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.

Clinicopathologic Impact of NANOG, ZEB1, and EpCAM Biomarkers on Prognosis of Serous Ovarian Carcinoma

OBJECTIVES

Serous ovarian carcinoma (SOC) is a biologically heterogeneous with different genomic and molecular profiles, beside clinical response to the chemotherapy with subsequent in obstacles in starting unified, acceptable treatments and so we assess immunoexpression of Nanog, ZEB1, and EpCAM in SOC.

METHODS

In this study, the immunoexpression of Nanog, ZEB1, and EpCAM was studied in 60 cases of SOC. Overall survival (OS), disease-free survival (DFS) data and response to chemotherapy were  analyzed.

RESULTS

NANOG was immunostained in 65% of the cases with a significant association with tumor grade, lymph node metastasis, and FIGO stage (p < 0.001 for each). ZEB1 showed moderate- high expression in 58.3% of the cases with significant up-regulation of ZEB1 expression with SOC grade, nodal metastasis, and SOC FIGO stage (p<0.001). EpCAM revealed high expression in 60% of the cases with significant association with higher grade, nodal metastasis, and advanced stage (p < 0.001 for each). Up-regulation of Nanog was significantly associated with response to chemotherapy, relapse, shorter OS and DFS (p < 0.001 for each). ZEB1 overexpression exhibited a significant association with response to chemotherapy (p= 0.012), relapse, shorter OS and DFS (p<0.001 for each). Moreover, the high EpCAM had a significant association with response to chemotherapy (p= 0.043), relapse (p < 0.001) shorter OS (p=0.006) and DFS (p< 0.001).

CONCLUSIONS

Up-regulation of Nanog and ZEB-1 and EpCAM perhaps promote an aggressive SOC with a high risk of relapse and unfavorable response to standard chemotherapy regimen.

Association of UBE2L6 and ABCB6 Expression With Platinum Resistance in Serous Ovarian Carcinoma

BACKGROUND/AIM

Platinum-based drugs are the standard treatment for ovarian cancer, and platinum resistance is a major problem. A previous study has reported that the UBE2L6 expression is elevated in cisplatin-resistant cells, which in turn leads to cisplatin resistance by modulating the transcriptional expression of ABCB6. The present study aimed to investigate the expression of UBE2L6 and ABCB6 in ovarian carcinoma and to evaluate the association between these markers and platinum resistance.

PATIENTS AND METHODS

Ninety-two patients diagnosed with serous ovarian carcinoma (SOC) were enrolled in this study. Tissue samples were collected from these patients and analysed using immunohistochemistry to assess the expression of UBE2L6 and ABCB6.

RESULTS

UBE2L6 and ABCB6 staining was positive in 41 (44.6%) and 46 (50.0%) cases, respectively. UBE2L6 expression was statistically significantly associated with International Federation of Gynecology and Obstetrics (FIGO) stage (p=0.008). Both UBE2L6 and ABCB6 were significantly associated with platinum sensitivity (p<0.001 and p<0.001). A positive correlation was observed between the expression levels of UBE2L6 and ABCB6 (r=0.673, p<0.001). Progression-free survival (PFS) was significantly longer in the UBE2L6 negative group than that in the positive group (median PFS, 31.4 vs. 11.1 months, p<0.01) and in the ABCB6 negative group than that in the positive group (median PFS, 29.6 vs. 12.2 months, p<0.01).

CONCLUSION

UBE2L6 and ABCB6 expression is associated with the prognosis of SOC. UBE2L6 and ABCB6 may be potential biomarkers of platinum-resistant ovarian cancer.

Prognostic risk factors of serous ovarian carcinoma based on mesenchymal stem cell phenotype and guidance for therapeutic efficacy

BACKGROUND

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in which serous ovarian carcinoma (SOC) is the most common histological subtype. Although PARP inhibitors (PARPi) and antiangiogenics have been accepted as maintenance treatment in SOC, response to immunotherapy of SOC patients is limited.

METHODS

The source of transcriptomic data of SOC was from the Cancer Genome Atlas database and Gene Expression Omnibus. The abundance scores of mesenchymal stem cells (MSC scores) were estimated for each sample by xCell. Weighted correlation network analysis is correlated the significant genes with MSC scores. Based on prognostic risk model construction with Cox regression analysis, patients with SOC were divided into low- and high-risk groups. And distribution of immune cells, immunosuppressors and pro-angiogenic factors in different risk groups was achieved by single-sample gene set enrichment analysis. The risk model of MSC scores was further validated in datasets of immune checkpoint blockade and antiangiogenic therapy. In the experiment, the mRNA expression of prognostic genes related to MSC scores was detected by real-time polymerase chain reaction, while the protein level was evaluated by immunohistochemistry.

