Chemotherapy‐induced gastrointestinal symptom clusters in breast cancer impair quality of life and treatment adherence, yet lack effective interventions. While acupuncture mitigates isolated chemotherapy‐induced symptoms, its mechanisms for multi‐symptom clusters remain unclear. This study evaluates electroacupuncture's efficacy and explores its biological mechanisms in managing these clusters.

This prospective, multicenter, block‐randomized, double‐blind, sham‐controlled trial will enroll 388 patients with breast cancer undergoing neoadjuvant/adjuvant chemotherapy, to be randomly assigned (1:1) to electroacupuncture or sham electroacupuncture groups. Both groups will receive the standard quadruple antiemetic regimen combined with electroacupuncture or sham intervention. The primary endpoint is the incidence of chemotherapy‐induced gastrointestinal symptom clusters within 120 h after chemotherapy. Secondary endpoints include improvement in gastrointestinal symptom clusters post‐first chemotherapy cycle, nausea‐free rates during acute and delayed phases, vomiting‐free rates during overall, acute, and delayed phases, complete response rate, complete protection rate, and quality of life. Adverse events will be documented throughout the study.

This study will assess the efficacy and safety of electroacupuncture in alleviating chemotherapy‐induced gastrointestinal symptom clusters in patients with breast cancer. By integrating multi‐omics analyses, we aim to elucidate the biological mechanisms underlying its therapeutic effects. The findings may offer a robust clinical foundation for optimizing symptom cluster management in cancer care.

Clinical Trials ID: NCT06952920. Date of registration: April 16, 2025. Prospectively registered. URL of Trial Registry Record: https://clinicaltrials.gov/study/NCT06952920cond=NCT06952920&rank=1.

While tumor cells can affect the biological behavior of malignant tumors, the tumor microenvironment (TME) also plays an important role in the occurrence, development, and metastasis of tumors. The dynamic changes in the immune and stromal components of the TME and their correlations with breast cancer (BCa) patient prognosis may help guide clinical practice.

In this study, transcriptomic data and clinical information of BCa samples were obtained from The Cancer Genome Atlas database. The immune score and matrix score were calculated using the ESTIMATE algorithm. Examining the differentially expressed genes (DEGs), protein–protein interaction network development, and univariate Cox analysis helped identify CD48 as a key BCa‐related gene.

The DEG and survival analysis results showed that CD48 was significantly upregulated in BCa samples compared with normal samples, potentially affecting patient prognosis. Gene set enrichment analysis showed that high CD48 expression was mainly associated with immune‐related pathways, suggesting that CD48 may be an important factor for maintaining an immune‐dominant TME in BCa. Analysis of tumor‐infiltrating immune cell types showed that high expression of CD48 could inhibit the infiltration of M2 macrophages and promote the entry of CD8+ T cells, CD4+ T cells, and M1 macrophages into the TME to exert anti‐tumor effects.

CD48 may serve as an effective biomarker for predicting BCa patient prognosis and a potential immune‐related therapeutic target.

Although there have been significant advancements in the treatment modalities for gastric cancer (GC) in recent years, the overall prognosis remains poor, particularly for individuals in advanced stages. The absence of a sensitive tumor marker in GC is a crucial factor contributing to this challenge.

Our study focused on investigating a newly discovered long noncoding RNA (lncRNA) known as TCONS_00251376, which has been confirmed to exhibit differential expression in GC compared to adjacent tissues. To further validate these expression differences, we collected 22 pairs of GC and adjacent noncancerous tissues. Subsequent cell function experiments and animal studies were conducted to elucidate the role and underlying mechanisms of lncRNA TCONS_00251376 in the development of GC.

The study revealed a significant upregulation of lncRNA TCONS_00251376 in cancer tissues (p < 0.01) and a consistent upregulation in GC cell lines (AGS, MKN45, BGC‐823, and MGC‐803). Furthermore, it was observed that lncRNA TCONS_00251376 played a promotive role in the proliferation, migration, and invasion of GC cells. Subsequent analysis indicated that lncRNA TCONS_00251376 could upregulate the expression of ETV1, a factor associated with the prognosis of GC.

Therefore, our findings suggest that lncRNA TCONS_00251376 functions as an oncogenic lncRNA, promoting tumorigenesis and progression by regulating the expression of ETV1 gene. This highlights its potential as an effective target for treating GC.

Young breast cancer (YBC) is a subset of breast cancer that is often more aggressive, but less is known about its prognosis. In this study, we aimed to generate nomograms to predict the overall survival (OS) and breast cancer‐specific survival (BCSS) of YBC patients.

Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated into a training cohort (n = 15,227) and internal validation cohort (n = 6,526) at a 7:3 ratio. With the Cox regression models, significant prognostic factors were identified and used to construct 3‐, 5‐, and 10‐year nomograms of OS and BCSS. Data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database were used as an external validation cohort (n = 90).

We constructed nomograms incorporating 10 prognostic factors for OS and BCSS. These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort, with C‐indexes of 0.806 and 0.813, respectively. The calibration curves verified that the nomograms have good prediction accuracy. Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates. Additionally, we provided dynamic nomograms to improve the operability of the results. The risk stratification ability assessment also showed that the OS and BCSS rates of the low‐risk group were significantly better than those of the high‐risk group.

Here, we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC. These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.

The wide use of antibody‐drug conjugates (ADCs) is transforming the cancer‐treatment landscape. Understanding the treatment‐related adverse events (AEs) of ADCs is crucial for their clinical application. We conducted a meta‐analysis to analyze the profile and incidence of AEs related to ADC use in the treatment of solid tumors and hematological malignancies.

We searched the PubMed, Embase, and Cochrane Library databases for articles published from January 2001 to October 2022. The overall profile and incidence of all‐grade and grade ≥ 3 treatment‐related AEs were the primary outcomes of the analysis.

A total of 138 trials involving 15,473 patients were included in this study. The overall incidence of any‐grade treatment‐related AEs was 100.0% (95% confidence interval [CI]: 99.9%–100.0%; I² = 89%) and the incidence of grade ≥ 3 treatment‐related AEs was 6.2% (95% CI: 3.0%–12.4%; I² = 99%).

This study provides a comprehensive overview of AEs related to ADCs used for cancer treatment. ADC use resulted in a high incidence of any‐grade AEs but a low incidence of grade ≥ 3 AEs. The AE profiles and incidence differed according to cancer type, ADC type, and ADC components.