Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated with prognosis

Searching for prognostic markers for Stage I epithelial ovarian cancer: A role for systemic inflammatory markers

OBJECTIVE

To determine the prognostic role of systemic inflammatory markers for Stage I epithelial ovarian cancer (EOC).

MATERIALS AND METHODS

We performed a retrospective, single-center, observational study. We included patients with Stage I EOC cancer undergoing primary surgery between 1993 and 2016. Inflammatory markers were assessed by analyzing blood samples collected at initial diagnosis before EOC surgery. We evaluated these markers' association with disease-free survival (DFS) and cancer-specific survival (CSS).

RESULTS

We included 176 women in our study. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) were related to both DFS and CSS in the univariate analysis. In the multivariate Cox analysis, adjuvant chemotherapy (hazard ratio [HR] 0.17, 95% confidence interval [CI] 0.04-0.71, P = 0.02) and SII ≥730 (HR 6.84, 95% CI 1.30-35.9, P = 0.023) were independent predictors of DFS, while FIGO Stage IB-IC (HR 7.91, 95% CI 1.04-59.8, P = 0.04), NLR ≥3 (HR 56.8, 95% CI 7.46-433, P < 0.001) and PLR ≥169 (HR 49.1 95% CI 11.1-217.8, P = 0.005) were independent predictors of CSS.

CONCLUSIONS

Systemic inflammatory markers are easily obtainable from patients' routine blood analyses and may represent inexpensive and reproducible prognostic markers in early-stage EOC.

Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer

Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic TP53 mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.

A pan-cancer landscape of pathogenic somatic copy number variations

OBJECTIVE

Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions.

METHODS

Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival.

RESULTS

Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression.

CONCLUSION

This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

Gynecological Healthcare: Unveiling Pelvic Masses Classification through Evolutionary Gravitational Neocognitron Neural Network Optimized with Nomadic People Optimizer

Accurate and early detection of malignant pelvic mass is important for a suitable referral, triage, and for further care for the women diagnosed with a pelvic mass. Several deep learning (DL) methods have been proposed to detect pelvic masses but other methods cannot provide sufficient accuracy and increase the computational time while classifying the pelvic mass. To overcome these issues, in this manuscript, the evolutionary gravitational neocognitron neural network optimized with nomadic people optimizer for gynecological abdominal pelvic masses classification is proposed for classifying the pelvic masses (EGNNN-NPOA-PM-UI). The real time ultrasound pelvic mass images are augmented using random transformation. Then the augmented images are given to the 3D Tsallis entropy-based multilevel thresholding technique for extraction of the ROI region and its features are further extracted with the help of fast discrete curvelet transform with the wrapping (FDCT-WRP) method. Therefore, in this work, EGNNN optimized with nomadic people optimizer (NPOA) was utilized for classifying the gynecological abdominal pelvic masses. It was executed in PYTHON and the efficiency of the proposed method analyzed under several performance metrics. The proposed EGNNN-NPOA-PM-UI methods attained 99.8%. Ultrasound image analysis using the proposed EGNNN-NPOA-PM-UI methods can accurately predict pelvic masses analyzed with the existing methods.

Hormone Receptors and Epithelial Ovarian Cancer: Recent Advances in Biology and Treatment Options

Epithelial ovarian cancer (EOC) is a significant cause of cancer-related mortality in women. Despite advances in diagnosis and treatment, EOC remains a challenging disease to manage, and the 5-year survival rate is still poor. The role of hormone receptors (HRs) in EOC carcinogenesis and prognosis has been actively explored; however, the role of hormone therapy (HT) in the treatment of these tumors is not well established. Most available data on HT mainly come from retrospective series and small early clinical trials. Several of these studies suggest that HT may have a role in adjuvant, maintenance therapy, or in the case of recurrent disease, especially for some subtypes of EOC (e.g., low-grade serous EOC). Furthermore, HT has recently been combined with targeted therapies, but most studies evaluating these combinations are still ongoing. The main aim of this review is to provide an overview of the progress made in the last decade to characterize the biological and prognostic role of HRs for EOC and the developments in their therapeutic targeting through HT.

