming increasingly important in the clinic alongside other molecular biomarkers and lung cancer is the most common cause of cancer-related deaths, we used protein biomarkers for lung cancer as an illustrative example to apply our in silico pre-clinical validation approach.

Methods

We collected the reported protein biomarkers for 3 cases (lung adenocarcinoma-LUAD, squamous cell carcinoma-LUSC, and unspecified lung cancer) and evaluated whether the protein biomarkers have cancer altering properties (i.e., act as tumor suppressors or oncoproteins and represent cancer hallmarks), are expressed in body fluids, and can be targeted by FDA-approved drugs.

Results

We collected 3008 protein biomarkers for lung cancer, 1189 for LUAD, and 182 for LUSC. Of these protein biomarkers for lung cancer, LUAD, and LUSC, only 28, 25, and 6 protein biomarkers passed the 3 in silico pre-clinical validation steps examined, and of these, only 5 and 2 biomarkers were specific for lung cancer and LUAD, respectively.

Conclusion

In this study, we applied our in silico pre-clinical validation approach the protein biomarkers for lung cancer cases. However, this approach can be applied and adapted to all cancer biomarkers. We believe that this approach will greatly facilitate the transition of cancer biomarkers into the clinical phase and offers great potential for future biomarker research.

Evaluation of circulating plasma proteins in prostate cancer using mendelian randomization

BACKGROUND

The proteome is an important resource for exploring potential diagnostic and therapeutic targets for cancer. This study aimed to investigate the causal associations between plasma proteins and prostate cancer (PCa), and to explore the downstream phenotypes that plasma proteins may influence and potential upstream intervening factors.

METHODS

Proteome-wide Mendelian randomization was used to investigate the causal effects of plasma proteins on PCa. Colocalization analysis examined the common causal variants between plasma proteins and PCa. Summary-statistics-based Mendelian Randomization (SMR) analyses identified associations between the expression of protein-coding genes and PCa. Phenome-wide association study was performed to explore the effect of target proteins on downstream phenotypes. Finally, a systematic Mendelian randomization analysis between lifestyle factors and plasma proteins was performed to assess upstream intervening factors for plasma proteins.

RESULTS

The findings revealed a positive genetic association between the predicted plasma levels of nine proteins and an elevated risk of PCa, while four proteins exhibited an inverse association with PCa risk. SMR analyses revealed ZG16B, PEX14 in blood and ZG16B, NAPG in prostate tissue were potential drug targets for PCa. The genetic association of PEX14 with PCa was further supported by colocalization analysis. Further Phenome-wide association study showed possible side effects of ZG16B, PEX14 and NAPG as drug targets. 10 plasma proteins (RBP7, TPST1, NFASC, LAYN, HDGF, SERPIMA5, DLL4, EFNA3, LIMA1, and CCL27) could be modulated by lifestyle-related factors.

CONCLUSION

This study explores the genetic associations between plasma proteins and PCa, provides evidence that plasma proteins serve as potential drug targets and enhances the understanding of the molecular etiology, prevention and treatment of PCa.

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.

Prevalence of CEA, CA 125, and CA 15-3 serum tumour markers in different regions of Saudi Arabia

OBJECTIVES

To study the prevalence of tumor marker (TM) carcinoembryonic antigen (CEA), cancer antigen 125 (CA 125), and cancer antigen 15-3 (CA 15-3) levels in the Saudi population, based on gender, age, and demographic region, and whether the patients were referred by a hospital or self-referred.

METHODS

Retrospective analysis was carried out on 7,019 samples gathered from the Western, Northern, Central, Southern, and Eastern regions of Saudi Arabia between 2021-2022. The TMs were categorized into normal and abnormal levels, according to the reference ranges. Statistical analysis was carried out to assess the relations between variants (age groups, gender, and demographic regions) using the Chi-square test, and their correlations were assessed using Spearman's test.

RESULTS

Among all patients, CEA, CA 125, and CA 15-3 levels were found to be significantly correlated with age (p=0.0001). The CEA and CA 15-3 levels increased in both males and females with age. The CA 125 was shown to have an abnormally increased level in males with age.