RESULTS

Three prognostic genes (PER1, AKAP12 and MMP17) were the constituents of risk model. Patients classified as high-risk exhibited worse prognosis, presented with an immunosuppressive phenotype, and demonstrated high micro-vessel density. Additionally, these patients were insensitive to immunotherapy and would achieve a longer overall survival with antiangiogenesis treatment. The validation experiments showed that the mRNA of PER1, AKAP12, and MMP17 was highly expressed in normal ovarian epithelial cells compared to SOC cell lines and there was a positive correlation between protein levels of PER1, AKAP12 and MMP17 and metastasis in human ovarian serous tumors.

CONCLUSION

This prognostic model established on MSC scores can predict prognosis of patients and provide the guidance for patients receiving immunotherapy and molecular targeted therapy. Because the number of prognostic genes was fewer than other signatures of SOC, it will be easily accessible on clinic.

Searching for the source: Extraovarian primary peritoneal carcinoma presenting as chest wall masses

Background

Extraovarian primary peritoneal carcinoma (EOPPC) is a rare form of epithelial adenocarcinoma arising from the peritoneal lining with little to no ovarian involvement. To date, very few cases of EOPPC with primary tumors outside of the peritoneum have been described, the majority of which present with a primary tumor in the retroperitoneum. No cases have been reported with primary presentation as a chest wall mass.

Case report

This case describes a 64-year-old woman referred for the evaluation of PAX8 positive chest wall masses. Biopsies of these masses demonstrated tumor architecture that was predominantly micropapillary with rare psammomatous calcifications. Immunohistochemically, the tumor was PAX8, CK7, ER, MOC31, and BerEP4 positive, with a mutational pattern of p53. This was consistent with Mullerian adenocarcinoma markers and suggestive of high-grade serous carcinoma. The patient was diagnosed with a unique presentation of EOPPC and is currently alive at 36 months post initial diagnosis. She has been treated with a combination of diagnostic surgery, chemotherapy and radiation therapy.

Conclusion

To the best of our knowledge, this is the first documented case of EOPPC presenting with a primary tumor of the chest wall. This case highlights the importance of pathology, immunohistology, and interdisciplinary collaboration in diagnosing and treating rare malignancies.

[Cytopathological characterization of ascites for the diagnosis of serous ovarian carcinoma]

Objective: To investigate the cytomorphological and immunocytochemical features of tumor cells in the ascites of ovarian plasmacytoma (SOC). Methods: Specimens of serous cavity effusions were collected from 61 tumor patients admitted to the Affiliated Wuxi People's Hospital of Nanjing Medical University from January 2015 to July 2021, including ascites from 32 SOC, 10 gastrointestinal adenocarcinomas, 5 pancreatic ductal adenocarcinomas, 6 lung adenocarcinomas, 4 benign mesothelial hyperplasia and 1 malignant mesothelioma patients, pleural effusions from 2 malignant mesothelioma patients and pericardial effusion from 1 malignant mesothelioma. Serous cavity effusion samples of all patients were collected, conventional smears were made through centrifugation, and cell paraffin blocks were made through centrifugation of remaining effusion samples. Conventional HE staining and immunocytochemical staining were applied to observe and summarize cytomorphological characteristics and immunocytochemical characteristics. The levels of serum tumor markers carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were detected. Results: Of the 32 SOC patients, 5 had low-grade serous ovarian carcinoma (LGSOC) and 27 had high-grade serous ovarian carcinoma (HGSOC). 29 (90.6%) SOC patients had elevated serum CA125, but the difference was not statistically significant between them and patients with non-ovarian primary lesions included in the study (P>0.05); The serum CEA was positive in 9 patients with gastrointestinal adenocarcinoma and 5 patients with lung adenocarcinoma, and the positive rate was higher than that in SOC patients (P<0.001); The serum CA19-9 was positive in 5 patients with gastrointestinal adenocarcinoma and 5 patients with pancreatic ductal adenocarcinoma, and the positive rate was higher than that in SOC patients (P<0.05). The serum CA125, CEA and CA19-9 were within the normal range in 4 patients with benign mesothelial hyperplasia. LGSOC tumor cells were less heterogeneous and aggregated into small clusters or papillary pattern, and psammoma bodies could be observed in some LGSOC cases. The background cells were fewer and lymphocytes were predominant; the papillary structure was more obvious after making cell wax blocks. HGSOC tumor cells were highly heterogeneous, with significantly enlarged nuclei and varying sizes, which could be more than 3-fold different, and nucleoli and nuclear schizophrenia could be observed in some cases; tumor cells were mostly clustered into nested clusters, papillae and prune shapes; there were more background cells, mainly histiocytes. Immunocytochemical staining showed that AE1/AE3, CK7, PAX-8, CA125, and WT1 were diffusely positively expressed in 32 SOC cases. P53 was focally positive in all 5 LGSOCs, diffusely positive in 23 HGSOCs, and negative in the other 4 HGSOCs. Most of adenocarcinomas of the gastrointestinal tract and lung had a history of surgery, and tumor cells of pancreatic ductal adenocarcinoma tend to form small cell nests. Immunocytochemistry can assist in the differential diagnosis of mesothelial-derived lesions with characteristic "open window" phenomenon. Conclusion: Combining the clinical manifestations of the patient, the morphological characteristics of the cells in the smear and cell block of the ascites can provide important clues for the diagnosis of SOC, and the immunocytochemical tests can further improve the accuracy of the diagnosis.

