Mural nodules in mucinous ovarian tumors represent a morphologic spectrum of clonal neoplasms: a morphologic, immunohistochemical, and molecular analysis of 13 cases

Case report: Ovarian mucinous tumor with a mural nodule of liposarcoma: a rare case

Background

Ovarian mucinous tumor with a mural nodule is a rare and special type of ovarian surface epithelial-stromal tumor. Mural nodules are morphologically classified into three types: sarcoma-like, anaplastic carcinomatous, and true sarcomatous nodules. Ovarian mucinous tumors with true sarcomatous mural nodules are rare and challenging to diagnose, with only 10 cases reported worldwide. Currently, liposarcoma mural nodules remain unreported.

Case presentation

A 91-year-old woman was hospitalized for postmenopausal vaginal bleeding for 3 weeks. Imaging revealed a large cystic mass (20.0 cm × 17.7 cm × 12.8 cm) on the right ovary. The mass was multilocular cystic, with a mural nodule (1.4 cm × 1.2 cm × 1.0 cm) in the focal cyst wall. Based on histological morphology, immunohistochemical staining, and MDM2/CDK4 fluorescence in situ hybridization testing, the diagnosis was ovarian mucinous cystadenoma with a mural nodule of well-differentiated liposarcoma. To the best of our knowledge, this has never been reported before. High-throughput sequencing identified KRAS mutations in the ovarian mucinous cystadenoma. However, the liposarcoma mural nodule did not exhibit KRAS mutations but displayed copy number amplifications of CDK4 and DDR2, as well as a frameshift mutation in exon 13 of ASXL1 (p. A627Gfs*8).

Conclusions

This case broadens the morphological spectrum of mural nodules in ovarian mucinous tumors, deepening our knowledge of this rare morphology. Meanwhile, through high-throughput sequencing, we found no overlapping genetic evidence between the liposarcoma mural nodule and associated ovarian mucinous cystadenoma.

Recurrent mucinous carcinoma with sarcomatoid and sarcomatous mural nodules: a case report and literature review

Ovarian mucinous tumors with sarcomatous mural nodules are rare. Sarcomatous nodules have a bad prognosis. Its diagnosis and treatment are controversial.It is still controversial whether malignant mural nodules represent a dedifferentiated form of mucinous tumors or collisional tumors. This is a case report of a 32-year-old female diagnosed with ovarian mucinous tumor recurred as a mucinous carcinoma combined with sarcomatoid and undifferentiated sarcoma mural nodules after surgery and chemotherapy. The primary lesion did not have a sarcomatous component after comprehensive sampling and repeated review, while the recurrent lesion had a predominantly sarcomatous component. The patient received a second operation and postoperative chemotherapy plus Anlotinib with no progression at 16 months of follow-up. Primary mucinous carcinoma and sarcomatous mural nodules revealed the same K-RAS mutation(c.35G>T, pG12V), TP53 mutation (c.817C>T, p.R273C), MLL2 mutation(c.13450C>T, p.R4484) and NF1 mutation(c.7876A>G, p.S2626G). We present a comprehensive analysis on morphologic characteristics, molecular detection results, clinical management, and prognosis of ovarian mucinous tumors with mural nodules of sarcomatoid and undifferentiated sarcoma. Mutation sharing between primary mucinous carcinoma and recurrent sarcomatous nodules supports monoclonal origin of primary and recurrent tumors, suggesting a tendency for sarcomatous differentiation during the progression of epithelial tumors. Malignant mural nodules represent dedifferentiation in mucinous ovarian tumors rather than collision of two different tumor types. Therefore, it is imperative to conduct comprehensive sampling, rigorous clinical examination, and postoperative follow-up in order to thoroughly evaluate all mural nodules of ovarian mucinous tumors due to their potential for malignancy and sarcomatous differentiation.

An integrated machine learning-based model for joint diagnosis of ovarian cancer with multiple test indicators

OBJECTIVE

To construct a machine learning diagnostic model integrating feature dimensionality reduction techniques and artificial neural network classifiers to develop the value of clinical routine blood indexes for the auxiliary diagnosis of ovarian cancer.

