Background: The aim was to evaluate the changes of 16S rDNA sequencing and LC-MS metabolomics in breast cancer and explore the growth inhibition of breast cancer cells by Faecalibacterium prausnitzii. Results: Total 49 significantly different flora and 26 different metabolites were screened between two groups, and the correlation was calculated. Relative abudance of Firmicutes and Bacteroidetes were decreased, while relative abundance of verrucomicrobla, proteobacteria and actinobacteria was increased in breast cancer group. Differentially expressed metabolites were mainly enriched in pathways such as linoleic acid metabolism, retrograde endocannabinoid signaling, biosynthesis of unsaturated fatty acids, choline metabolism in cancer and arachidonic acid metabolism. Lipid upregulation was found in breast cancer patients, especially phosphorocholine. The abundance of Faecalibacterium was reduced in breast cancer patients, which was negatively correlated with various phosphorylcholines. Moreover, Faecalibacterium prausnitzii, the most well-known species in Faecalibacterium genus, could inhibit the secretion of interleukin-6 (IL-6) and the phosphorylation of Janus kinases 2 (JAK2)/signal transducers and activators of transcription 3 (STAT3) in breast cancer cells. Faecalibacterium prausnitzii also suppressed the proliferation and invasion and promoted the apoptosis of breast cancer cells, while these effects disappeared after adding recombinant human IL-6. Conclusions: Flora-metabolites combined with the flora-bacteria (such as Faecalibacterium combined with phosphorocholine) might a new detection method for breast cancer. Faecalibacterium may be helpful for prevention of breast cancer. Faecalibacterium prausnitzii suppresses the growth of breast cancer cells through inhibition of IL-6/STAT3 pathway.

Radiotherapy is an important treatment for many unresectable advanced malignant tumors, and radiotherapy-associated inflammatory reactions to radiation and other toxic side effects are significant reasons which reduce the quality of life and survival of patients. FLASH-radiotherapy (FLASH-RT), a prominent topic in recent radiation therapy research, is an ultra-high dose rate treatment known for significantly reducing therapy time while effectively targeting tumors. This approach minimizes radiation side effects on at-risk organs and maximally protects surrounding healthy tissues. Despite decades of preclinical exploration and some notable achievements, the mechanisms behind FLASH effects remain debated. Standardization is still required for the type of FLASH-RT rays and dose patterns. This review addresses the current state of FLASH-RT research, summarizing the biological mechanisms behind the FLASH effect. Additionally, it examines the impact of FLASH-RT on immune cells, cytokines, and the tumor immune microenvironment. Lastly, this review will discuss beam characteristics, potential clinical applications, and the relevance and applicability of FLASH-RT in treating advanced cancers.

Although radiotherapy is the second most effective cancer treatment, radiation injuries limit its use. About 80% of abdominal-pelvic radiotherapy patients develop acute radiation enteritis, with 20% discontinuing radiotherapy. The lack of effective mitigation measures restricts its clinical application. Recent studies have proposed gut microbiota as a potential biomarker for radiation injuries. However, the interaction between gut microbiota and radiation injuries remains poorly understood. This review summarizes two forms of interaction between gut microbiota and radiation injuries based on the location of the radiation field. One type of interaction, referred to as “direct interaction,” involves changes in the diversity and composition of gut microbiota, alterations in microbiota-derived metabolites, disruption of the intestinal barrier, activation of inflammatory responses within the intestine, and involvement of the host’s immune system. The second form, called “indirect interaction,” includes the influence of the gut microbiota on various body systems, such as gut microbiota–brain axis, gut microbiota–cardiopulmonary axis, and gut microbiota–oral axis. Additionally, we examine promising interventions aimed at reshaping the gut microbiota, including the use of probiotics, prebiotics, and fecal microbiota transplantation. The interaction between radiation injuries and gut microbiota is more complex than previously understood. Therefore, further clarification of the underlying mechanisms will facilitate the application of gut microbiota in preventing and alleviating radiation injuries.

Challenges and exploration for immunotherapies targeting cold colorectal cancer

Radical prostatectomy (prostate removal) is a standard treatment for clinically localized prostate cancer and is often followed by postoperative radiotherapy. Postoperative radiotherapy requires accurate delineation of the clinical target volume (CTV) and lymph node drainage area (LNA) on computed tomography (CT) images. However, the CTV contour cannot be determined by the simple prostate expansion after resection of the prostate in the CT image. Constrained by this factor, the manual delineation process in postoperative radiotherapy is more time-consuming and challenging than in radical radiotherapy. In addition, CTV and LNA have no boundaries that can be distinguished by pixel values in CT images, and existing automatic segmentation models cannot get satisfactory results. Radiation oncologists generally determine CTV and LNA profiles according to clinical consensus and guidelines regarding surrounding organs at risk (OARs). In this work, we design a cascade segmentation block to explicitly establish correlations between CTV, LNA, and OARs, leveraging OARs features to guide CTV and LNA segmentation. Furthermore, inspired by the success of the self-attention mechanism and self-supervised learning, we adopt SwinTransformer as our backbone and propose a pure SwinTransformer-based segmentation network with self-supervised learning strategies. We performed extensive quantitative and qualitative evaluations of the proposed method. Compared to other competitive segmentation models, our model shows higher dice scores with minor standard deviations, and the detailed visualization results are more consistent with the ground truth. We believe this work can provide a feasible solution to this problem, making the postoperative radiotherapy process more efficient.

Background: Prostate alignment is subject to interobserver variability in cone-beam CT (CBCT)-based soft-tissue matching. This study aims to analyze the impact of possible interobserver variability in CBCT-based soft-tissue matching for prostate cancer radiotherapy. Methods: Retrospective data, consisting of 156 CBCT images from twelve prostate cancer patients with elective nodal irradiation were analyzed in this study. To simulate possible interobserver variability, couch shifts of 2 mm relative to the resulting patient position of prostate alignment were assumed as potential patient positions (27 possibilities). For each CBCT, the doses of the potential patient positions were re-calculated using deformable image registration-based synthetic CT. The impact of the simulated interobserver variability was evaluated using tumor control probabilities (TCPs) and normal tissue complication probabilities (NTCPs). Results: No significant differences in TCPs were found between prostate alignment and potential patient positions (0.944 ± 0.003 vs 0.945 ± 0.003, P = 0.117). The average NTCPs of the rectum ranged from 5.16 to 7.29 (%) among the potential patient positions and were highly influenced by the couch shift in the anterior–posterior direction. In contrast, the average NTCPs of the bladder ranged from 0.75 to 1.12 (%) among the potential patient positions and were relatively negligible. Conclusions: The NTCPs of the rectum, rather than the TCPs of the target, were highly influenced by the interobserver variability in CBCT-based soft-tissue matching. This study provides a theoretical explanation for daily CBCT-based image guidance and the prostate-rectum interface matching procedure. Trial registration: Not applicable.