Clinical Medicine Insights-Oncology最新文献

Background: Malignant peritoneal mesothelioma (MPeM) is a rare and progressive cancer originating from the mesothelial cells of the peritoneum. In patients with early-stage disease who are suitable for surgery, the treatment of choice is CRS + HIPEC, whereas in advanced-stage patients, systemic treatments are applied. Pemetrexed plus platinum regimens are at the forefront of first-line systemic treatments. Gemcitabine plus platinum regimens are rarely used as first-line treatment for MPeM. The aim of our study is to compare the efficacy of first-line pemetrexed plus platinum with gemcitabine plus platinum regimens in patients with MPeM.

Methods: In this study, a retrospective analysis was conducted on 48 patients with MPeM who were followed up in our clinic between 2001 and 2025. In our study, 28 patients received pemetrexed plus platinum as a first-line regimen, while 20 patients received gemcitabine plus platinum. The median overall survival (OS), median progression-free survival (PFS), and response rates for both regimens were analyzed. In addition, prognostic factors influencing overall survival were investigated in the entire patient population.

Results: The median PFS and OS were 11.1 months and 17.0 months for pemetrexed and 8.01 months and 14.4 months for gemcitabine. Although pemetrexed showed numerically higher PFS and OS, the difference was not statistically significant. The objective response rate (ORR) and disease control rate (DCR) were 32.1% and 57.1% for pemetrexed, compared with 25% and 40% for gemcitabine, showing pemetrexed's superiority in response rates. In the entire patient population, CRS + HIPEC was the main prognostic factor for survival.

Conclusion: We have demonstrated that the pemetrexed + platinum regimen has better response rates compared with the gemcitabine + platinum regimen in MPeM patients. However, gemcitabine-based regimens can be used as an alternative to pemetrexed in patients with MPeM.

Background: This study aimed to examine severe bone marrow suppression risk factors during radiotherapy in patients with cervical cancer and to develop and validate a visual evaluation tool for predicting the risk of severe bone marrow suppression during radiotherapy in these patients.

Methods: A total of 300 patients with cervical cancer who underwent radiotherapy were retrospectively included in this cohort study. Patients were randomly divided into a model group (n = 240) and a validation group (n = 60) at a ratio of 8:2. Univariate and multivariate logistic regression analyses were performed to explore and establish a nomogram prediction model. The feasibility of this nomogram model in predicting the risk of severe bone marrow suppression during radiotherapy in patients with cervical cancer was assessed in the validation cohort. The discrimination ability, accuracy, and clinical utility of the model were evaluated via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results: Menopausal status, Karnofsky performance score (KPS), clinical stage, concurrent chemotherapy status, and pre-radiotherapy creatinine level were identified as independent risk factors for severe bone marrow suppression during radiotherapy in patients (P < .05). DCA revealed that the nomogram model had a greater net benefit in predicting the risk of severe bone marrow suppression during radiotherapy in patients with cervical cancer when the patient's threshold probability was between 0.20 and 0.93.

Conclusion: The nomogram model based on these independent risk factors exhibited good predictive performance, assisting in individualized risk assessment and facilitating early intervention to benefit patients during radiotherapy.

Background: Vietnam is an endemic region for nasopharyngeal cancer (NPC), with approximately 70% of cases diagnosed at stage III-IVa and 90% presenting with undifferentiated histology closely related to Epstein-Barr virus (EBV) infection. However, no studies have identified biomarkers predictive of recurrence and metastasis. This study aimed to determine the cut-off concentrations of cell-free (cf) EBV DNA for predicting recurrence and metastasis in NPC.

Methods: A longitudinal descriptive study was conducted on 58 patients with stage III-IVa undifferentiated NPC between August 2021 and August 2024. We analysed the predictive value of cf EBV DNA concentrations at pre-treatment (preEBV) and post-treatment (postEBV, 6 months postEBV [EBV6], 12 months postEBV [EBV12]) in relation to disease progression and survival outcomes.

Results: Of the 58 patients, 23 experienced recurrence and/or metastasis. The recurrence prediction cut-off concentration was 3980.0 copies/mL for preEBV (area under the curve [AUC] = 0.705, 95% confidence interval [CI]: 0.499-0.911, Se = 80.0%, Sp = 64.6%, odds ratio [OR] = 7.294, 95% CI: 1.389-38.307, accuracy [ACC] = 67.2%); 12.5 copies/mL for EBV6 (AUC = 0.783, 95% CI: 0.600-0.966, Se = 77.8%, Sp = 75.0%, OR = 10.5, 95% CI: 1.839-54.242, ACC = 75.5%); and 5.5 copies/mL for EBV12 (AUC = 0.766, 95% CI: 0.577-0.954, Se = 83.3%, Sp = 78.0%, OR = 17.778, 95% CI: 1.835-172.219, ACC = 78.7%). The metastasis prediction cut-off concentration for EBV12 was 42.5 copies/mL (AUC = 0.748, 95% CI: 0.502-0.994, Se = 66.7%, Sp = 80.5%, OR = 8.250, 95% CI: 1.278-52.254, ACC = 78.7%). Cut-off concentrations of preEBV, EBV6, and EBV12 were independent predictors of survival outcomes (except for EBV6). All results were statistically significant (P < .05).

