Papillary thyroid carcinoma (PTC) has a high incidence, and its proper treatment remains challenging. Therefore, identifying PTC progression markers is essential. Here, using 16S RNA sequences, we analyzed the PTC intratumor microbiome and its role in tumor progression. Substantial microbial abundance was detected in PTC from all patients. The tumor bacterial diversity in patients with advanced lesions (T3/T4) was significantly higher than that in patients with relatively mild lesions (T1/T2). Importantly, we identified signatures of eight tumor bacterial taxa highly predictive of PTC invasion status. Hence, microbial host factors—independent of the genomic composition of the tumor—may determine tumor behaviors and patient outcomes. Furthermore, the correlation between specific bacterial genus and thyroid hormones or autoimmune thyroid disease-related antibodies may indicate the potential contribution of the microbiome in the relationship between autoimmune thyroid disease or irregular thyroid function and PTC progression, intervention of which might therefore be worth exploring for advancing oncology care.

BackgroundSentinel lymph node (SLN) biopsy is feasible for breast cancer (BC) patients with clinically negative axillary lymph nodes; however, complications develop in some patients after surgery, although SLN metastasis is rarely found. Previous predictive models contained parameters that relied on postoperative data, thus limiting their application in the preoperative setting. Therefore, it is necessary to find a new model for preoperative risk prediction for SLN metastasis to help clinicians facilitate individualized clinical decisions.Materials and MethodsBC patients who underwent SLN biopsy in two different institutions were included in the training and validation cohorts. Demographic characteristics, preoperative tumor pathological features, and ultrasound findings were evaluated. Multivariate logistic regression was used to develop the nomogram. The discrimination, accuracy, and clinical usefulness of the nomogram were assessed using Harrell’s C-statistic and ROC analysis, the calibration curve, and the decision curve analysis, respectively.ResultsA total of 624 patients who met the inclusion criteria were enrolled, including 444 in the training cohort and 180 in the validation cohort. Young age, high BMI, high Ki67, large tumor size, indistinct tumor margins, calcifications, and an aspect ratio ≥1 were independent predictive factors for SLN metastasis of BC. Incorporating these parameters, the nomogram achieved a robust predictive performance with a C-index and accuracy of 0.92 and 0.85, and 0.82 and 0.80 in the training and validation cohorts, respectively. The calibration curves also fit well, and the decision curve analysis revealed that the nomogram was clinically useful.ConclusionsWe established a nomogram to preoperatively predict the risk of SLN metastasis in BC patients, providing a non-invasive approach in clinical practice and serving as a potential tool to identify BC patients who may omit unnecessary SLN biopsy.

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Background: A sentinel lymph node biopsy (SLNB) is a routine procedure for axillary staging in cN0 breast cancer (BC) patients. Indocyanine green (ICG) fluorescence can detect sentinel lymph nodes with higher sensitivity than carbon nanoparticle suspension (CNS). The present study investigated the availability and benefits of a near-infrared (NIR) laparoscopy-assisted SLNB using ICG and carbon nanoparticle suspension as tracers.Methods: Forty patients with invasive BC, who had clinically negative axillary lymph nodes, participated in this observational study. ICG and CNS tracers were injected into the periareolar region simultaneously or sequentially. In the endoscopy-assisted group (n=20), the patients were given NIR laparoscopic SLNB based on ICG fluorescence and CNS staining. In the open-surgery group, the patients were given traditional SLNB using an open incision, and CNS tracers were injected into the same region as that in the endoscopyassisted group.Results: In the endoscopy-assisted group, lymphatic vessels and sentinel lymph nodes (SLNs) were successfully identified using ICG fluorescence imaging in most patients (19/20). The average number of SLNs removed was 2.85 (range, 1-4) in the endoscopy-assisted group, and 3.40 (range, 1-7) in the opensurgery group. There was no significant difference between the number of detected nodes (P=0.30). The patients who underwent endoscopy-assisted SLNBs had similar operating times, blood loss and hospital-stay lengths, but lower postoperative drainage volumes and higher satisfaction scores, as they did not have axillary incisions. Conclusions:The NIR laparoscopy-assisted ICG-guided technique is a feasible and surgeon-friendly method for SLNB with good efficacy and acceptable safety. When combined with CNS, more SLNs can be detected and dissected.

Background: It has been established that clusterin is involved in the invasion of immune cells in the tumor microenvironment, but it remains unknown how it promotes immune invasion in breast cancer. Methods:We used Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to assess the relation between expression of clusterin and immunoinfiltration-related marker genes. TIMER database was used to evaluate the expression of clusterin, and its relation to tumor immune invasion was examined. Based on Kaplan-Meier plotter database, we investigated the association between clusterin expression and prognosis in patients with cancer, and the impact of clinicopathological factors and cancer-related outcomes.Results: Clusterin expression was markedly associated with prognosis of a variety of tumors, specifically breast cancer. Enhanced clusterin expression was markedly associated with molecular typing of breast cancer and expression of multiple markers related to specific immune cell subsets.Conclusions: These results indicate that clusterin is connected to prognosis of breast cancer patients and tumor immune cell infiltration. This demonstrates that clusterin may be a biomarker of immune cell recruitment into breast tumors and an important biomarker for immune cell infiltration; consequently being a valuable prognostic factor in breast cancer patients.