Recent Advancements in Prognostic Factors of Epithelial Ovarian Carcinoma

Exploring a multiparameter MRI-based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma

OBJECTIVES

To develop a multiparameter magnetic resonance imaging (MRI)-based radiomics approach that can accurately predict the tumor cell proliferation status of serous ovarian carcinoma (SOC).

MATERIALS AND METHODS

A total of 134 patients with SOC who met the inclusion and exclusion criteria were retrospectively screened from institution A, spanning from January 2016 to March 2022. Additionally, an external validation set comprising 42 SOC patients from institution B was also included. The region of interest was determined by drawing each ovarian mass boundaries manually slice-by-slice on T2-weighted imaging fat-suppressed fast spin-echo (T2FSE) and T1 with contrast enhancement (T1CE) images using ITK-SNAP software. The handcrafted radiomic features were extracted, and then were selected using variance threshold algorithm, SelectKBest algorithm, and least absolute shrinkage and selection operator. The optimal radiomic scores and the clinical/radiological independent predictors were integrated as a combined model.

RESULTS

Compared with the area under the curve (AUC) values of each radiomic signature of T2FSE and T1CE, respectively, the AUC value of the radiomic signature (T1CE-T2FSE) was the highest in the training set (0.999 vs. 0.965 and 0.860). The homogeneous solid component of the ovarian mass was considered the only independent predictor of tumor cell proliferation status among the clinical/radiological variables. The AUC of the radiomic-radiological model was 0.999.

CONCLUSIONS

The radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can accurately predict tumor cell proliferation status of SOC which has high repeatability and may enable more targeted and effective treatment strategies.

CRITICAL RELEVANCE STATEMENT

The proposed radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can predict tumor cell proliferation status of SOC which has high repeatability and may guide individualized treatment programs.

KEY POINTS

• The radiomic-radiological nomogram may guide individualized treatment programs of SOC. • This radiomic-radiological nomogram showed a favorable prediction ability. • Homogeneous slightly higher signal intensity on T2FSE is vital for Ki-67.

Prognostic role of different PD-L1 expression patterns and tumor-infiltrating lymphocytes in high-grade serous ovarian cancer: a systematic review and meta-analysis

Background

The prognostic value of programmed cell death ligand 1 (PD-L1) expression and tumor-infiltrating lymphocytes (TILs) in high-grade serous ovarian cancer (HGSOC) remains a controversial topic in the research field. To comprehensively assess the importance of PD-L1 and TILs in this particular subtype of ovarian cancer, we performed a meta-analysis.

Methods

We conducted a comprehensive search of PubMed, Embase, Scopus, Web of Science, and Cochrane Library databases up to December 25, 2022. The association between PD-L1, TILs, and survival outcomes was evaluated using the combined hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs).

Results

This meta-analysis comprised 11 trials involving a total of 1746 cases. The results revealed no significant association between PD-L1 expression in tumor cells (TCs) and overall survival (OS, HR = 0.76, 95% CI: 0.52-1.09, p = 0.136) or progression-free survival (PFS, HR = 0.71, 95% CI: 0.4 -1.24, p = 0.230). Nevertheless, a correlation was observed between PD-L1 expression in immune cells (ICs) and OS (HR = 0.73, 95% CI: 0.55-0.97, p = 0.031). Furthermore, the presence of CD8+ and PD-1+ TILs was found to significantly enhance OS (HR = 0.70, 95% CI = 0.55-0.87, p = 0.002; HR = 0.57, 95% CI = 0.40-0.80, p = 0.001, respectively) and PFS (HR = 0.62, 95% CI = 0.41-0.92, p = 0.019; HR = 0.52, 95% CI = 0.35-0.78, p = 0.002, respectively), whereas the presence of CD3+ and CD4+ TILs was positively associated with OS (HR = 0.50, 95% CI = 0.29-0.87, p = 0.014; HR = 0.55, 95% CI = 0.34-0.91, p = 0.020, respectively).