CONCLUSION

Increased levels of CEA, CA 125, and CA 15-3 TMs in the study population were significantly correlated with age. The CEA and CA 15-3 levels were within the normal range, while CA 125 levels were above the normal range in the older male population. These results suggest that the utilization of such TMs is age dependent and would have validity if applied with other parameters.

Exploring the cross-cancer effect of circulating proteins and discovering potential intervention targets for 13 site-specific cancers

BACKGROUND

The proteome is an important reservoir of potential therapeutic targets for cancer. This study aimed to examine the causal associations between plasma proteins and cancer risk and to identify proteins with cross-cancer effects.

METHODS

Genetic instruments for 3991 plasma proteins were extracted from a large-scale proteomic study. Summary-level data of 13 site-specific cancers were derived from publicly available datasets. Proteome-wide Mendelian randomization and colocalization analyses were used to investigate the causal effect of circulating proteins on cancers. Protein-protein interactions and druggability assessment were conducted to prioritize potential therapeutic targets. Finally, systematical Mendelian randomization analysis between healthy lifestyle factors and cancer-related proteins was conducted to identify which proteins could act as interventional targets by lifestyle changes.

RESULTS

Genetically determined circulating levels of 58 proteins were statistically significantly associated with 7 site-specific cancers. A total of 39 proteins were prioritized by colocalization, of them, 11 proteins (ADPGK, CD86, CLSTN3, CSF2RA, CXCL10, GZMM, IL6R, NCR3, SIGLEC5, SIGLEC14, and TAPBP) were observed to have cross-cancer effects. Notably, 5 of these identified proteins (CD86, CSF2RA, CXCL10, IL6R, and TAPBP) have been targeted for drug development in cancer therapy; 8 proteins (ADPGK, CD86, CXCL10, GZMM, IL6R, SIGLEC5, SIGLEC14, TAPBP) could be modulated by healthy lifestyles.

CONCLUSION

Our study identified 39 circulating protein biomarkers with convincing causal evidence for 7 site-specific cancers, with 11 proteins demonstrating cross-cancer effects, and prioritized the proteins as potential intervention targets by either drugs or lifestyle changes, which provided new insights into the etiology, prevention, and treatment of cancers.

FoxO1 promotes ovarian cancer by increasing transcription and METTL14-mediated m6A modification of SMC4

The transcription factor forkhead box protein O1 (FoxO1) is closely related to the occurrence and development of ovarian cancer (OC), however its role and molecular mechanisms remain unclear. Herein, we found that FoxO1 was highly expressed in clinical samples of OC patients and was significantly correlated with poor prognosis. FoxO1 knockdown inhibited the proliferation of OC cells in vitro and in vivo. ChIP-seq combined with GEPIA2 and Kaplan-Meier database analysis showed that structural maintenance of chromosome 4 (SMC4) is a downstream target of FoxO1, and FoxO1 promotes SMC4 transcription by binding to its -1400/-1390 bp promoter. The high expression of SMC4 significantly blocked the tumor inhibition effect of FoxO1 knockdown. Furtherly, FoxO1 increased SMC4 mRNA abundance by transcriptionally activating methyltransferase-like 14 (METTL14) and increasing SMC4 m6A methylation on its coding sequence region. The Cancer Genome Atlas dataset analysis confirmed a significant positive correlation between FoxO1, SMC4, and METTL14 expression in OC. In summary, this study revealed the molecular mechanisms of FoxO1 regulating SMC4 and established a clinical link between the expression of FoxO1/METTL14/SMC4 in the occurrence of OC, thus providing a potential diagnostic target and therapeutic strategy.

