Clinical Profile and Survival Outcome of Endometrial Cancer with p53 Mutation

Alukal, Anila Tresa; Suchetha, S.; Rema, P.; Dinesh, Dhanya; Sivaranjith, J.; Nair, Sindhu P.; Mathew, Aleyamma; Viswanathan, Ammu Jayanthi; Kumar, Aswin

doi:10.1007/s13193-022-01523-9

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…2A ). Among these were PTEN mutations (AUROC 0.73 ± 0.03) involved in hereditary cancer; 21 TP53 mutations (AUROC 0.72 ± 0.05), which is associated with poor prognosis 22 and APC (AUROC 0.72 ± 0.11), as a potential predictive marker for immunotherapy in endometrial cancer 23 . We identified 7 genes for which mutations were predictable (out of 16 analyzable genes) for colorectal cancer (CRC) with AUROCs of over 0.6 in the external validation cohort.…”

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confidence: 99%

Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology

et al. 2023

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The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep learning can predict genetic alterations from pathology slides, but it is unclear how well these predictions generalize to external datasets. We performed a systematic study on Deep-Learning-based prediction of genetic alterations from histology, using two large datasets of multiple tumor types. We show that an analysis pipeline that integrates self-supervised feature extraction and attention-based multiple instance learning achieves a robust predictability and generalizability.

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confidence: 99%

Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology

et al. 2023

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“…16,17 The association between p53 mutation and poor prognosis in endometrial carcinoma has been reported in several studies. 18,19 In this study, we found that 62.5% of cases with p53 mutation showed poor performance. This highlights the importance of p53 immunohistochemical staining in the prognostication and management of endometrial carcinoma.…”

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confidence: 53%

Correlation between immunohistochemical staining and clinicopathological findings in endometrial carcinoma

Saharti,

Altaf

2024

SMJ

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Objectives:To analyze the immunohistochemical staining pattern of mismatch repair (MMR) proteins and p53 in endometrial carcinoma cases, including different subtypes and stages, to gain insights into their role in the pathogenesis and clinical behaviour of this malignancy. Methods:In this study, we investigate the association between MMR deficiency, p53 mutational status, and clinical outcomes in various subtypes of endometrial carcinoma. The immunohistochemical staining pattern of MMR proteins in 96 cases of endometrial carcinoma have been analyzed, including 72 endometrioid, 14 papillary serous, 5 clear cell, and 5 mixed Müllerian tumor. Results:The results showed that 36 cases were MMR deficient, with the majority being of endometrioid subtype. The p53 immunostain showed a mutational pattern in a subset of cases, with a documented dismal prognosis. However, aforementioned stains failed to predict synchronous or metachronous cancers in 5 patients. Conclusion: These findings highlight the importance of MMR and p53 immunohistochemical stainingOriginal Article in the classification, and prognosis of endometrial carcinoma.

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“…Furthermore, mutations in the TP53 gene determine the loss of its suppressive functions, allowing cells to avoid apoptosis and to accumulate genetic modifications. Thus, the presence of TP53 mutations in ECs is associated with high aggressiveness and a poor prognosis [ 27 ].…”

Section: Molecular Mechanisms Involved In the Pathogenesis Of Endomet...mentioning

confidence: 99%

Landscape of Endometrial Cancer: Molecular Mechanisms, Biomarkers, and Target Therapy

Bostan,

Mihaila,

Roman

et al. 2024

Cancers

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Endometrial cancer is one the most prevalent gynecological cancers and, unfortunately, has a poor prognosis due to low response rates to traditional treatments. However, the progress in molecular biology and understanding the genetic mechanisms involved in tumor processes offers valuable information that has led to the current classification that describes four molecular subtypes of endometrial cancer. This review focuses on the molecular mechanisms involved in the pathogenesis of endometrial cancers, such as genetic mutations, defects in the DNA mismatch repair pathway, epigenetic changes, or dysregulation in angiogenic or hormonal signaling pathways. The preclinical genomic and molecular investigations presented allowed for the identification of some molecules that could be used as biomarkers to diagnose, predict, and monitor the progression of endometrial cancer. Besides the therapies known in clinical practice, targeted therapy is described as a new cancer treatment that involves identifying specific molecular targets in tumor cells. By selectively inhibiting these targets, key signaling pathways involved in cancer progression can be disrupted while normal cells are protected. The connection between molecular biomarkers and targeted therapy is vital in the fight against cancer. Ongoing research and clinical trials are exploring the use of standard therapy agents in combination with other treatment strategies like immunotherapy and anti-angiogenesis therapy to improve outcomes and personalize treatment for patients with endometrial cancer. This approach has the potential to transform the management of cancer patients. In conclusion, enhancing molecular tools is essential for stratifying the risk and guiding surgery, adjuvant therapy, and cancer treatment for women with endometrial cancer. In addition, the information from this review may have an essential value in the personalized therapy approach for endometrial cancer to improve the patient’s life.

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Clinical Profile and Survival Outcome of Endometrial Cancer with p53 Mutation

Cited by 9 publications

References 20 publications

Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology

Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology

Correlation between immunohistochemical staining and clinicopathological findings in endometrial carcinoma

Landscape of Endometrial Cancer: Molecular Mechanisms, Biomarkers, and Target Therapy

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