Conclusion

This study indicates a positive correlation between ICs-derived PD-L1 and survival, while no significant correlation was observed between TCs-derived PD-L1 and prognosis. These results highlight the importance of studying PD-L1 expression in ICs as a prognostic predictor. In addition, the presence of TILs was found to significantly improve patient survival, suggesting that TILs may be a valuable prognostic biomarker.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022366411.

CA-125 Levels Are Predictive of Survival in Low-Grade Serous Ovarian Cancer-A Multicenter Analysis

Simple Summary

Low-grade serous cancer (LGSC) accounts for approximately 5% of all ovarian cancers. It is characterized by its high resistance to chemotherapy. Cytoreductive surgery, therefore, is the primary treatment modality for this disease and previous studies have shown that complete removal of all visible tumor tissue should be achieved. In this study, 176 women with LGSC were included and most of them had advanced disease stages, where the disease had already spread. CA-125 is a biomarker that has been previously studied in ovarian cancer. We have found that CA-125 level following treatment of LGSC is an important and independent prognostic factor for progression-free and overall survival. It may be a better surrogate for the true amount of residual disease following treatment compared to the gross estimation of visible residual disease during surgery.

Abstract

Objective: Studies on low-grade serous ovarian cancer (LGSC) are limited by a low number of cases. The aim of this study was to define the prognostic significance of age, stage, and CA-125 levels on survival in a multi-institutional cohort of women with pathologically confirmed LGSC. Methods: Women with LGSC were identified from the collaborative Ovarian Cancer Association Consortium (OCAC). Cases of newly diagnosed primary LGSC were included if peri-operative CA-125 levels were available. Age at diagnosis, FIGO stage, pre- and post-treatment CA-125 levels, residual disease, adjuvant chemotherapy, disease recurrence, and vital status were collected by the participating institutions. Progression-free (PFS) and overall survival (OS) were calculated. Multivariable (MVA) Cox proportional hazard models were used and hazard ratios (HR) calculated. Results: A total of 176 women with LGSC were included in this study; 82% had stage III/IV disease. The median PFS was 2.3 years and the median OS was 6.4 years. Age at diagnosis was not significantly associated with worse PFS (p = 0.23) or OS (p = 0.3) (HR per year: 0.99; 95%CI, 0.96–1.01 and 0.98; 95%CI 0.95–1.01). FIGO stage III/IV was independently associated with PFS (HR 4.26, 95%CI 1.43–12.73) and OS (HR 1.69, 95%CI 0.56–5.05). Elevated CA-125 (≥35 U/mL) at diagnosis was not significantly associated with worse PFS (p = 0.87) or OS (p = 0.78) in MVA. Elevated CA-125 (≥35 U/mL) after completion of primary treatment was independently associated with worse PFS (HR 2.81, 95%CI 1.36–5.81) and OS (HR 6.62, 95%CI 2.45–17.92). In the MVA, residual disease was independently associated with PFS (0.022), but not OS (0.85). Conclusion: Advanced LGSC was associated with poor long-term prognosis. FIGO stage and abnormal post-treatment CA-125 level are key prognostic factors inversely associated with PFS and OS. Highlights: 1. Through a multi-center collaborative effort, data from 176 women with low-grade serous ovarian cancer were analyzed. 2. Although low-grade serous ovarian cancer is often considered indolent, the progression-free and overall survival are poor. 3. Elevated post-treatment CA-125 levels are independently associated with poor survival.

Computational image features of immune architecture is associated with clinical benefit and survival in gynecological cancers across treatment modalities

BACKGROUND

We present a computational approach (ArcTIL) for quantitative characterization of the architecture of tumor-infiltrating lymphocytes (TILs) and their interplay with cancer cells from digitized H&E-stained histology whole slide images and evaluate its prognostic role in three different gynecological cancer (GC) types and across three different treatment types (platinum, radiation and immunotherapy).

METHODS

In this retrospective study, we included 926 patients with GC diagnosed with ovarian cancer (OC), cervical cancer, and endometrial cancer with available digitized diagnostic histology slides and survival outcome information. ArcTIL features quantifying architecture and spatial interplay between immune cells and the rest of nucleated cells (mostly comprised cancer cells) were extracted from the cell cluster graphs of nuclei within the tumor epithelial nests, surrounding stroma and invasive tumor front compartments on H&E-stained slides. A Cox proportional hazards model, incorporating ArcTIL features was fit on the OC training cohort (N=51), yielding an ArcTIL signature. A unique threshold learned from the training set stratified the patients into a low and high-risk group.