Screening and prevention of ovarian cancer

Ovarian cancer remains the most lethal gynaecological malignancy with 314 000 cases and 207 000 deaths annually worldwide. Ovarian cancer cases and deaths are predicted to increase in Australia by 42% and 55% respectively by 2040. Earlier detection and significant downstaging of ovarian cancer have been demonstrated with multimodal screening in the largest randomised controlled trial of ovarian cancer screening in women at average population risk. However, none of the randomised trials have demonstrated a mortality benefit. Therefore, ovarian cancer screening is not currently recommended in women at average population risk. More frequent surveillance for ovarian cancer every three to four months in women at high risk has shown good performance characteristics and significant downstaging, but there is no available information on a survival benefit. Population testing offers an emerging novel strategy to identify women at high risk who can benefit from ovarian cancer prevention. Novel multicancer early detection biomarker, longitudinal multiple marker strategies, and new biomarkers are being investigated and evaluated for ovarian cancer screening. Risk-reducing salpingo-oophorectomy (RRSO) decreases ovarian cancer incidence and mortality and is recommended for women at over a 4-5% lifetime risk of ovarian cancer. Pre-menopausal women without contraindications to hormone replacement therapy (HRT) undergoing RRSO should be offered HRT until 51 years of age to minimise the detrimental consequences of premature menopause. Currently risk-reducing early salpingectomy and delayed oophorectomy (RRESDO) should only be offered to women at increased risk of ovarian cancer within the context of a research trial. Pre-menopausal early salpingectomy is associated with fewer menopausal symptoms and better sexual function than bilateral salpingo-oophorectomy. A Sectioning and Extensively Examining the Fimbria (SEE-FIM) protocol should be used for histopathological assessment in women at high risk of ovarian cancer who are undergoing surgical prevention. Opportunistic salpingectomy may be offered at routine gynaecological surgery to all women who have completed their family. Long term prospective opportunistic salpingectomy studies are needed to determine the effect size of ovarian cancer risk reduction and the impact on menopause.

Transcriptome analysis reveals the clinical significance of CXCL13 in Pan-Gyn tumors

BACKGROUND

Gynecologic and breast tumors (Pan-Gyn) exhibit similar characteristics, and the role of CXCL13 in anti-tumor immunity and it's potential as a biomarker for immune checkpoint blockade (ICB) therapy have been gradually revealed. However, the precise role of CXCL13 in Pan-Gyn remains unclear, lacking a systematic analysis.

METHODS

We analyzed 2497 Pan-Gyn samples from the TCGA database, categorizing them into high and low CXCL13 expression groups. Validation was conducted using tumor expression datasets sourced from the GEO database. Correlation between CXCL13 and tumor immune microenvironment (TIME) was evaluated using multiple algorithms. Finally, we established nomograms for 3-year and 5-year mortality.

RESULTS

High expression of CXCL13 in Pan-Gyn correlates with a favorable clinical prognosis, increased immune cell infiltration, and reduced intra-tumor heterogeneity. Model was assessed using the C-index [BRCA: 0.763 (0.732-0.794), UCEC: 0.821 (0.793-0.849), CESC: 0.736 (0.684-0.788), and OV: 0.728 (0.707-0.749)], showing decent prediction of discrimination and calibration.

CONCLUSION

Overall, this study provides comprehensive insights into the commonalities and differences of CXCL13 in Pan-Gyn, potentially opening new avenues for personalized treatment.

Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4

Ovarian cancer (OC) is the most lethal gynaecologic malignancy, attributed to its insidious growth, non-specific symptoms and late presentation. Unfortunately, current screening modalities are inadequate at detecting OC and many lack the appropriate specificity and sensitivity that is desired from a screening test. Nearly 70% of cases are diagnosed at stage III or IV with poor 5-year overall survival. Therefore, the development of a sensitive and specific biomarker for early diagnosis and screening for OC is of utmost importance. Currently, diagnosis is guided by CA125, the patient's menopausal status and imaging features on ultrasound scan. However, emerging evidence suggests that a combination of CA125 and HE4 (another serum biomarker) and patient characteristics in a multivariate index assay may provide a higher specificity and sensitivity than either CA125 and HE4 alone in the early detection of OC. Other attempts at combining various serum biomarkers into one multivariate index assay such as OVA1, ROMA and Overa have all shown promise. However, significant barriers exist before these biomarkers can be implemented in clinical practice. This article aims to provide an up-to-date review of potential biomarkers for screening and early diagnosis of OC which may have the potential to transform its diagnostic landscape.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Early Detection of Ovarian Cancer

