scholarly journals Acquired Evolution of Mitochondrial Metabolism Regulated by HNF1B in Ovarian Clear Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2413
Author(s):  
Ken Yamaguchi ◽  
Sachiko Kitamura ◽  
Yoko Furutake ◽  
Ryusuke Murakami ◽  
Koji Yamanoi ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Endometrioid Carcinoma ◽  
Eosinophilic Cytoplasm ◽  
Clinical Questions ◽  
Nuclear Factor 1 ◽  
Carcinogenic Process ◽  
And Control ◽  
Stressful Environments

Clear cell carcinoma (CCC) of the ovary exhibits a unique morphology and clinically malignant behavior. The eosinophilic cytoplasm includes abundant glycogen. Although the growth is slow, the prognosis is poor owing to resistance to conventional chemotherapies. CCC often arises in endometriotic cysts and is accompanied by endometriosis. Based on these characteristics, three clinical questions are considered: why does ovarian cancer, especially CCC and endometrioid carcinoma, frequently occur in endometriotic cysts, why do distinct histological subtypes (CCC and endometrioid carcinoma) arise in the endometriotic cyst, and why does ovarian CCC possess unique characteristics? Mutations in AT-rich interacting domain-containing protein 1A and phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit alpha genes may contribute to the carcinogenesis of ovarian CCC, whereas hepatocyte nuclear factor-1-beta (HNF1B) plays crucial roles in sculpting the unique characteristics of ovarian CCC through metabolic alterations. HNF1B increases glutathione synthesis, activates anaerobic glycolysis called the Warburg effect, and suppresses mitochondria. These metabolic changes may be induced in stressful environments. Life has evolved to utilize and control energy; eukaryotes require mitochondria to transform oxygen reduction into useful energy. Because mitochondrial function is suppressed in ovarian CCC, these cancer cells probably acquired further metabolic evolution during the carcinogenic process in order to survive stressful environments.

scholarly journals A rare case of synchronous right ovarian clear cell carcinoma and an incidental left ovarian endometrioid carcinoma with immunohistochemical study

2014 ◽  
Vol 5 (2) ◽  
pp. 91
Author(s):  
SiddhiG. S. Khandeparkar ◽  
SanjayD Deshmukh ◽  
HemantS Lekawale ◽  
Amit Bhoge ◽  
AnsariTabassum Parveen Maqbool Ahmed
Keyword(s):  
Cell Carcinoma ◽  
Rare Case ◽  
Clear Cell ◽  
Immunohistochemical Study ◽  
Clear Cell Carcinoma ◽  
Endometrioid Carcinoma ◽  
Ovarian Clear Cell Carcinoma

Hyalinising clear cell carcinoma of salivary gland: a case report

2020 ◽  
Vol 18 (2) ◽  
pp. 127-130
Author(s):  
Michał Osuchowski ◽  
◽  
Dorota Bartusik-Aebisher ◽  
Ewa Kaznowska ◽  
David Aebisher ◽  
...  
Keyword(s):  
Salivary Gland ◽  
Lymph Node ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Distant Metastases ◽  
Minor Salivary Glands ◽  
Not Otherwise Specified ◽  
Eosinophilic Cytoplasm ◽  
History Of

Introduction. Clear cell carcinoma, not otherwise specified/hyalinising clear cell carcinoma of the salivary gland (HCCC) is a malignancy that arises in minor salivary glands. It rarely leads to distant metastases or cancer-related death but has the potential for recurrence and focal metastases. Aim. A case is reported. Description of the case. A 72 years old female patient has reported to the Clinic of Otolaryngology with a tongue lesion. The patient had no history of malignancy. The lymph node has been surgically removed for further examination. Cords and nests of clear cells and cells with eosinophilic cytoplasm in a hyalinized stroma were identified within the lymph node. After the diagnosis the patient has been transferred to another Oncology Hospital for further treatment. Conclusion. The diagnosis of clear cell carcinoma may be challenging because many of it‘s features frequently overlap with other salivary gland lesions.

scholarly journals Whole-tumor ADC histogram analysis for differentiating endometriosis-related tumors: seromucinous borderline tumor, clear cell carcinoma and endometrioid carcinoma

2021 ◽  
Author(s):  
Jing Lu ◽  
Yong'ai Li ◽  
Songqi Cai ◽  
Shuhui Zhao ◽  
Fenghua Ma ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Characteristic Curve ◽  
Histogram Analysis ◽  
Borderline Tumor ◽  
Endometrioid Carcinoma ◽  
Mri Findings ◽  
Diagnostic Efficacy ◽  
Apparent Diffusion

Abstract Background: In view of the similar MRI findings of endometriosis-related ovarian neoplasms, this study aimed to investigate the feasibility of whole-tumor apparent diffusion coefficient (ADC) histogram analysis for differentiating endometriosis-related tumors: seromucinous borderline tumor (SMBT), clear cell carcinoma (CCC) and endometrioid carcinoma (EC).Methods: A total of 85 patients (22 with SMBT, 42 with CCC and 21 with EC) were retrospectively enrolled. Clinical data including age, stage, laterality, solid component ADC (ADCSC) and whole-tumor ADC histogram-derived parameters, such as the volume, ADCmean, the 10th, 50th and 90th percentile ADCs, inhomogeneity, skewness, kurtosis and entropy, were compared among SMBT, CCC and EC. The diagnostic efficacy of these parameters was evaluated using receiver operating characteristic curve analysis.Results: There were significant differences in age, ADCSC and histogram parameters including volume, ADCmean, the 10th, 50th and 90th percentile ADCs among three kinds of tumors (all p < 0.05). Patients with SMBT were significantly younger than patients with CCC/EC. The significantly higher ADCSC and smaller volume were found in SMBT than in CCC/ EC. The ADCmean was significantly higher in CCC than in EC. The 10th percentile ADC was significantly lower in EC than in SMBT/CCC. The 50th and 90th percentile ADCs were significantly higher in CCC than in SMBT/EC. For differentiating SMBT from CCC, AUCs of the ADCSC, volume, the 50th and 90th percentile ADCs were 0.97, 0.86, 0.72 and 0.81, respectively. For differentiating SMBT from EC, AUCs of the ADCSC, volume and the 10th percentile ADC were 0.97, 0.71 and 0.72, respectively. For differentiating CCC from EC, AUCs of the ADCmean, the 10th, 50th and 90th percentile ADCs were 0.79, 0.72, 0.81 and 0.85, respectively. Conclusions: Similar with ADCSC, whole-tumor ADC histogram analysis was valuable for differentiating endometriosis-related tumors. It was helpful for the 50th, 90th percentile ADCs and volume in differentiating SMBT from CCC; for the volume and 10th percentile ADC in differentiating SMBT from EC, and for the ADCmean, the 10th, 50th and 90th percentile ADCs in differentiating CCC from EC.

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