RESULTS

The seven feature ArcTIL classifier was found to significantly correlate with overall survival in chemotherapy and radiotherapy-treated validation cohorts and progression-free survival in an immunotherapy-treated validation cohort. ArcTIL features relating to increased density of TILs in the epithelium and invasive tumor front were found to be associated with better survival outcomes when compared with those patients with an increased TIL density in the stroma. A statistically significant association was found between the ArcTIL signature and signaling pathways for blood vessel morphogenesis, vasculature development, regulation of cell differentiation, cell-substrate adhesion, biological adhesion, regulation of vasculature development, and angiogenesis.

CONCLUSIONS

This study reveals that computationally-derived features from the spatial architecture of TILs and tumor cells are prognostic in GCs treated with chemotherapy, radiotherapy, and checkpoint blockade and are closely associated with central biological processes that impact tumor progression. These findings could aid in identifying therapy-refractory patients and further enable personalized treatment decision-making.

Meta-analysis identifying epithelial-derived transcriptomes predicts poor clinical outcome and immune infiltrations in ovarian cancer

BACKGROUND

Previous studies revealed that the epithelial component is associated with the modulation of the ovarian tumor microenvironment (TME). However, the identification of key transcriptional signatures of laser capture microdissected human ovarian cancer epithelia remains lacking.

METHODS

We identified the differentially expressed transcriptional signatures of human ovarian cancer epithelia by meta-analysis of GSE14407, GSE2765, GSE38666, GSE40595, and GSE54388. Then we investigated the enrichment of KEGG pathways that are associated with epithelia-derived transcriptomes. Finally, we investigated the correlation of key epithelia-hub genes with the survival prognosis and immune infiltrations. Finally, we investigated the genetic alterations of key prognostic hub genes and their diagnostic efficacy in ovarian cancer epithelia.

RESULTS

We identified 1339 differentially expressed genes (DEGs) in ovarian cancer epithelia including 541upregulated and 798 downregulated genes. We identified 21 (such as E2F4, FOXM1, TFDP1, E2F1, and SIN3A) and 11 (such as JUN, DDX4, FOSL1, NOC2L, and HMGA1) master transcriptional regulators (MTRs) that are interacted with upregulated and the downregulated genes in ovarian tumor epithelium, respectively. The STRING-based analysis identified hub genes (such as CDK1, CCNB1, AURKA, CDC20, and CCNA2) in ovarian cancer epithelia. The significant clusters of identified hub genes are associated with the enrichment of KEGG pathways including cell cycle, DNA replication, cytokine-cytokine receptor interaction, pathways in cancer, and focal adhesion. The upregulation of SCNN1A and CDCA3 and the downregulation of SOX6 are correlated with a shorter survival prognosis in ovarian cancer (OV). The expression level of SOX6 is negatively correlated with immune score and positively correlated with tumor purity in OV. Moreover, SOX6 is negatively correlated with the infiltration of TILs, CD8+ T cells, CD4+ Regulatory T cells, cytolytic activity, T cell activation, pDC, neutrophils, and macrophages in OV. Also, SOX6 is negatively correlated with various immune markers including CD8A, PRF1, GZMA, GZMB, NKG7, CCL3, and CCL4, indicating the immune regulatory efficiency of SOX6 in the TME of OV. Furthermore, SCNN1A, CDCA3, and SOX6 genes are genetically altered in OV and the expression levels of SCNN1A and SOX6 genes showed diagnostic efficacy in ovarian cancer epithelia.

CONCLUSIONS

The identified ovarian cancer epithelial-derived key transcriptional signatures are significantly correlated with survival prognosis and immune infiltrations, and may provide new insight into the diagnosis and treatment of epithelial ovarian cancer.