The risk of death from ovarian cancer is highly associated with the clinical stage at diagnosis. Efforts to implement screening for ovarian cancer have been largely unsuccessful, due to the low prevalence of the disease in the general population and the heterogeneity of the various cancer types that fall under the ovarian cancer designation. A practical test for early detection will require both high sensitivity and high specificity to balance reducing the number of cancer deaths with minimizing surgical interventions for false positive screens. The technology must be cost-effective to deliver at scale, widely accessible, and relatively noninvasive. Most importantly, a successful early detection test must be effective not only at diagnosing ovarian cancer but also in reducing ovarian cancer deaths. Stepwise or multimodal approaches among the various areas under investigation will likely be required to make early detection a reality.

Immunogenic Biomarkers HMGB1 and sRAGE Are Potential Diagnostic Tools for Ovarian Malignancies

BACKGROUND

High mobility group box 1 (HMGB1), soluble receptor of advanced glycation end products (sRAGE) and programmed cell death markers PD-1 and PD-L1 are immunogenic serum biomarkers that may serve as novel diagnostic tools for cancer diagnosis.

METHODS

We investigated the four markers in sera of 231 women, among them 76 with ovarian cancer, 87 with benign diseases and 68 healthy controls, using enzyme immunoassays. Discrimination between groups was calculated using receiver operating characteristic (ROC) curves and sensitivities at fixed 90% and 95% specificities.

RESULTS

HMGB1 levels were significantly elevated and sRAGE levels were decreased in cancer patients as compared to benign and healthy controls. In consequence, the ratio of HMGB1 and sRAGE discriminated best between diagnostic groups. The areas under the curve (AUCs) of the ROC curves for differentiation of cancer vs. healthy were 0.77 for HMGB1, 0.65 for sRAGE and 0.78 for the HMGB1/sRAGE ratio, and slightly lower for the differentiation of cancer vs. benigns with 0.72 for HMGB1, 0.61 for sRAGE and 0.74 for the ratio of both. The highest sensitivities for cancer detection at 90% specificity versus benign diseases were achieved using HMGB1 with 41.3% and the HMGB1/sRAGE ratio with 39.2%, followed by sRAGE with 18.9%. PD-1 showed only minor and PD-L1 no power for discrimination between ovarian cancer and benign diseases.

CONCLUSION

HMGB1 and sRAGE have differential diagnostic potential for ovarian cancer detection and warrant inclusion in further validation studies.

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.

Cytokine profiling identifies circulating IL-6 and IL-15 as prognostic stratifiers in patients with non-small cell lung cancer receiving anti-PD-1/PD-L1 blockade therapy

Whether circulating levels of specific cytokines at baseline link with treatment efficacy of immune checkpoint blockade (ICB) therapy in patients with non-small cell lung cancer remains unknown. In this study, serum samples were collected in two independent, prospective, multicenter cohorts before the initiation of ICB. Twenty cytokines were quantified, and cutoff values were determined by receiver operating characteristic analyses to predict non-durable benefit. The associations of each dichotomized cytokine status with survival outcomes were assessed. In the discovery cohort (atezolizumab cohort; N = 81), there were significant differences in progression-free survival (PFS) in accordance with the levels of IL-6 (log-rank test, P = 0.0014), IL-15 (P = 0.00011), MCP-1 (P = 0.013), MIP-1β (P = 0.0035), and PDGF-AB/BB (P = 0.016). Of these, levels of IL-6 and IL-15 were also significantly prognostic in the validation cohort (nivolumab cohort, N = 139) for PFS (log-rank test, P = 0.011 for IL-6 and P = 0.00065 for IL-15) and overall survival (OS; P = 3.3E-6 for IL-6 and P = 0.0022 for IL-15). In the merged cohort, IL-6^high and IL-15^high were identified as independent unfavorable prognostic factors for PFS and OS. The combined IL-6 and IL-15 status stratified patient survival outcomes into three distinct groups for both PFS and OS. In conclusion, combined assessment of circulating IL-6 and IL-15 levels at baseline provides valuable information to stratify the clinical outcome of patients with non-small cell lung cancer treated with ICB. Further studies are required to decipher the mechanistic basis of this finding.