Conclusions: In advanced-stage NPC-undifferentiated subtype, preEBV, EBV6, and EBV12 serve as predictive biomarkers for recurrence and metastasis. Among these, EBV12 demonstrated the highest predictive value.

Background: Myelosuppression is a frequent complication in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy. Current clinical practice relies predominantly on treatment-phase monitoring for myelosuppression risk assessment, while effective pretreatment prediction tools are lacking. This study developed a predictive model based on pretreatment clinical indicators to facilitate early identification of high-risk patients and support clinical decision-making.

Methods: We conducted a retrospective cohort study using electronic medical records of 210 patients with NPC who received chemoradiotherapy at the First Affiliated Hospital of Bengbu Medical University between May 2016 and December 2021. Using R software, patients were randomly allocated into a training set (n = 150) and an internal validation set (n = 60) at a 7:3 ratio. Variable selection was performed using Least Absolute Shrinkage and Selection Operator regression, followed by univariable and multivariable logistic regression analyses to identify potential predictors. Following categorization of these identified potential predictors, Firth penalized-likelihood regression was employed to correct for small-sample bias, while multicollinearity was rigorously assessed using variance inflation factors (VIFs). A predictive nomogram was subsequently constructed. Model performance was evaluated through multiple validation metrics, including the concordance index (C-index), receiver operating characteristic curve analysis, clinical decision curve analysis, and calibration curve.

Results: Multivariable logistic regression analysis identified 3 potential predictors of myelosuppression: pretreatment plateletcrit (PCT), direct bilirubin (DBIL), and sodium ions (Na⁺) (all P < .05). All these potential predictors met strict stability criteria after conversion to categorical variables (all VIF < 2.1, with a predefined threshold of VIF < 5). Model evaluation demonstrates that the developed nomogram exhibits favorable predictive performance.

Conclusion: Pretreatment PCT, DBIL, and Na⁺ may serve as potential predictors of myelosuppression in patients with NPC undergoing chemoradiotherapy. This nomogram could serve as a risk stratification tool to identify high-risk patients before treatment, enabling early interventions for myelosuppression prevention.

Background: Triple-negative breast cancer (TNBC) lacks effective targeted therapies, underscoring the need for novel molecular targets. Gonadotropin-releasing hormone receptor (GnRHR) has been shown to suppress TNBC proliferation and metastasis. G protein-coupled receptor 173 (GPR173), known to regulate GnRHR in neuroendocrine cells, has an undefined role in TNBC. This study aimed to determine whether GPR173 modulates TNBC progression through GnRHR-mediated signaling.

Methods: GPR173 and GnRHR expression levels were analyzed in TNBC tissues and correlated with patient prognosis. In vitro, TNBC cell lines were modified to knock down or overexpress GPR173 and GnRHR. Cell proliferation, migration, invasion, and expression of dual specificity phosphatase 1 (DUSP1), phosphorylated/total protein kinase B (AKT), phosphorylated/total extracellular signal-regulated kinase (ERK), and matrix metallopeptidase 2 (MMP2) were evaluated.

Results: GPR173 and GnRHR expression was significantly reduced in TNBC tumors compared to normal breast tissues. Low expression of either protein correlated with poorer overall survival and increased lymph node metastasis. In vitro, GPR173 knockdown promoted TNBC cell proliferation, migration, and invasion, and reduced GnRHR expression. These changes were accompanied by increased phosphorylation of AKT and ERK, and elevated MMP2 expression. Notably, the pro-proliferative, pro-migratory, and pro-invasive effects of GPR173 knockdown were reversed by rescue overexpression of GnRHR. This GnRHR overexpression was accompanied by upregulation of DUSP1, dephosphorylation of AKT and ERK, and decreased MMP2 levels.

Conclusions: Based on these in vitro data, GPR173 likely constrains the pro-proliferative, pro-migratory, and pro-invasive phenotypes of TNBC cells by enhancing GnRHR signaling. These findings highlight GnRHR and GPR173 as potential therapeutic targets for TNBC.

Accumulating evidence demonstrates that the tumor microenvironment (TME) drives immune suppression through complicated regulations including host-microbe interactions, which poses vaginal microbiome as one of vital regulators of immune microenvironment. This narrative review examined the composition and dynamic changes of vaginal microbiota during carcinogenesis, focusing on mechanistic insights linking microbial dysbiosis to tumor immunity. Notably, commensal bacteria exhibit diverse immunoregulatory functions that can either potentiate or inhibit anti-tumor responses. Clinical evidence further reveals that CST IV microbiota associates with significantly elevated cancer risk, while probiotic interventions show promise in restoring immune surveillance. Critical gaps in standardization of microbiota-based therapies are addressed, emphasizing the need for strain-specific characterization and optimized delivery systems. Collectively, deciphering vaginal microbiome-immune crosstalk opens new avenues for precision interception against cervical cancer.