An Italian National Survey on Ovarian Cancer Treatment at first diagnosis. There's None so Deaf as those who will not Hear

Objective: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, crucial prognostic factors are no gross residual disease and centralization of cases. To evaluate the centralization of EOC patients, we report the results of a survey that shows the daily management of EOC patients in Italy.

Methods: A 49-items electronic unblinded survey assessing demographics, practice characteristics, current opinions and approach to managing advanced EOC at first diagnosis was sent both to general gynecologists (GG) and gynecologic oncologists (GO). Differences in frequency distribution of answers between gynecologists with different expertise were evaluated using Fisher exact test. Multivariable analyses were performed applying generalized linear models.

Results: 84/192 (44%) GG and 108/192 (56%) GO from all Italian regions answered to our survey. GOs declared to perform fertility sparing surgery in early EOC more frequently than GG (p=0.002).

GOs can perform a frozen section and have both a gynecopathologist and a dedicated general surgeon. 89% of GOs consider as “optimal debulking” no gross residual disease and 81% achieve this at upfront cytoreduction in more than 40% of patients. Use of neoadjuvant chemotherapy decreases in higher volume centers (p<0.001) while it is lower in the group of GOs than in the GGs group (p<0.001).

Conclusions: EOC patients are still treated by GGs. GOs perform more upfront surgery and achieve optimal debulking in a greater percentage of patients than GGs. In Italy an adequate centralization of cases has not yet been achieved, and this may have detrimental effects on the quality of treatment.

Construction autophagy-related prognostic risk signature to facilitate survival prediction, individual treatment and biomarker excavation of epithelial ovarian cancer patients

Background

Existing clinical methods for prognosis evaluating for Epithelial Ovarian Cancer (EOC) patients had defects of invasive, unsystematic and subjective and little data are available for individualizing treatment, therefore, to identify potential prognostic markers and new therapeutic targets for EOC is urgently required.

Results

Expression of 232 autophagy-related genes (ARGs) in 354 EOC and 56 human ovarian surface epithelial specimens from 7 independent laboratories were analyzed, 31 mRNAs were identified as DEARGs. We did functional and pathway enrichment analysis and constructed protein–protein interaction network for all DEARGs. To screen out candidate DEARGs related to EOC patients’ survival and construct an autophagy-related prognostic risk signature, univariate and multivariate Cox proportional hazards models were established separately. Finally, 5 optimal independent prognostic DEARGs (PEX3, DNAJB9, RB1, HSP90AB1 and CXCR4) were confirmed and the autophagy-related risk model was established by the 5 prognostic DEARGs. The accuracy and robustness of the prognostic risk model for survival prediction were evaluated and verified by analyzing the correlation between EOC patients’ survival status, clinicopathological features and risk scores.

Conclusions

The autophagy-related prognostic risk model can be independently used to predict overall survival in EOC patients, it can also potentially assist in individualizing treatment and biomarker development.

Ovarian cancer risk score predicts chemo-response and outcome in epithelial ovarian carcinoma patients

OBJECTIVE

Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients.

METHODS

We designed a case-control study with total 149 EOC women including 75 chemosensitives and 74 chemoresistants. Gene expression was measured using the quantitative real-time polymerase chain reaction. We tested for correlation between the OVRS and chemosensitivity or chemoresistance, disease-free survival (DFS), and overall survival (OS), and validated the OVRS by analyzing patients from the TCGA database.

RESULTS

The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p≤0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p<0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p<0.001) had higher OVRS than those without. OVRS ≥10 (hazard ratio=3.29; 95% confidence interval=1.94-5.58; p<0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. >60 months) of patients with OVRS ≥10 were significantly shorter than those of patients with OVRS <10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046).

CONCLUSIONS

Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer.

Expression of Circulating MicroRNA-141 in Epithelial Ovarian Cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is a lethal disease due to late diagnosis and lack of effective screening methods. MicroRNA (miR/miRNA) plays an important role in ovarian carcinogenesis and may serve as a non-invasive biomarker for EOC. This study aimed to assess miR-141 expression in the blood plasma of patients with EOC and healthy subjects and determine its association with the clinical stage of EOC.