Genomic landscapes of ovarian clear cell carcinoma from latin countries reveal aberrations linked to survival and progression

BACKGROUND

Ovarian clear cell carcinomas (OCCCs) are rare, aggressive and chemoresistant tumors. Geographical and ethnic differences in the incidence of OCCC have been reported with a higher incidence in Asiatic countries. There is a paucity of information regarding OCCC in Latin America (LA) and other countries.

METHODS

Here, we characterized two cohorts of 33 patients with OCCC from LA (24 from Brazil and 9 from Costa Rica) and a cohort of 27 patients from Spain. Genomic analysis was performed for 26 OCCC using the OncoScan platform. Tumors were classified according to their genomic landscapes into subgroups. Clinical parameters were related to the frequency of genomic aberrations.

RESULTS

The median overall survival (OS) was not significantly different between the cohorts. Genomic landscapes were characterized by different homologous recombination deficiency (HRD) levels. No difference in the distribution of genomic landscapes profiles was detected between patients from the different cohorts. OCCCs with MYC-amplified tumors harboring a concomitant loss of a region in chromosome 13q12-q13 that includes the BRCA2 gene had the longest OS. In contrast, patients carrying a high number (> 30) of total copy number (CN) aberrations with no concomitant alterations in MYC and BRCA2 genes presented the shortest OS. Furthermore, amplification of the ASH1L gene was also associated with a shorter OS. Initial-stage OCCCs with early progression were characterized by gains in the JNK1 and MKL1 genes.

CONCLUSIONS

Our results provide new data from understudied OCCC populations and reveal new potential markers for OCCCs.

A comprehensive investigation of histotype-specific microRNA and their variants in Stage I epithelial ovarian cancers

isomiRs, the sequence-variants of microRNA, are known to be tissue and cell type specific but their physiological role is largely unknown. In our study, we explored for the first time the expression of isomiRs across different Stage I epithelial ovarian cancer (EOC) histological subtypes, in order to shed new light on their biological role in tumor growth and progression. In a multicentric retrospective cohort of tumor biopsies (n = 215) we sequenced small RNAs finding 971 expressed miRNAs, 64% of which are isomiRs. Among them, 42 isomiRs showed a clear histotype specific pattern, confirming our previously identified miRNA markers (miR192/194 and miR30a-3p/5p for mucinous and clear cell subtypes, respectively) and uncovering new biomarkers for all the five subtypes. Using integrative models, we found that the 38% of these miRNA expression alterations is the result of copy number variations while the 17% of differential transcriptional activities. Our work represents the first attempt to characterize isomiRs expression in Stage I EOC within and across subtypes and to contextualize their alterations in the framework of the large genomic heterogeneity of this tumor.

Update on Prognostic and Predictive Markers in Mucinous Ovarian Cancer

This review includes state-of-the-art prognostic and predictive factors of mucinous ovarian cancer (MOC), a rare tumor. Clinical, pathological, and molecular features and treatment options according to prognosis are comprehensively discussed. Different clinical implications of MOC are described according to the The International Federation of Gynecology and Obstetrics (FIGO) stage: early MOC (stage I-II) and advanced MOC (stage III-IV). Early MOC is characterized by a good prognosis. Surgery is the mainstay of treatment. Fertility-sparing surgery could be performed in patients who wish to become pregnant and that present low recurrence risk of disease. Adjuvant chemotherapy is not recommended, except in patients with high-risk clinical and pathological features. Regarding the histological features, an infiltrative growth pattern is the major prognostic factor of MOC. Furthermore, novel molecular biomarkers are emerging for tailored management of early-stage MOC. In contrast, advanced MOC is characterized by poor survival. Radical surgery is the cornerstone of treatment and adjuvant chemotherapy is recommended, although the efficacy is limited by the intrinsic chemoresistance of these tumors. Several molecular hallmarks of advanced MOC have been described in recent years (e.g., HER2 amplification, distinct methylation profiles, peculiar immunological microenvironment), but target therapy for these rare tumors is not available yet.