Performance of IOTA Simple Rules Risks, ADNEX Model, Subjective Assessment Compared to CA125 and HE4 with ROMA Algorithm in Discriminating between Benign, Borderline and Stage I Malignant Adnexal Lesions

BACKGROUND

Borderline ovarian tumors (BOTs) and early clinical stage malignant adnexal masses can make sonographic diagnosis challenging, while the clinical utility of tumor markers, e.g., CA125 and HE4, or the ROMA algorithm, remains controversial in such cases.

OBJECTIVE

To compare the IOTA group Simple Rules Risk (SRR), the ADNEX model and the subjective assessment (SA) with serum CA125, HE4 and the ROMA algorithm in the preoperative discrimination between benign tumors, BOTs and stage I malignant ovarian lesions (MOLs).

METHODS

A multicenter retrospective study was conducted with lesions classified prospectively using subjective assessment and tumor markers with the ROMA. The SRR assessment and ADNEX risk estimation were applied retrospectively. The sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-) were calculated for all tests.

RESULTS

In total, 108 patients (the median age: 48 yrs, 44 postmenopausal) with 62 (79.6%) benign masses, 26 (24.1%) BOTs and 20 (18.5%) stage I MOLs were included. When comparing benign masses with combined BOTs and stage I MOLs, SA correctly identified 76% of benign masses, 69% of BOTs and 80% of stage I MOLs. Significant differences were found for the presence and size of the largest solid component (p = 0.0006), the number of papillary projections (p = 0.01), papillation contour (p = 0.008) and IOTA color score (p = 0.0009). The SRR and ADNEX models were characterized by the highest sensitivity (80% and 70%, respectively), whereas the highest specificity was found for SA (94%). The corresponding likelihood ratios were as follows: LR+ = 3.59 and LR- = 0.43 for the ADNEX; LR+ = 6.40 and LR- = 0.63 for SA and LR+ = 1.85 with LR- = 0.35 for the SRR. The sensitivity and specificity of the ROMA test were 50% and 85%, respectively, with LR+ = 3.44 and LR- = 0.58. Of all the tests, the ADNEX model had the highest diagnostic accuracy of 76%.

CONCLUSIONS

This study demonstrates the limited value of diagnostics based on CA125 and HE4 serum tumor markers and the ROMA algorithm as independent modalities for the detection of BOTs and early stage adnexal malignant tumors in women. SA and IOTA methods based on ultrasound examination may present superior value over tumor marker assessment.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Molecular Biomarkers for the Early Detection of Ovarian Cancer

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

Serum immune modulators associated with immune-related toxicities and efficacy of atezolizumab in patients with non-small cell lung cancer

PURPOSE

Identifying patients at high risk of immune-related adverse events (irAEs) that impede the achievement of durable efficacy of programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) blockade therapy is important in improving their management. Identification of a novel predictive factor of therapeutic benefit is also important in improving patient selection for treatment with PD-1/PD-L1 inhibitors. Further determinants driving response and linking with irAEs are urgently required.

METHODS

To address these unmet needs in the field, we explored whether 27 soluble checkpoint proteins and immunomodulatory proteins in serum at the therapy baseline and after week 3 were associated with irAE onset and therapeutic efficacy using MILLIPLEX Human Immuno-Oncology Checkpoint Protein Panel assays in a prospective, multicenter cohort of 81 patients with non-small cell lung cancer (NSCLC) receiving atezolizumab monotherapy.

RESULTS

By competing-risks regression analysis, we identified that high levels of B cell-activating factor (BAFF) at baseline were a significant and strong risk factor of irAEs (hazard ratio, 5.61; 95% confidence interval, 2.43-12.96; P < 0.0001). We also identified that increased inducible T cell co-stimulator (ICOS) during the first therapeutic cycle was an independent factor associated with prolonged progression-free survival and overall survival.

CONCLUSION

These findings are in keeping with the reported mechanistic basis of these molecules and may provide potential guidance for clinical decision-making to improve patient care. Further validation studies are warranted. Trial registration UMIN000035616 (January 28, 2019).