METHODS

This cross-sectional study used blood plasma from 30 newly diagnosed untreated patients with EOC and 25 healthy subjects. The mean age was 47.73 (SD = 10.29) years for EOC and 44.48 (SD = 16.14) years for healthy subject. The total RNA was isolated from blood plasma and reversed transcribed to obtain cDNA. The expression of miR-141 was measured by real-time quantitative polymerase chain reaction (qRT-PCR), and calculated using 2-ΔΔCt methods. The data were analysed using Mann-Whitney test.

RESULTS

The expression of miR-141 was upregulated 8.41 fold in the blood plasma of EOC patients compared to healthy controls (P < 0.001). Expression of miR-141 in the advanced stage was upregulated 4.2 fold compared to the early stage (P < 0.001).

CONCLUSION

The miR-141 was upregulated in the blood plasma of EOC and associated with an advanced stage of disease, suggesting it has potential as a biomarker for EOC detection.

AB0 Blood Group and Ovarian Cancer Survival

Background: Epithelial ovarian cancer is the most lethal gynecological malignancy because is usually diagnosed at advanced stage. New prognostic factors have been investigated but these biomarkers do not have a strong direct relationship with survival. Several studies investigated the association between AB0 blood group with ovarian cancer but with conflicting results. We investigated the association between AB0 blood group and epithelial ovarian cancer patients consecutively surgically treated at our department from 2004 to 2015.

Methods: Clinical charts of ovarian cancer patients treated and followed from 2004 to 2015 were checked for inclusion and exclusion criteria. Clinical and pathological data were recorded in an electronic separate, anonymous, password-protected database. All relevant data were extrapolated and used for final analysis.

Results: A population of 265 ovarian cancer patients was analyzed in this study. 121 (45.6%) patients presented blood type 0, 112 (42.3%) had blood type A, 23 (8.7%) B and 9 (3.4%) AB. A significantly lower percentage of death (8.7%) in patients with blood type B in comparison with patients presenting different genotypes (group 0: 34.7%, group A: 32.1%, group AB: 22.2%) was found. In invasive serous ovarian cancer patients the analysis showed a 5 fold significant reduction of the risk of death in patients with B genotype. However, postoperative residual tumor resulted the most important prognostic factor for overall survival.

Conclusions: AB0 blood group might be a preoperative prognostic factor in epithelial ovarian cancer patients. According to the literature, postoperative residual disease remain the most important prognostic factor also in our study.

The Potential Role of iNOS in Ovarian Cancer Progression and Chemoresistance

Inducible nitric oxide synthase (iNOS), the enzyme responsible for nitric oxide (NO) production, is not present in most cells under normal conditions. The expression of its mRNA, as well as its protein synthesis and full enzymatic activity, undergoes multilevel regulation including transcriptional and posttranscriptional mechanisms, the availability of iNOS substrate and cofactors and oxygen tension. However, in various malignant diseases, such as ovarian cancer, the intracellular mechanisms controlling iNOS are dysregulated, resulting in the permanent induction of iNOS expression and activation. The present review summarizes the multistaged processes occurring in normal cells that promote NO synthesis and focuses on factors regulating iNOS expression in ovarian cancer. The possible involvement of iNOS in the chemoresistance of ovarian cancer and its potential as a prognostic/predictive factor in the course of disease development are also reviewed. According to the available yet limited data, it is difficult to draw unequivocal conclusions on the pros and cons of iNOS in ovarian cancer. Most clinical data support the hypothesis that high levels of iNOS expression in ovarian tumors are associated with a greater risk of disease relapse and patient death. However, in vitro studies with various ovarian cancer cell lines indicate a correlation between a high level of iNOS expression and sensitivity to cisplatin.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Molecular genetics complexity impeding research progress in breast and ovarian cancers