A prediction nomogram for suboptimal debulking surgery in patients with serous ovarian carcinoma based on MRI T1 dual-echo imaging and diffusion-weighted imaging

BACKGROUND

Serous ovarian carcinoma (SOC) has the highest morbidity and mortality among ovarian carcinoma. Accurate identification of the probability of suboptimal debulking surgery (SDS) is critical. This study aimed to develop a preoperative prediction nomogram of SDS for patients with SOC.

METHODS

A prediction model was established including 205 patients of SOC from institution A, and 45 patients from institution B were enrolled for external validation. Multivariate logistic regression was used to screen independent predictors and establish a nomogram to predict the occurrence of SDS.

RESULTS

Multivariate logistic regression demonstrated that the CA-125 level (odds ratio [OR] 8.260, 95% confidence interval [CI] 2.003-43.372), relationship between the sigmoid colon/rectum and ovarian mass (OR 28.701, 95% CI 4.561-286.070), diaphragmatic metastasis (OR 12.369, 95% CI 1.675-274.063), and FIGO stage (OR 32.990, 95% CI 6.623-274.509) were independent predictors for SDS. The area under the curve, concordance index, and 95% CI of the nomogram constructed from the above four factors were 0.951, 0.934, and 0.919-0.982, respectively. The model showed a good fit by the Hosmer-Lemeshow test (training set, p = 0.2475; internal validation set, p = 0.2355; external validation set, p = 0.2707). The external validation proved the reliability of the prediction nomogram. The calibration curve was close to the ideal diagonal line. The decision curve analysis demonstrated a significantly better net benefit. The clinical impact curve indicated good effectiveness in clinical application.

CONCLUSION

A prediction nomogram for SDS in patients with SOC provides gynecologists with an accurate and effective tool for appropriate management.

Assessing the predictive response of a simple and sensitive blood-based biomarker between estrogen-negative solid tumors

PURPOSE

We investigated N^w-hydroxy l-Arginine (NOHA) predictive response in serous ovarian carcinoma based on estrogen-hormone receptor expression status; and assessed the distinctive NOHA response between estrogen-receptor-negative (ER-) tumor subtypes of ovarian and breast cancer.

MATERIALS/METHODS

Three-dimensional (3D) spheroids models of ER- and estrogen-receptor-positive (ER+) from breast and ovarian tumor, cultured for 9 weeks, were assayed for cellular levels of inducible nitric oxide synthase (NOS2), nitric oxide (as total nitrite) and l-Arginine, and compared to NOHA in culture medium. Statistical difference was set at p < 0.01.

RESULTS

Nine-week in vitro studies showed a progressive NOHA reduction in culture medium by at least 0.4-0.8 fold, and 0.65-0.92 fold only in the ER- breast tumor and ER- ovarian tumor 3D spheroids, respectively; with increases in cellular NOS2 and nitric-oxide levels, by at least 1.0-2.45 fold in both ER- tumor subtype 3D spheroids (p < 0.01; n = 6). Within ER- subtypes, medium NOHA decreased by ≥ 38.9% in ovarian cancer over breast cancer 3D-spheroids, with cellular increases in NOS2 (by ≥ 17.4%), and nitric oxide (by ≥ 18.8%). Cellular l-Arginine to medium NOHA ratio was higher, and by at least 6.5-22.5 fold in ER- breast tumor 3D-spheroids, and at least 10-70 fold in ER- ovarian tumor 3D spheroids, than in ER+ and control conditions; and was ≥48% higher in ER- ovarian cancer than in ER- breast cancer 3D-spheroids.

CONCLUSIONS

The present study shows NOHA as a sensitive and selective indicator differentiating and distinguishing ER- subtypes based on the tumor grade.

Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks

BACKGROUND

Ovarian cancer causes 151,900 deaths per year worldwide. Treatment and prognosis are primarily determined by the histopathologic interpretation in combination with molecular diagnosis. However, the relationship between histopathology patterns and molecular alterations is not fully understood, and it is difficult to predict patients' chemotherapy response using the known clinical and histological variables.

