Cancer Management and Research最新文献

Background: Stem cell therapy is a potential approach for tumor treatment; however, its efficacy and safety remain incompletely controllable. Therefore, early prediction of tumor progression and therapeutic evaluation post-treatment to guide timely therapeutic adjustments is essential. Radiomics has recently been widely applied to assess tumor behavior and characteristics. This study aims to investigate the predictive value of MRI radiomics for therapeutic outcomes in the early stages of stem cell intervention in colon cancer.

Methods: Subcutaneous tumor models were established by implanting CM38 colon cancer cells into the inguinal region of C57BL/6 mice. Bone marrow mesenchymal stem cells (MSCs) were intravenously injected via the tail vein within 24 hours. T1 weighted MRI scans were performed on day 7 to extract radiomic features, monitor tumor growth, and evaluate neovascularization (CD34) and proliferation (Ki67) via immunohistochemistry. An early-stage MRI radiomics model was constructed to predict colon cancer progression.

Results: Tumors in the stem cell intervention group exhibited faster growth compared to the control group, though no significant volume difference was observed in the early phase. A total of 1162 radiomic features were extracted, with 17 strongly associated features (including texture features, first-order features texture and shape features) selected to build the prediction model. The final model demonstrated an AUC > 0.8 across both training and testing datasets.

Conclusion: Intravenous MSC injection promotes the progression of subcutaneously implanted CM38 colon cancer. An MRI radiomics-based predictive model was successfully established, enabling early prediction of tumor progression post-intervention.

Purpose: This study evaluates the effect of pandemic-related diagnostic and treatment delays on 3-year disease-free survival (DFS) in Taiwanese breast cancer patients.

Material and methods: This single-institution study analyzed breast cancer patients across three distinct periods: non-COVID-19 in 2017, pre-COVID-19 in 2019, and during the COVID-19 pandemic in 2020, to investigate the impact of the COVID-19 pandemic on DFS rates and recurrence rates. DFS was defined as the interval from surgery to the occurrence of breast cancer recurrence or death, whereas overall survival (OS) was defined as the interval from surgery to death from any cause. Follow-up protocol included regular clinical examinations and annual imaging, with a minimum follow-up of 36 months unless an event occurred earlier.

Results: The demographics of breast cancer patients changed from 2017 to 2020, with an average age increasing from 54.6 to 58.6 years. While overall survival (OS) did not vary significantly across the cohorts, DFS differed significantly, with the 2020 cohort experiencing a significant decline in DFS compared to 2017 (p = 0.027). Recurrence rates also increased, from 3.1% in 2017 to 7.6% in 2020.

Conclusion: The COVID-19 pandemic had a negative impact on the DFS of breast cancer patients, with the 2020 cohort experiencing a significantly shorter DFS time compared to the 2017 cohort.

Background: EGFR exon 20 insertion (Exon 20ins) is the most common type among rare EGFR mutations. It involves over 100 identified subtypes. These mutations are generally insensitive to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). The development of small-molecule targeted agents specifically designed for Exon 20ins has brought new hope to this patient population. However, responses to Exon 20ins targeting agents vary across different insertion subtypes, and there is currently a lack of research focused on treatment strategies specifically for near-loop mutations such as P772_H773insGNP.

Methods: To explore individualized treatment strategies, we reviewed the medical records of a patient with Exon 20ins P772_H773insGNP. Relevant medical history, laboratory and imaging findings, and treatment details were collected and analyzed.

Results: This case report describes a patient with advanced non-small cell lung cancer (NSCLC). The patient was diagnosed with adenocarcinoma of the right upper lobe (T3N1M1a, stage IV). Next-generation sequencing (NGS) detected an EGFR exon 20ins, specifically P772_H773insGNP. The patient experienced disease progression despite multiple lines of therapy. Following multidisciplinary discussion, furmonertinib was initiated as sixth-line therapy. The best overall response was assessed as partial response (PR), and as of the last follow-up, the patient had achieved a progression-free survival (PFS) of 10.5 months.