Development of a Multiprotein Classifier for the Detection of Early Stage Ovarian Cancer

BACKGROUND

Individual serum biomarkers are neither adequately sensitive nor specific for use in screening the general population for ovarian cancer. The purpose of this study was to develop a multiprotein classifier to detect the early stages of ovarian cancer, when it is most treatable.

METHODS

The Olink Proseek Multiplex Oncology II panel was used to simultaneously quantify the expression levels of 92 cancer-related proteins in sera.

RESULTS

In the discovery phase, we generated a multiprotein classifier that included CA125, HE4, ITGAV, and SEZ6L, based on an analysis of sera from 116 women with early stage ovarian cancer and 336 age-matched healthy women. CA125 alone achieved a sensitivity of 87.9% at a specificity of 95%, while the multiprotein classifier resulted in an increased sensitivity of 91.4%, while holding the specificity fixed at 95%. The performance of the multiprotein classifier was validated in a second cohort comprised of 192 women with early stage ovarian cancer and 467 age-matched healthy women. The sensitivity at 95% specificity increased from 74.5% (CA125 alone) to 79.2% with the multiprotein classifier. In addition, the multiprotein classifier had a sensitivity of 95.1% at 98% specificity for late stage ovarian cancer samples and correctly classified 80.5% of the benign samples using the 98% specificity cutpoint.

CONCLUSIONS

The inclusion of the proteins HE4, ITGAV, and SEZ6L improved the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer in serum samples. Furthermore, we identified several proteins that may be novel biomarkers of early stage ovarian cancer.

Applications of Proteomics in Ovarian Cancer: Dawn of a New Era

The ability to identify ovarian cancer (OC) at its earliest stages remains a challenge. The patients present an advanced stage at diagnosis. This heterogeneous disease has distinguishable etiology and molecular biology. Next-generation sequencing changed clinical diagnostic testing, allowing assessment of multiple genes, simultaneously, in a faster and cheaper manner than sequential single gene analysis. Technologies of proteomics, such as mass spectrometry (MS) and protein array analysis, have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of OC. Proteomics analysis of OC, as well as their adaptive responses to therapy, can uncover new therapeutic choices, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is an urgent need to better understand how the genomic and epigenomic heterogeneity intrinsic to OC is reflected at the protein level, and how this information could potentially lead to prolonged survival.

Detection of plasma exosomal miRNA-205 as a biomarker for early diagnosis and an adjuvant indicator of ovarian cancer staging

Background

Ovarian cancer (OC) is one of the serious threats to the health of women worldwide, and accurate biomarkers are urgently demanded for early diagnosis of OC. We have previously confirmed that miR-205 promotes the invasion and metastasis of OC cells by inhibiting the expression of the tumor suppressor gene TCF21. In this study, we used liquid biopsy technology to detect the expression levels of the four genes, miR-205, CA125, HE4 and TCF21, in the exosomes of plasma of OC patients. Combined with analysis of clinicopathological parameters of OC patients, we aimed to provide efficient and non-invasive laboratory biomarkers for early diagnosis of OC.

Methods

36 OC patients who were diagnosed in local hospitals from September 2020 to July 2021 were selected as OC group, 31 cases of surgically diagnosed with ovarian benign lesions were selected as benign group, and 32 healthy people who underwent physical examination during the same period were selected as a control group. We employed transmission electron microscope (TEM), Western blotting (WB), and nanoparticle tracking analysis (NTA) to identify biomarkers in the exosomes extracted from plasma of the three groups. The RNA levels of miR-205, CA125, HE4 and TCF21 genes in plasma exosomes were detected by real-time quantitative PCR (qRT-PCR) method. We used clinical pathological parameters and the Receiver Operating Characteristic (ROC) curves to evaluate the diagnostic efficacy for the genes detected in plasma exosomes.

Results

We found that the expression level of miR-205 in plasma exosomes of the OC group was significantly higher than that of the benign and control groups (P <  0.05), and the level of miR-205 was elevated during the III-IV periods of OC and lymph node metastasis.

Conclusion

The level of miR-205 in plasma exosomes is a valuable tumor biomarker to improve OC diagnosis.