Background: Artificial intelligence (AI) is increasingly applied to colposcopy to enhance the detection of cervical intraepithelial neoplasia (CIN) and cervical cancer. We conducted a systematic review to summarize the diagnostic performance achieved by AI‑based colposcopic systems.

Methods: Following the PRISMA 2020 guidelines, the PubMed database was searched using the search terms 'artificial intelligence' and 'colposcop*' for articles published between 2019 and 2024. From the initial 43 articles retrieved, 19 studies were selected based on specific inclusion criteria: original research articles, written in the English language, and relevant to CIN or cervical cancer diagnosis. For each, we extracted the sample size, AI architecture (e.g., convolutional neural networks, U-Net/DeepLab V3 + segmentation models, multimodal fusion networks), reference standard, and reported metrics (sensitivity, specificity, accuracy, and area under the curve).

Results: Across multiple studies, AI systems demonstrated superior diagnostic accuracy, sensitivity, and specificity, particularly for early detection of high-risk lesions and classification of cervical abnormalities. Deep-learning models, such as convolutional neural networks, consistently outperformed conventional methods by reducing diagnostic variability and offering robust performance even in low-resource settings. The review also highlights the potential of AI for real-time diagnostics and its capacity to support clinical decision-making via automated systems.

Conclusion: AI has the potential to revolutionize cervical cancer diagnosis and management by enhancing the accuracy and efficiency of colposcopic evaluations. However, challenges remain, including the development of standardized datasets, validation in diverse populations, and ethical considerations surrounding data privacy and access to technology. Continued research and development are crucial to harness AI's global potential to improve patient outcomes.

Background: With the increasing number of cancer survivors, second primary malignancies (SPMs) are attracting clinical interest. Although SPMs following multiple myeloma (MM) have been studied, data on second primary multiple myeloma (SPMM) remain limited. This study aimed to compare the clinical characteristics and outcomes of SPMM with those of primary MM through a retrospective analysis.

Methods: We retrospectively reviewed 183 patients with primary MM and 12 patients with SPMM treated at a single center between 2003 and 2022. To reduce selection bias, propensity score matching (1:3) was performed based on age, sex, year of MM diagnosis, and International Staging System stage. Survival outcomes were assessed using Kaplan-Meier analysis and Cox proportional hazards models.

Results: After matching, 48 patients (36 with primary MM and 12 with SPMM) were included in the final analysis. At the time of MM diagnosis, 83.3% of patients with SPMM had achieved complete remission of their primary malignancy. All but one received standard MM treatment. The median overall survival (OS) was 45.1 months for the primary MM group and 41.5 months for the SPMM group. There was no statistically significant difference in OS between the groups (hazard ratio: 0.72; 95% confidence interval: 0.33-1.56).

Conclusions: Patients with SPMM, most of whom had well-controlled primary cancers, received active treatment and demonstrated clinical outcomes not significantly different from those with primary MM. These findings support the use of aggressive treatment strategies for SPMM. Larger prospective studies are warranted to establish optimal treatment strategies.

Background: This retrospective cohort study aims to study the changes of the exposed volume of the bladder and rectum under different filling states, and to clarify the influences of the morphing organs on themselves and each other, to provide the basis for reducing the risk of organ damage by intensity-modulated radiotherapy (IMRT) for cervical cancer.

Methods: A retrospective analysis was performed on 24 patients with cervical cancer who received IMRT. Before radiotherapy, a comfortably full bladder and active defecation was ensured for all patients, and interative cone-beam computed tomography (iCBCT) was performed to delineate the bladder, rectum, and small intestine. The filling degree of the bladder, rectum, and small intestine and their intersection with the planned target volume were recorded.

Results: 83.44% of patients exhibited reduced bladder volume during treatment. When the planned bladder volume was 400-500 cc, the bladder volume changed the least during treatment (F = 58.39, P < .001). The exposed volume of the small intestine was moderately correlated with the degree of bladder filling (r = -.674, P < .01). For every 10% increase in bladder volume, the exposed volume of the small intestine decreased by 24.05% (P < .01). Furthermore, 45.83% patients had an increase in rectum volume during treatment. The exposed volume increased by 9.47% for every 10% increase in rectum volume (P < .01).

Conclusion: Comfortable bladder and active defecation regimens may not keep bladder and rectal stability. Targeting a planned bladder volume of 400 to 500cc minimizes intrafraction variability. Strategic bladder filling optimization may mitigate small intestine exposure.