METHODS

Patients with ovarian cancer clearly diagnosed in our hospital were collected as a case group (n = 185), and three groups of patients with other malignant otolaryngology tumors (n = 138), patients with benign otolaryngology diseases (n = 339) and those with normal physical examination (n = 92) were used as an overall control group. In this paper, a fully automated segmentation network for magnetic resonance images of ovarian cancer is proposed to improve the reproducibility of tumor segmentation results while effectively reducing the burden on radiologists. A pre-trained Res Net50 is used to the three edge output modules are fused to obtain the final segmentation results. The segmentation results of the proposed network architecture are compared with the segmentation results of the U-net based network architecture and the effect of different loss functions and region of interest sizes on the segmentation performance of the proposed network is analyzed.

RESULTS

The average Dice similarity coefficient, average sensitivity, average specificity (specificity) and average hausdorff distance of the proposed network segmentation results reached 83.62%, 89.11%, 96.37% and 8.50, respectively, which were better than the U-net based segmentation method. For ROIs containing tumor tissue, the smaller the size, the better the segmentation effect. Several loss functions do not differ much. The area under the ROC curve of the machine learning diagnostic model reached 0.948, with a sensitivity of 91.9% and a specificity of 86.9%, and its diagnostic efficacy was significantly better than that of the traditional way of detecting CA125 alone. The model was able to accurately diagnose ovarian cancer of different disease stages and showed certain discriminative ability for ovarian cancer in all three control subgroups.

CONCLUSION

Using machine learning to integrate multiple conventional test indicators can effectively improve the diagnostic efficacy of ovarian cancer, which provides a new idea for the intelligent auxiliary diagnosis of ovarian cancer.

Ovarian serous borderline tumor with mural nodules of anaplastic carcinoma and omental involvement: A case report

Mural nodules are rarely identified in cystic ovarian neoplasms, and have been categorized into sarcoma-like, sarcomatous, and anaplastic carcinomatous types. Most reports of these mural nodules have been described in mucinous ovarian tumors. In this case report, we describe an ovarian serous borderline tumor with mural nodules composed of high-grade carcinoma with anaplastic features and necrosis, including the morphologic features, immunoprofile, and results of tumor DNA sequencing. Omental involvement was also identified. Recognition of this phenomenon in serous tumors is important, so that thickened areas of cyst wall in ovarian serous tumors will be thoroughly examined.

Rapid recurrence of a ruptured mucinous borderline ovarian tumor harboring K-RAS mutation followed by progression into anaplastic carcinoma with TP53 mutation

We describe the case of a young patient with a borderline mucinous ovarian tumor that progressed into ipsilateral ovarian anaplastic carcinoma in only 3 months with metastasis to the contralateral ovary and extensive spread in the pelvic and abdominal regions. The mucinous tumor harbored micro-foci of intraepithelial carcinoma, but no mural nodules, microinvasion, or invasive adenocarcinoma were detected. Notably, a rupture on the ovarian mass and low-grade pseudomyxoma peritonei were present. Next-generation sequencing identified an identical KRAS mutation in the mucinous tumor and anaplastic carcinoma, while the latter had KRAS gene amplification and CDKN2A, MPL and TP53 mutations. These findings indicate the anaplastic carcinoma might have arisen via recurrence, malignant transformation and dedifferentiation of the former low-grade mucinous tumor. We consider that the mass rupture and pseudomyxoma peritonei were high-risk factors for recurrence, while genetic mutations were key drivers of progression. Accordingly, such cases may benefit from active surgical treatment and early chemotherapy.

