Hyperinsulinemia and Hypoadiponectinemia are Associated with Increased Risk for Occurrence of Ovarian Cancer in Non-diabetic Women of North Indian Population

Gupta, Rohit; Dholariya, Sagar; Kaushik, Smita; Gupta, Santosh Kumar; Tripathi, Reva; Jain, Shyama

doi:10.1007/s12291-020-00891-9

Cited by 7 publications

(16 citation statements)

References 30 publications

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“…Nevertheless, living in an urban area with a high education does not guarantee that patients will be diagnosed early since cases in the present study were predominantly in advanced-stage diseases (80%). Indeed, ~75% of cases of ovarian cancer are diagnosed at a late stage due to the non-specific nature of symptoms and the absence of practical screening tests (49). The present study revealed that most of the patients were old (>40 years), similar to a study conducted in India (49), with young women mostly having benign ovarian neoplasm (Table I).…”

Section: Discussionsupporting

confidence: 83%

“…Indeed, ~75% of cases of ovarian cancer are diagnosed at a late stage due to the non-specific nature of symptoms and the absence of practical screening tests (49). The present study revealed that most of the patients were old (>40 years), similar to a study conducted in India (49), with young women mostly having benign ovarian neoplasm (Table I). Meanwhile, older women were more commonly involved in malignant cases.…”

Section: Discussionsupporting

confidence: 83%

“…Limited evidence is available on the association of IR with ovarian neoplasm ( 16 , 24 , 49 ), particularly among Southeast Asians. Thus the present study investigated whether there is a difference in IR between benign and malignant ovarian neoplasm since IR plays a vital role in FIL homeostasis related to cancer.…”

Section: Discussionmentioning

confidence: 99%

“…This RLU value is proportional to the insulin concentration in the sample. This process was referred to in a study by Gupta et al ( 49 ).…”

Section: Methodsmentioning

confidence: 96%

“…The third limitation is that the sample size was relatively small; thus, type II errors may have occurred in the study. Nevertheless, earlier research on this issue also used a small sample size with similar settings (24,25,49,59) and the sample size of the present study was more extensive than those. Fourth, the present study did not recruit a healthy control group, making it impossible to assess and compare the development of the neoplasm case group to a normal state.…”

Section: Correlation Between Clinical Features and Surrogate Markersmentioning

confidence: 95%

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Is there any difference in insulin resistance status between cases of benign and malignant ovarian neoplasms? A study on surrogate markers of insulin resistance in Indonesian non‑diabetic women

et al. 2022

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The association between insulin resistance (IR) and ovarian neoplasm is little known. The present study attempted to investigate the difference in clinicopathological characteristics, metabolic parameters, and IR prevalence between benign and malignant ovarian neoplasms. The cross-sectional study involved 52 non-diabetic women with benign (n=27) and malignant (n=25) diagnoses in a tertiary hospital in Indonesia. Fasting insulin level (FIL), homeostatic model assessment of IR and β-cell dysfunction (HOMA-IR and HOMA-β), fasting IR index (FIRI), and quantitative insulin sensitivity check index (QUICKI) were used as surrogate markers to evaluate IR. Parametric and nonparametric statistical tests were employed to analyze the different parameters between the two groups. Pearson or Spearman's rank test assessed the correlation between markers and clinical variables. Results revealed that patients with benign neoplasms were younger than those with malignant neoplasms (38.63 vs. 47.40 years; P=0.003) and had a higher median body mass index (BMI) than their counterparts (22.98 vs. 18.61 kg/m 2 ; P=0.014). Different characteristics between benign and malignant neoplasm cases were found in menopausal status, ovary side affected, systolic blood pressure, and BMI classes. Endometrial cysts and mucinous carcinoma were the most often diagnosed benign and malignant neoplasms. Malignant neoplasms had a lower median HOMA-β score than benign neoplasms (49.33 vs. 75.79; P=0.011), indicating more severe β-cell dysfunction. No significant difference was observed in the prevalence of IR between benign and malignant ovarian neoplasms for the following values of each marker: FIL (25.9% vs. 12.0%), HOMA-IR (37.0% vs. 28.0%), FIRI (51.9% vs. 48.0%) and QUICKI (81.5% vs. 92.0%). The indicators of FIL, HOMA-IR, HOMA-β, FIRI, and QUICKI correlated with each other and confirmed the reliability of these surrogate markers for measuring IR status in ovarian neoplasms. In brief, benign ovarian neoplasms tended to have more IR when compared with malignant ovarian neoplasms. However, this difference was not statistically significant.

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Section: Discussionsupporting

confidence: 83%

Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 99%

“…This RLU value is proportional to the insulin concentration in the sample. This process was referred to in a study by Gupta et al ( 49 ).…”

Section: Methodsmentioning

confidence: 96%

Section: Correlation Between Clinical Features and Surrogate Markersmentioning

confidence: 95%

See 3 more Smart Citations

Is there any difference in insulin resistance status between cases of benign and malignant ovarian neoplasms? A study on surrogate markers of insulin resistance in Indonesian non‑diabetic women

et al. 2022

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Exploring the logic and conducting a comprehensive evaluation of AdipoRon-based adiponectin replacement therapy against hormone-related cancers—a systematic review

Laurindo,

Sosin,

Lamas

et al. 2023

Naunyn-Schmiedeberg's Arch Pharmacol

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Neddylation of insulin receptor substrate acts as a bona fide regulator of insulin signaling and its implications for cancer cell migration

Park,

Moon,

Cho

et al. 2024

Cancer Gene Ther

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Irregularities in insulin signaling have significantly increased the risk of various cancers, yet the precise underlying mechanisms remain unclear. Within our study, we observed that inhibiting neddylation enhances cancer cell migration across different cancer types by activating both insulin receptor substrates 1 and 2 (IRS1 and IRS2), along with the PI3K/AKT signaling pathway. Notably, in the context of high-grade serous carcinoma (HGSC) patients, whether they had type 2 diabetes mellitus or not, IRS1 and IRS2 displayed a parallel relationship with each other while exhibiting an inverse relationship with NEDD8. We also identified C-CBL as an E3 ligase responsible for neddylating IRS1 and IRS2, with clinical evidence further confirming a reciprocal relationship between C-CBL and pAKT, thereby reinforcing the tumor suppressive role of C-CBL. Altogether, these findings suggest that neddylation genuinely participates in IRS1 and IRS2-dependent insulin signaling, effectively suppressing cancer cell migration. Thus, caution is advised when considering neddylation inhibitors as a treatment option for cancer patients, particularly those presenting with insulin signaling dysregulations linked to conditions like obesity-related type 2 diabetes or hyperinsulinemia.

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Hyperinsulinemia and Hypoadiponectinemia are Associated with Increased Risk for Occurrence of Ovarian Cancer in Non-diabetic Women of North Indian Population

Cited by 7 publications

References 30 publications

Is there any difference in insulin resistance status between cases of benign and malignant ovarian neoplasms? A study on surrogate markers of insulin resistance in Indonesian non‑diabetic women

Is there any difference in insulin resistance status between cases of benign and malignant ovarian neoplasms? A study on surrogate markers of insulin resistance in Indonesian non‑diabetic women

Exploring the logic and conducting a comprehensive evaluation of AdipoRon-based adiponectin replacement therapy against hormone-related cancers—a systematic review

Neddylation of insulin receptor substrate acts as a bona fide regulator of insulin signaling and its implications for cancer cell migration

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