METHODS

We analyzed the whole-slide histopathology images, RNA-Seq, and proteomics data from 587 primary serous ovarian adenocarcinoma patients and developed a systematic algorithm to integrate histopathology and functional omics findings and to predict patients' response to platinum-based chemotherapy.

RESULTS

Our convolutional neural networks identified the cancerous regions with areas under the receiver operating characteristic curve (AUCs) > 0.95 and classified tumor grade with AUCs > 0.80. Functional omics analysis revealed that expression levels of proteins participated in innate immune responses and catabolic pathways are associated with tumor grade. Quantitative histopathology analysis successfully stratified patients with different response to platinum-based chemotherapy (P = 0.003).

CONCLUSIONS

These results indicated the potential clinical utility of quantitative histopathology evaluation in tumor cell detection and chemotherapy response prediction. The developed algorithm is easily extensible to other tumor types and treatment modalities.

Results of an abbreviated phase II study of AKT inhibitor MK-2206 in the treatment of recurrent platinum-resistant high grade serous ovarian, fallopian tube, or primary peritoneal carcinoma (NCT 01283035)

•

PI3K/AKT pathway alterations are frequently seen in ovarian cancer, providing rationale for targeted AKT inhibition.

•

AKT inhibitor MK-2206 in platinum resistant high grade serous ovarian cancer was notable for dermatologic toxicity.

•

Best response of stable disease was seen, with one patient experiencing a prolonged SD of 19 weeks.

Platinum-resistant, recurrent, high grade epithelial ovarian carcinoma remains challenging to treat. Chemotherapy produces limited responses with modest survival benefits in the treatment of recurrent disease. In this context, targeted therapies may improve upon conventional therapies. PI3K/AKT pathway alterations are frequently found in several cancer types, including ovarian cancer, and thus AKT inhibition is a rational targeted therapy. Here we report the results of an abbreviated trial of AKT inhibitor MK-2206 in platinum resistant high grade serous ovarian, fallopian tube, and primary peritoneal cancer with PTEN loss.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data

BACKGROUND

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues.

RESULTS

To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies.

CONCLUSIONS

The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Expression of Toll-like receptor 4 in ovarian serous adenocarcinoma and correlation with clinical stage and pathological grade

Toll-like receptor 4 (TLR4) plays an essential role in adaptive and innate immunity, and its expression has been described in various tumors. This study aimed to examine the expression of TLR4 in serous tumors and to evaluate its correlation to clinicopathological parameters. The expression of TLR4 was immunohistochemically examined in 63 species of normal ovarian epithelia and 336 species of serous epithelial lesions. Moreover, the association between TLR4 expression and various clinicopathologic features was assessed. The expression intensity of TLR4 in benign and borderline to malignant ovarian tumours showed a gradual rising trend. We identified positive correlations between TLR4 expression levels and both FIGO stage and pathological stage. In serous adenocarcinoma, TLR4 expression levels were significantly associated with chemoresistance. There was no relationship between the expression of TLR4 and the patient's age or pretreatment serum CA125 levels. Our data suggest that TLR4 might stimulate serous ovarian carcinoma initiation and progression. TLR4 expression is correlated with poor chemoresponse, which has important implications for the development of new therapeutic strategies for drug-resistant ovarian cancer.

Expression pattern of RAGE and IGF-1 in the human fetal ovary and ovarian serous carcinoma

The expression pattern of RAGE and IGF-1 proteins in different ovarian cell lineages was histologically analyzed in six fetal, nine adult human ovaries, and nine serous ovarian carcinomas (OSC) using immunohistochemical methods. Mild expression of IGF-1 in ovarian surface epithelium (Ose) and oocytes in the 15-week human ovaries increased to moderate or strong in the stromal cells, oocytes and follicular cells in week 22. Occasional mild RAGE expression was observed in Ose during week 15, while strong expression characterized primordial follicles in week 22. In the reproductive human ovary, IGF-1 was mildly to moderately expressed in all ovarian cell lineages except in theca cells of the tertiary follicle where IGF-1 was negative. RAGE was strongly positive in the granulosa cells and some theca cells of the tertiary follicle, while negative to mildly positive in all cells of the secondary follicle. In the postmenopausal human ovary IGF-1 and RAGE were mildly expressed in Ose and stroma. In OSC, cells were strongly positive to IGF-1 and RAGE, except for some negative stromal cells. Different levels of IGF-1 and RAGE co-expression characterized fetal ovarian cells during development. In reproductive ovaries, IGF-1 and RAGE were co-localized in the granulosa and theca interna cells of tertiary follicles, while in postmenopausal ovaries and OSC, IGF-1 and RAGE were co-localized in Ose and OSC cells respectively. Our results indicate that intracellular levels of IGF-1 and RAGE protein might regulate the final destiny of the ovarian cell populations prior and during folliculogenesis, possibly controlling the metastatic potential of OSC as well.