Peptides for diagnosis and treatment of ovarian cancer

Guo, Lei; Wang, Jing; Li, Nana; Cui, Jialin; Su, Yajuan

doi:10.3389/fonc.2023.1135523

Cited by 8 publications

(2 citation statements)

References 128 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, these techniques lack enough specificity and often present artefacts that hamper the correct analysis of the results. This leads, in the end, to the abovementioned low patient survival rates [ 11 ].…”

Section: Ovarian Cancer: a Rare But Fatal Malignancymentioning

confidence: 99%

Biomarkers in Ovarian Cancer: Towards Personalized Medicine

López-Portugués,

Montes-Bayón,

Díez

2024

Proteomes

View full text Add to dashboard Cite

Ovarian cancer is one of the deadliest cancers in women. The lack of specific symptoms, especially at the initial stages of disease development, together with the malignancy heterogeneity, lower the life expectancy of patients. Aiming to improve survival rates, diagnostic and prognostic biomarkers are increasingly employed in clinics, providing gynecologists and oncologists with new tools to guide their treatment decisions. Despite the vast number of investigations, there is still an urgent need to discover more ovarian cancer subtype-specific markers which could further improve patient classification. To this end, high-throughput screening technologies, like mass spectrometry, are applied to deepen the tumoral cellular landscape and describe the malignant phenotypes. As for disease treatment, new targeted therapies, such as those based on PARP inhibitors, have shown great efficacy in destroying the tumoral cells. Likewise, drug-nanocarrier systems targeting the tumoral cells have exhibited promising results. In this narrative review, we summarize the latest achievements in the pursuit of biomarkers for ovarian cancer and recent anti-tumoral therapies.

show abstract

Section: Ovarian Cancer: a Rare But Fatal Malignancymentioning

confidence: 99%

Biomarkers in Ovarian Cancer: Towards Personalized Medicine

López-Portugués,

Montes-Bayón,

Díez

2024

Proteomes

View full text Add to dashboard Cite

show abstract

“…Ovarian cancer is the leading cause of death among the gynecologic cancers (1) and the fifth most common cause of death after lung, breast, colorectal, and pancreatic cancers (2). In addition, ovarian cancer is the most difficult gynecologic malignancy to treat in the clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Survival prognosis model for elderly women with epithelial ovarian cancer based on the SEER database

Zhou,

Wang,

Sun

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

ObjectivesWe aimed to analyze the risk factors of elderly women with epithelial ovarian cancer (EOC) using data on the SEER database, and to generate a nomogram model their 1-, 3-, and 5-year prognoses. The resulting nomogram model should be useful for clinical diagnoses and treatment.MethodsWe collected clinical data of women older than 70 years with epithelial ovarian cancer (diagnosed on the basis of surgical pathology) from the SEER database including datasets between 2010 and 2019. We randomly grouped the data into two groups (7:3 ratio) using the R language software. We divided the independent prognostic factors obtained by univariate and multi-factor Cox regression analyses into training and validation sets, and we plotted the same independent prognostic factors in a nomogram model of overall survival (OS) at 1, 3, and 5 years. We used the C-index, calibration curve, and area under the curve to validate the nomograms. We further evaluated the model and its clinical applicability using decision curve analyses.ResultsWe identified age, race, marital status, histological type, AJCC staging, differentiation degree, unilateral and bilateral tumor involvement, number of positive lymph nodes, chemotherapy, surgery, sequence of systemic treatment versus surgery, and time from diagnosis to treatment as independent prognostic factors for elderly women with EOC (P < 0.5). The C-indexes were 0.749 and 0.735 in the training and validation sets, respectively; the ROC curves showed that the AUC of each prognostic factor was greater than 0.7; and, the AUC values predicted by the line plot were similar in the training and validation sets. The decision curves suggest that this line plot model has a high clinical value for predicting overall survivals at 1, 3, and 5 years in elderly women with EOC.ConclusionThe nomogram model in this study can provide an accurate assessment of the overall survival of women older than 70 years with EOC at the time of the first treatment, and it provides a basis for individualized clinical treatment.

show abstract

Immunomodulatory Peptides for Tumor Treatment

Song,

Lei,

Cai

et al. 2024

Adv Healthcare Materials

View full text Add to dashboard Cite

Peptides exhibit various biological activities, including biorecognition, cell targeting, and tumor penetration, and can stimulate immune cells to elicit immune responses for tumor immunotherapy. Peptide self‐assemblies and peptide‐functionalized nanocarriers can reduce the effect of various biological barriers and the degradation by peptidases, enhancing the efficiency of peptide delivery and improving anti‐tumor immune responses. To date, the design and development of peptides with various functionalities have been extensively reviewed for enhanced chemotherapy; however, peptide‐mediated tumor immunotherapy using peptides acting on different immune cells, to the knowledge, has not yet been summarized. Thus, we provide a review of this emerging subject of research, focusing on immunomodulatory anticancer peptides. This review introduces the role of peptides in the immunomodulation of innate and adaptive immune cells, followed by a link between peptides in the innate and adaptive immune systems. The peptides are discussed in detail, following a classification according to their effects on different innate and adaptive immune cells, as well as immune checkpoints. Subsequently, two delivery strategies for peptides as drugs are presented: peptide self‐assemblies and peptide‐functionalized nanocarriers. The concluding remarks regarding the challenges and potential solutions of peptides for tumor immunotherapy are presented.This article is protected by copyright. All rights reserved

show abstract

Peptides for diagnosis and treatment of ovarian cancer

Cited by 8 publications

References 128 publications

Biomarkers in Ovarian Cancer: Towards Personalized Medicine

Biomarkers in Ovarian Cancer: Towards Personalized Medicine

Survival prognosis model for elderly women with epithelial ovarian cancer based on the SEER database

Immunomodulatory Peptides for Tumor Treatment

Contact Info

Product

Resources

About