Distant Lymph Node Metastases From Breast Cancer-Is it Time to Review TNM Cancer Staging?

Prognostic value of preoperative modified Glasgow prognostic score in predicting overall survival in breast cancer patients: A retrospective cohort study

The modified Glasgow prognostic score (mGPS), based on C-reactive protein and albumin levels, is an inflammation-based prognostic tool used in various cancers. However, related research in breast cancer is limited. The present study evaluated the prognostic value of the preoperative mGPS in predicting overall survival (OS) of patients with breast cancer undergoing surgery. A retrospective cohort study was conducted involving 300 patients with breast cancer with up to 10 years of follow-up. Patients were categorized into three groups based on mGPS scores of 0, 1 and 2, and their clinical and pathological data were collected. Kaplan-Meier survival analysis and Cox proportional hazards models were used to assess survival outcomes and identify risk factors associated with higher mGPS scores. A prognostic nomogram was developed based on multivariate analysis to predict 5- and 10-year OS. Patients with high mGPS scores showed significantly poor survival outcomes. The 5- and 10-year survival rates for mGPS 0, 1 and 2 were 80, 70 and 55%, and 71, 55 and 22%, respectively (P<0.001). Multivariate Cox analysis identified the mGPS, age, smoking, PAM50 and TNM stage as independent predictors of OS. The nomogram based on the mGPS demonstrated good predictive accuracy (concordance index: 0.81) and calibration. The preoperative mGPS is an independent prognostic factor for OS of patients with breast cancer. It is a simple, cost-effective tool that can aid in risk stratification and guide treatment strategies. Further validation in larger cohorts is recommended.

Fast cancer metastasis location based on dual magnification hard example mining network in whole-slide images

Breast cancer has become the most common form of cancer among women. In recent years, deep learning has shown great potential in aiding the diagnosis of pathological images, particularly through the use of convolutional neural networks for locating lymph node metastasis under gigapixel whole slide images (WSIs). However, the massive size of these images at the highest magnification introduces redundant computation during the inference process. Additionally, the diversity of biological textures and structures within WSIs can cause confusion for classifiers, particularly in identifying hard examples. As a result, the trade-off between accuracy and efficiency remains a critical issue for whole-slide image metastasis localization. In this paper, we propose a novel two-stream network that takes a pair of low- and high-magnification image patches as input for identifying hard examples during the training phase. Specifically, our framework focuses on samples where the outputs of the two magnification networks are dissimilar. We adopt a dual magnification hard mining loss to re-weight the ambiguous samples. To more efficiently locate tumor metastasis cells in whole slide images, the two stream networks are decomposed into a cascaded network during the inference phase. The low magnification WSIs scanned by the low-mag network generate a coarse probability map, and the suspicious areas in the map are refined by the high-mag network. Finally, we evaluate our fast location dual magnification hard example mining network on the Camelyon16 breast cancer whole-slide image dataset. Experiments demonstrate that our proposed method achieves a 0.871 FROC score with a faster inference time, and our high magnification network also achieves a 0.88 FROC score.

Current status and influencing factors of care burden of pancreatic cancer caregivers under COVID-19

Objective

To explore the level of care burden and its influencing factors of caregivers of pancreatic cancer patients during hospitalization under the background of COVID-19.

Methods

From September 2021 to December 2021, in Jiangsu Province Hospital, the convenience sampling method was used to investigate the care burden level of family caregivers of pancreatic cancer patients, and univariate and multivariate analysis methods were used to analyze the influencing factors. The survey tools included the General Information Questionnaire, the Family Caregiver Care Burden Scale, the Hospital Anxiety and Depression Scale, the Benefit Discovery Rating Scale, and the General Self-Efficacy Scale.

Results

A total of 100 subjects were included in this study, of which 45% were male and 55% were older than 50 years. In the Context of COVID-19, the care burden of caregivers of pancreatic cancer patients was at a mild level, and the main influencing factors were family economic status (p < 0.001), anxiety and depression level (p < 0.001) and self-efficacy (p < 0.001).

Conclusion

Medical staff should pay attention to the caregivers of pancreatic cancer with a heavy family burden, and pay attention to their anxiety and depression, and take corresponding measures to improve the self-efficacy of the caregivers, so as to reduce the care burden.

Circular RNA KIF4A Promotes Liver Metastasis of Breast Cancer by Reprogramming Glucose Metabolism

Background

Circular RNAs (circRNAs) regulate complex functional processes and play crucial roles in cancer development and progression. It was reported that circKIF4 regulates the progression of triple-negative breast cancer (TNBC). This study evaluates the role of circKIF4 in breast cancer distant metastasis and metabolic reprogramming.

Methods

RT-qPCR was performed to verify the expression of circKIF4A in breast cancer, liver metastatic tissues, and cell lines. The function of circKIF4A in metastasis was evaluated both in vitro and in vivo through a series of experiments, including cell migration and glucose intake experiments. Additionally, we conducted molecular experiments to clarify the regulatory role of circKIF4A. We then conducted a Luciferase reporter assay and an RNA immunoprecipitation assay to identify the molecular interactions between circKIF4A and miRNA.

Results

circKIF4A was overexpressed in breast cancer cell lines and tissues, inhibiting its expression and suppressing breast cancer growth and metastasis. Interestingly, we observed that circKIF4A reprogrammed the glucose metabolism of breast cancer, and silencing circKIF4A greatly affected glucose uptake and lactate production in breast cancer cells. miR-335 can be sponged by circKIF4A, which affected the expression of ALDOA/OCT4 protein and regulated HK2/PKM2 expression.

Conclusions

This study demonstrated that the circKIF4A-miR-335-OCT4/ALDOA-HK2/PKM2 axis is critical to breast cancer metabolic reprogramming, indicating that this axis could be a novel therapeutic target for the treatment of liver metastasis of breast cancer.