Conclusion: This case represents the first report of a favorable response to furmonertinib in a patient with the EGFR exon 20ins subtype P772_H773insGNP, a near-loop mutation. EGFR exon 20ins mutations are highly heterogeneous, and different subtypes exhibit varying sensitivities to targeted drugs. Exploring individualized treatment approaches is of great clinical importance.

Breast cancer (BC) surgery has been advanced through artificial intelligence (AI), which helps surgeons to gain more accurate results and apply surgical procedures. Despite the increasing focus on AI in BC management, there are knowledge gaps in the current understanding that can be readily identified from the existing works of literature. This narrative review aims to provide an update on the influencing role of AI technologies in precise and personalized clinical decision-making in BC surgery. We included articles published in English during the past 5 years from the major databases. Furthermore, this review used appropriate keywords with and without Boolean operators like "AND", "OR" and "NOT". We considered three major aspects for surgical practice: preoperative planning, intraoperative decision-making, and postoperative outcomes, while interpreting the studies. We found that AI-assisted BC surgery has advanced through the development of a new real-time, accurate tumor identifier, margin assessment, and robotic-assisted surgeries. Moreover, AI-based algorithms are gradually incorporated into the evaluation of the postoperative probability of reoccurrence, complications, and patient satisfaction. It is documented that integrating AI technologies into BC care is inevitable and set to expand further in all aspects. Furthermore, this review identified some major challenges in the algorithm and ethical aspects. The limitations, such as lack of external validation, integration barriers, and the "black box" nature of some AI models, remain unresolved. To fully utilize AI's capabilities, it is recommended that surgeons, AI developers, and policymakers collaborate on more advanced AI that is enhanced for personalized care by including patients' genetics, medical history, and lifestyle factors. Additionally, future prospective and exploratory cost-effective analysis studies are to be done.

Background: This study aimed to evaluate the survival predictability of preoperative systemic inflammation response index (SIRI), calculated as the absolute neutrophil count multiplied by the absolute monocyte count and divided by the absolute lymphocyte count, in patients with metachronous secondary primary head and neck squamous cell carcinoma (mspHNSCC) who had undergone prior radiotherapy for first primary HNSCC (fpHNSCC).

Methods: A total of 101 consecutive patients who underwent upfront surgery for mspHNSCC at a single institute between 2007 and 2016 were retrospectively reviewed between December 2023 and November 2024 and included in the analysis. The baseline leukocyte counts for the fpHNSCC and mspHNSCC were collected. Cox proportional hazards models were constructed using age and variables significant in univariate analysis to assess the impact of SIRI on overall survival (OS) and cancer-specific survival (CSS). Additionally, a SIRI-based nomogram was developed and validated.

Results: Statistically significant declines in baseline leukocyte counts were observed in mspHNSCC compared to fpHNSCC (p < 0.001). Among the inflammatory markers, the preoperative SIRI was the most predictive of survival outcomes for mspHNSCC. Higher SIRI values were significantly associated with poorer outcomes in both OS and CSS. The optimal SIRI cutoff for survival prediction was 1.383, as determined by receiver operating characteristic curve analysis with Youden's index; patients with SIRI ≥ 1.383 had significantly lower 5-year OS (32.9% vs 60.1%, p = 0.001) and CSS (64.7% vs 83.9%, p = 0.003). Multivariate analysis revealed lymphovascular invasion, extranodal extension, and high SIRI as independent adverse risk factors for CSS. The SIRI-based nomogram accurately predicted CSS, with a concordance index of 0.773.

Conclusion: Data from preoperative SIRI assessment, coupled with the presence of pathological adverse features, serve as valuable references for risk stratification in patients with previously irradiated mspHNSCC.

Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related death worldwide, and its complex tumor microenvironment (TME) presents significant challenges for the treatment of this disease. In recent years, tumor immunotherapy has emerged as one of the most successful strategies in cancer treatment, especially for advanced HCC. Programmed cell death protein-1 (PD-1) inhibitors have moderate efficacy as monotherapies for HCC. Tumor angiogenesis, a crucial factor in tumor growth and proliferation, plays a pivotal role in the immune regulation of HCC. The vascular and immune microenvironments of solid tumors engage in dynamic reciprocal crosstalk, forming a complex vascular-immune axis that critically shapes antitumor immune responses and drives therapy resistance. The high degree of angiogenesis observed in HCC leads to abnormal vascular structure and function, which not only promotes tumor growth but also induces hypoxia and acidosis within the TME, thereby suppressing the immune response through various mechanisms. Given the regulatory role of tumor blood vessels in the immune system, the integration of antiangiogenic therapy into current immunotherapy approaches provides a novel treatment option. This integration involves the inhibition of tumor angiogenesis, improvements in the TME, and enhancements of the immune response, among other mechanisms. This review summarizes the angiogenic mechanisms of HCC, the clinical applications of immunotherapy and the regulatory effects of angiogenesis on the immune response in HCC.

Objective:  To evaluate the incremental diagnostic value of combining free prostate-specific antigen density (FPSAD) with Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for clinically significant prostate cancer (csPCa,defined as Gleason score≥3+4) in the diagnostic gray zone (tPSA 4-10 ng/mL).

Methods: This retrospective study analyzed 137 patients (75 with csPCa and 62 with non-clinically significant prostate cancer (ncsPCa) who underwent transperineal prostate biopsy at Xiangtan Central Hospital between January 2022 and January 2024. PI-RADS v2.1 scores were assigned based on magnetic resonance (MR) imaging, and prostate volume (PV) and FPSAD were calculated. Statistical analyses included chi-square/Fisher's exact tests for categorical variables and independent t-tests for continuous variables. Logistic regression identified independent predictors of csPCa, and a nomogram model was developed. Model performance was evaluated using calibration curves and receiver operating characteristic (ROC) analysis.

Results:  Significant differences were observed in FPSAD, PI-RADS v2.1 scores, and free PSA (fPSA) between the csPCa and ncsPCa groups (P < 0.01). FPSAD (OR = 1.95, 95% CI: 1.22-2.22, P < 0.01) and PI-RADS v2.1 scores (OR = 2.41, 95% CI: 1.57-3.70, P < 0.01) were independent predictors of csPCa. The combined FPSAD and PI-RADS v2.1 model demonstrated superior diagnostic performance (AUC =0.829) compared to FPSAD alone (AUC = 0.69) or PI-RADS v2.1 alone (AUC = 0.773) (P < 0.01), with 91% sensitivity and 32% fewer unnecessary biopsies than PI-RADS≥3 criteria. In PI-RADS 3 subgroup (n=41), FPSAD correctly reclassified 13/18 (72.2%) indeterminate cases.

Conclusion:  For Asian men with tPSA 4-10 ng/mL, the FPSAD+PI-RADS algorithm (cutoffs: >0.017 and ≥4) provides 15-20% higher accuracy than either marker alone, while reducing biopsies by 25%. This approach is particularly valuable for PI-RADS 3 cases, where it resolved >65% of diagnostic uncertainties in our cohort.

Introduction: Research of Near-Infrared Photoimmunotherapy (NIR-PIT) related to human epidermal growth factor receptor (EGFR) in cancer is very popular in recent years. By destroying the cell membrane, NIR-PIT can kill cancer cells and prevent tumor development. By using a statistical method, our study aims to find out the suitable indices for evaluating the efficacy of EGFR-targeted NIR-PIT.

Methods: Exploring strategy: (mice OR vivo study OR animal model) AND (NIR-PIT OR near-infrared photoimmunotherapy OR photoimmunotherapy) AND (EGFR OR EGFR receptor) AND (cancer OR tumor). Including standard: ① Reports could obtain full text from 2014 to 2024. ② Reports using tumor volume as an index of outcome. ③ Reports using IR-700, NIR-PIT, and EGFR antigens. The exclusion criteria were as follows: ① Reports could not obtain the full text. ② Reports that did not use the index above. ③ Reports that did not use IR-700, NIR-PIT, or EGFR antigens. ④ Reports could not obtain concrete data from articles.