Invasive Mucinous Adenocarcinoma of the Lung with a Mural Nodule-like Lesion

Invasive mucinous adenocarcinoma (IMA) of the lung shares some clinicopathological features with mucinous carcinoma of other organs, such as the ovary. Sarcoma-like lesions, called mural nodules, have been reported in the cystic walls of ovarian mucinous tumors. In this study, we analyzed 213 surgically resected cases of IMA of the lung to determine whether similar mural nodule-like lesions were present. We considered abrupt discrete lesions composed of dedifferentiated tumor cells as mural nodule-like lesions. Of 213 IMAs, we identified 11 tumors with mural nodule-like lesions that were histologically categorized into three subtypes similar to those in the ovary. The sarcomatoid and anaplastic carcinoma-like nodules were composed of spindle cell proliferations and polygonal undifferentiated carcinoma, respectively. Sarcoma-like lesions mimicked sarcomatoid nodules, but the spindle cell proliferations were considered a fibroblastic reaction to the scattered, isolated clusters of tumor cells. Molecular analysis of the components of differentiated IMAs and mural nodule-like lesions revealed a clonal relationship, suggesting a spectrum of tumors with different histology. Clinicopathologically, an older age, the male sex, and smokers were significantly associated with IMAs with mural nodule-like lesions. Notably, patient outcomes were unaffected by the presence or absence of these lesions. Our findings demonstrated that IMA of the lung rarely develops mural nodule-like lesions (11 of 213, 5%). Despite a histological impression of clinical aggressiveness, there was no clear trend in patient outcomes, suggesting that pathologists should avoid overstating this mural nodule-like lesion.

Ovarian mucinous tumor with mural nodules of anaplastic carcinoma: Three case reports

BACKGROUND

Anaplastic carcinoma mural nodules in ovarian mucinous tumors are very rare. This study aimed to report the morphological characteristics, molecular detection results, clinical treatment and prognosis of three ovarian mucinous tumors with mural nodules of anaplastic carcinoma.

CASE SUMMARY

The pathomorphological features, molecular detection results, clinical treatment and prognosis of anaplastic carcinoma mural nodules were described in three cases. In case 1, sarcoma-like mural nodules (SLMNs) coexisted with anaplastic carcinoma mural nodules. No mutation was found in mucinous tumors. KRAS mutation was found in anaplastic carcinoma nodules and heterotypic cells were found in SLMNs. In case 2, KRAS mutation occurred in the mucinous epithelium and BRAF mutation occurred in mural nodules. In case 3, both mural nodules and mucinous tumors had the same KRAS mutation and a morphological transition between them was observed. All three patients died within 2 years, whether receiving chemotherapy or not.

CONCLUSION

Anaplastic carcinoma mural nodules may develop from dedifferentiation of mucinous tumors or are unrelated to mucinous tumors.

The Protein Landscape of Mucinous Ovarian Cancer: Towards a Theranostic

MOC is a rare histotype of epithelial ovarian cancer, and current management options are inadequate for the treatment of late stage or recurrent disease. A shift towards personalised medicines in ovarian cancer is being observed, with trials targeting specific molecular pathways, however, MOC lags due to its rarity. Theranostics is a rapidly evolving category of personalised medicine, encompassing both a diagnostic and therapeutic approach by recognising targets that are expressed highly in tumour tissue in order to deliver a therapeutic payload. The present review evaluates the protein landscape of MOC in recent immunohistochemical- and proteomic-based research, aiming to identify potential candidates for theranostic application. Fourteen proteins were selected based on cell membrane localisation: HER2, EGFR, FOLR1, RAC1, GPR158, CEACAM6, MUC16, PD-L1, NHE1, CEACAM5, MUC1, ACE2, GP2, and PTPRH. Optimal proteins to target using theranostic agents must exhibit high membrane expression on cancerous tissue with low expression on healthy tissue to afford improved disease outcomes with minimal off-target effects and toxicities. We provide guidelines to consider in the selection of a theranostic target for MOC and suggest future directions in evaluating the results of this review.

Ovarian mucinous and seromucinous neoplasms: problematic aspects and modern diagnostic approach

The morphological spectrum of primary ovarian mucinous and seromucinous tumours is broad and presents an array of diagnostic challenges, many unique to these tumour types. This reflects the heterogeneous nature of these lesions, their varied histogenesis and evolving classification systems over recent decades, with further modification to the seromucinous category incorporated in the recently published 5^th edition of the WHO Classification of Female Genital Tumours. In this review we provide an update on the classification of these neoplasms and discuss their histogenesis and diverse morphology, focusing on areas which are diagnostically problematic. We also cover tumour grading, differential diagnosis, immunohistochemistry, the recent elucidation of the molecular underpinnings of ovarian mucinous neoplasia and discuss the gross and intraoperative handling of these tumours. A number of diagnostic issues remain unresolved highlighting the importance of further research on this front, as well as a multidisciplinary approach in the care of patients with ovarian mucinous and seromucinous neoplasia.