Breast and ovarian cancer are heterogeneous diseases. While breast cancer accounts for 25% of cancers worldwide, ovarian cancer accounts for 3.5% of all cancers and it is considered to be the most lethal type of cancer among women. In Oman, breast cancer accounts for 25% and ovarian cancer for 4.5% of all cancer cases. Various risk factors, including variable biological and clinical traits, are involved in the onset of breast and ovarian cancer. Although highly developed diagnostic and therapeutic methods have paved the way for better management, targeted therapy against specific biomarkers has not yet shown any significant improvement, particularly in triple-negative breast cancer and epithelial ovarian cancer, which are associated with high mortality rates. Thus, elucidating the mechanisms underlying the pathology of these diseases is expected to improve their prevention, prognosis and management. The aim of the present study was to provide a comprehensive review and updated information on genomics and proteomics alterations associated with cancer pathogenesis, as reported by several research groups worldwide. Furthermore, molecular research in our laboratory, aimed at identifying new pathways involved in the pathogenesis of breast and ovarian cancer using microarray and chromatin immunoprecipitation (ChIP), is discussed. Relevant candidate genes were found to be either up- or downregulated in a cohort of breast cancer cases. Similarly, ChIP analysis revealed that relevant candidate genes were regulated by the E2F5 transcription factor in ovarian cancer tissue. An ongoing study aims to validate these genes with a putative role as biological markers that may contribute to the development of targeted therapies for breast and ovarian cancer.

Diagnostic and Prognostic Significance of Ki-67 Immunohistochemical Expression in Surface Epithelial Ovarian Carcinoma

INTRODUCTION

The Surface Epithelial Ovarian Carcinoma (SEOC) at the moment of diagnosis, the disease is extended beyond the structures of the pelvis. Ki-67 is one of the prognostic marker which determines the growth fraction of a tumour and its over expression is associated with malignancy, tumour aggression, reserved prognosis and metastasis.

AIM

To evaluate the proliferative activity using Ki-67 immuno-staining in SEOC and to correlate with histological subtype, grade, Federation of Gynecology and Obstetrics (FIGO) stage, CA125 levels for diagnostic and prognostic purpose.

MATERIALS AND METHODS

The study was conducted in JSS Medical College and Hospital, JSS University, Mysuru. It was a descriptive cross-sectional study involving 40 cases of SEOC over a period of two years. The proliferation expression related to Ki-67 antigen was evaluated by immunohistochemical monoclonal MIB-1 antibody. In each case, the Ki-67 labeling index (Ki-67 LI) was articulated as percentage of positively stained cells using high power objective of the microscope (x400).

RESULTS

Among the 40 carcinomas, 26 were serous, five mucinous, four each of clear cell and undifferentiated and one transitional cell carcinoma. A total of 75% were high grade tumours. High Ki-67 LI was associated with high grade tumours (69.9%), high grade serous tumours (65.34%) and advanced FIGO staging (70.6%) with the p-value of <0.001. CA 125 levels did not have a significant correlation with Ki-67 LI.

CONCLUSION

Ki-67 is an exceptionally a cost effective marker to determine the growth fraction of a tumour cell population. In SEOC histological grade and FIGO stage when combined with Ki-67 LI in histopathology report would help in diagnostic differentiation of subtypes, prognostication, deciding the need for adjuvant chemotherapy and in predicting survival analysis.

Lesser-Known Molecules in Ovarian Carcinogenesis

Currently, the deciphering of the signaling pathways brings about new advances in the understanding of the pathogenic mechanism of ovarian carcinogenesis, which is based on the interaction of several molecules with different biochemical structure that, consequently, intervene in cell metabolism, through their role as regulators in proliferation, differentiation, and cell death. Given that the ensemble of biomarkers in OC includes more than 50 molecules the interest of the researchers focuses on the possible validation of each one's potential as prognosis markers and/or therapeutic targets. Within this framework, this review presents three protein molecules: ALCAM, c-FLIP, and caveolin, motivated by the perspectives provided through the current limited knowledge on their role in ovarian carcinogenesis and on their potential as prognosis factors. Their structural stability, once altered, triggers the initiation of the sequences characteristic for ovarian carcinogenesis, through their role as modulators for several signaling pathways, contributing to the disruption of cellular junctions, disturbance of pro-/antiapoptotic equilibrium, and alteration of transmission of the signals specific for the molecular pathways. For each molecule, the text is built as follows: (i) general remarks, (ii) structural details, and (iii) particularities in expression, from different tumors to landmarks in ovarian carcinoma.