Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics-Clinical Integration Approach.

BACKGROUND: Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations. PURPOSE: To analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients. STUDY TYPE: Retrospective. POPULATION: Two hundred forty-two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC - TLS group (N = 120). FIELD STRENGTH/SEQUENCE: 3.0T; Caipirinha-Dixon-TWIST-volume interpolated breath-hold sequence for dynamic contrast-enhanced (DCE) MRI and inversion-recovery turbo spin echo sequence for T2-weighted imaging (T2WI). ASSESSMENT: Three models for differentiating BC + TLS and BC - TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were compared to evaluate the prognostic value of TLSs. STATISTICAL TESTS: LASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan-Meier method was used to calculate the survival rate. RESULTS: The radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow-up time was 52 months. While there was no significant difference in 3-year OS (P = 0.22) between BC + TLS and BC - TLS patients, there were significant differences in 3-year DFS and 3-year DMFS between the two groups. DATA CONCLUSION: The nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long-term disease control rates and better prognoses than those without TLS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Implanted, Wireless, Self-Powered Photodynamic Therapeutic Tablet Synergizes with Ferroptosis Inducer for Effective Cancer Treatment.

The effective and targeted treatment of resistant cancer cells presents a significant challenge. Targeting cell ferroptosis has shown remarkable efficacy against apoptosis-resistant tumors due to their elevated iron metabolism and oxidative stress levels. However, various obstacles have limited its effectiveness. To overcome these challenges and enhance ferroptosis in cancer cells, we have developed a self-powered photodynamic therapeutic tablet that integrates a ferroptosis inducer (FIN), imidazole ketone erastin (IKE). FINs augment the sensitivity of photodynamic therapy (PDT) by increasing oxidative stress and lipid peroxidation. Furthermore, they utilize the Fenton reaction to supplement oxygen, generating a greater amount of reactive oxygen species (ROS) during PDT. Additionally, PDT facilitates the release of iron ions from the labile iron pool (LIP), accelerating lipid peroxidation and inducing ferroptosis. In vitro and in vivo experiments have demonstrated a more than 85% tumor inhibition rate. This synergistic treatment approach not only addresses the limitations of inadequate penetration and tumor hypoxia associated with PDT but also reduces the required medication dosage. Its high efficiency and specificity towards targeted cells minimize adverse effects, presenting a novel approach to combat clinical resistance in cancer treatment.

Detection and quantitative analysis of tumor-associated tertiary lymphoid structures. / è‚¿ç˜¤ç›¸å ³çš„ä¸‰çº§æ·‹å·´ç»“æž„çš„æ£€æµ‹å’Œé‡åŒ–åˆ†æž.

Tumor-associated tertiary lymphoid structures (TLSs) are ectopic lymphoid formations within tumor tissue, with mainly B and T cell populations forming the organic aggregates. The presence of TLSs in tumors has been strongly associated with patient responsiveness to immunotherapy regimens and improving tumor prognosis. Researchers have been motivated to actively explore TLSs due to their bright clinical application prospects. Various studies have attempted to decipher TLSs regarding their formation mechanism, structural composition, induction generation, predictive markers, and clinical utilization. Meanwhile, the scientific approaches to qualitative and quantitative descriptions are crucial for TLS studies. In terms of detection, hematoxylin and eosin (H&E), multiplex immunohistochemistry (mIHC), multiplex immunofluorescence (mIF), and 12-chemokine gene signature have been the top approved methods. However, no standard methods exist for the quantitative analysis of TLSs, such as absolute TLS count, analysis of TLS constituent cells, structural features, TLS spatial location, density, and maturity. This study reviews the latest research progress on TLS detection and quantification, proposes new directions for TLS assessment, and addresses issues for the quantitative application of TLSs in the clinic.

Altered temporal-parietal morphological similarity networks in non-small cell lung cancer patients following chemotherapy: an MRI preliminary study.

Non-small cell lung cancer (NSCLC) accounts for more than 85% of all lung cancer cases, and chemotherapy-related brain changes (known as "chemobrain") in NSCLC patients were found in previous studies. However, the effects of platinum-based chemotherapy on brain structural networks are still unclear. Structural magnetic resonance imaging (sMRI) data were collected from 32 NSCLC patients following platinum-based chemotherapy, 36 NSCLC patients without chemotherapy, and 39 healthy controls. Clinical physiological indicators of patients were collected. Then, morphological similarity networks were constructed using MRI data, and topological properties were calculated using graph theory method. Differences between three groups were investigated using one-way ANOVA and two-sample t-test, and relations between topological properties and clinical physiological indicators were calculated. We found that degree and nodal efficiency in temporal-parietal networks were significantly reduced in NSCLC patients following platinum-based chemotherapy compared to healthy controls/patients without chemotherapy (F-test, p < 0.001; post hoc t-test, p < 0.01, Bonferroni corrected). These changes (p < 0.05) were positively correlated with clinical measures, including thrombocytes, granulocytes and hemoglobin, and were negatively correlated with measures of triglycerides and cholesterol levels. Network properties including clustering coefficient (F(2,104) = 41.435, p < 0.001), number of K-edges (F(2,104) = 40.304, p < 0.001), density of K-edges (F(2,104) = 40.304, p < 0.001), global efficiency (F(2,104) = 42.585, p < 0.001) and small-world (F(2,104) = 37.132, p < 0.001) were also significantly reduced (post hoc t-test, p < 0.01, Bonferroni corrected). These results indicate that platinum-based chemotherapy might cause cerebrovascular damage and clinical indicators' changes, which then cause the properties of morphological similarity networks' changes in the temporal and parietal lobes. This study may help us better understand the "chemobrain" in NSCLC patients.

Integration of MRI-Based Radiomics Features, Clinicopathological Characteristics, and Blood Parameters: A Nomogram Model for Predicting Clinical Outcome in Nasopharyngeal Carcinoma.

Purpose: This study aimed to develop a nomogram model based on multiparametric magnetic resonance imaging (MRI) radiomics features, clinicopathological characteristics, and blood parameters to predict the progression-free survival (PFS) of patients with nasopharyngeal carcinoma (NPC). Methods: A total of 462 patients with pathologically confirmed nonkeratinizing NPC treated at Sichuan Cancer Hospital were recruited from 2015 to 2019 and divided into training and validation cohorts at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was used for radiomics feature dimension reduction and screening in the training cohort. Rad-score, age, sex, smoking and drinking habits, Ki-67, monocytes, monocyte ratio, and mean corpuscular volume were incorporated into a multivariate Cox proportional risk regression model to build a multifactorial nomogram. The concordance index (C-index) and decision curve analysis (DCA) were applied to estimate its efficacy. Results: Nine significant features associated with PFS were selected by LASSO and used to calculate the rad-score of each patient. The rad-score was verified as an independent prognostic factor for PFS in NPC. The survival analysis showed that those with lower rad-scores had longer PFS in both cohorts (p < 0.05). Compared with the tumor-node-metastasis staging system, the multifactorial nomogram had higher C-indexes (training cohorts: 0.819 vs. 0.610; validation cohorts: 0.820 vs. 0.602). Moreover, the DCA curve showed that this model could better predict progression within 50% threshold probability. Conclusion: A nomogram that combined MRI-based radiomics with clinicopathological characteristics and blood parameters improved the ability to predict progression in patients with NPC.