Results: Using the above standards, we finally acquired 20 articles that conformed to requests. In this analysis, tumor volume showed statistical meaning of differentiation between experimental and control groups. However, 50% survival did not show the statistical meaning in the analysis.

Discussion: Through analysis, we found that the NIR-PIT groups had obvious differences compared with the control groups in tumor volume. However, we did not find any difference in the survival rates between NIR-PIT and control groups. This may be due to the following reasons: ① the number of samples was insufficient. ② Other indices of survival rate were more suitable in this study than 50% survival rate.

Conclusion: Compared with 50% survival rate, tumor volume may be better for evaluating the efficacy of NIR-PIT.

Introduction: S100 calcium binding protein A6 (S100A6) has been confirmed to be involved in the occurrence and development of various malignant tumors, including lung adenocarcinoma (LADC). The impact of S100A6 on the drug resistance of cancer cell lines is still uncovered. PC9 cells with EGFR 19 exon mutation is commonly used in lung cancer cell experiments.

Methods: In this work, PC9 cells over-expressing S100A6 (PC9/S100A6) was successfully constructed, and the PC9 cells were set as control group simultaneously. MTT assay was used to detect and compare the growth rates of the cells in two groups at different concentrations and time points of gefitinib, cisplatin, pemetrexed, bevacizumab.

Results: Data showed that the inhibitory rates of gefitinib (0.01µmol/L, 0.1µmol/L, 1µmol/L) on PC9/S100A6 cells significantly decreased at 24h, 48h, 72h (P<0.05). Additionally, the inhibitory effects on PC9/S100A6 cells were significantly lower for 10 µmol/L gefitinib (at 48h and 72h), 100 µmol/L gefitinib (at 72h), 2.5 µg/mL cisplatin (at 48h and 72h), and 10 µg/mL cisplatin (at 72h). However, there is no obvious difference in the inhibitory rate of cisplatin (2.5µg/mL 24h; 10µg/mL 24h, 48h; 5µg/mL, 20µg/mL, 40µg/mL 24h, 48h, and 72h), pemetrexed, bevacizumab on two groups.

Conclusion: Our results demonstrated that S100A6 can apparently promote the resistance to gefitinib of LADC PC9 cell lines with EGFR 19 exon mutations.

Background: Accurate preoperative prediction of axillary lymph node (ALN) metastasis in breast cancer is crucial for surgical planning and reducing morbidity. Conventional ultrasound and Doppler methods are limited by subjectivity, while existing machine learning (ML) models often lack interpretability and multi-center validation.

Aim: To evaluate 11 ML algorithms and develop a validated model integrating ultrasound and Doppler features for ALN metastasis prediction, using SHapley Additive exPlanations (SHAP) for interpretability.

Methods: This retrospective dual-center study included 303 patients from Xiamen (internal cohorts: 212 training, 91 validation) and 102 from Longyan (external validation). Features were extracted from preoperative ultrasound and Doppler images. Recursive feature elimination (RFE) and SHAP selected key predictors. Gradient Boosting was identified as optimal and compared to B-mode/Doppler submodels and clinicopathological scores (Logical, Tumor, Tenon). Performance was assessed via AUC, calibration, decision curve analysis (DCA), and a web calculator was developed.

Results: Five features-tumor diameter, cortex-to-hilum ratio, lymph node systolic/diastolic ratio, peak systolic velocity, and end-diastolic velocity-were selected. The combined model achieved AUCs of 0.981 (training), 0.975 (internal validation), and 0.987 (external validation), outperforming scores (AUCs 0.517-0.700). It showed superior calibration (Brier scores 0.045-0.061) and net benefit in DCA.

Conclusion: The Gradient Boosting model with SHAP provides accurate, interpretable ALN metastasis prediction, supporting noninvasive risk stratification and personalized breast cancer management.