Clinical & Translational Oncology最新文献

Background and objectives: Genomic alterations after resistance to osimertinib therapy in advanced T790M-mutated non-small cell lung cancer (NSCLC) are complex and poorly understood. In this study, we aimed to detect these genomic alternations via comprehensive next-generation sequencing (NGS) of tissue and liquid biopsies.

Patients and methods: From September 2020 to June 2021, 31 stage IIIB/IV T790M-mutated NSCLC patients who exhibited progressive disease after osimertinib therapy and provided written informed consent were recruited. Liquid and tissue biopsy samples for NGS testing were collected from 31 and 18 patients, respectively. Eighteen study patients had paired NGS data from tissue and liquid biopsies.

Results: With respect to the T790M mutation status, the preservation and loss rates were 33% and 67%, respectively, in both liquid and tissue biopsy samples. Five patients (16.1%) had the C797S mutation (4 liquid samples and 1 tissue sample). Two (6.5%) had MET mutations, 3 (9.7%) had BRAF-V600E mutations, and 1 (3.2%) had a KRAS-G12C mutation. Among the 18 patients who underwent tissue rebiopsies, those with preserved T790M mutation had significantly longer progression-free survival (PFS) with osimertinib therapy than those with T790M mutation loss (10.8 vs. 5.0 months, P = 0.045). Among all patients, those with T790M mutation loss in liquid biopsy samples had longer PFS after osimertinib therapy (10.8 vs. 7.5 months, P = 0.209) and postprogression survival (17.7 vs. 9.6 months, P = 0.132) than those with preserved T790M mutation based on liquid biopsies.

Conclusions: NGS using either tissue or liquid biopsy samples from advanced T790M-mutated NSCLC patients with acquired resistance to osimertinib therapy can detect various genomic alternations. Future studies focusing on subsequent tailored therapies on the basis of NGS results are warranted.

Immune checkpoint inhibitors (ICIs) redefined the therapeutics of non-small cell lung cancer (NSCLC), leading to significant survival benefits and unprecedented durable responses. However, the majority of the patients develop resistance to ICIs, either primary or acquired. Establishing a definition of primary resistance to ICIs in different clinical scenarios is challenging and remains a work in progress due to the changing landscape of ICI-based regimens, mainly in the setting of early-stage NSCLC. The mechanisms of primary resistance to ICIs in patients with NSCLC include a plethora of pathways involving a cross-talk of the tumor cells, the tumor microenvironment and the host, leading to the development of an immunosuppressive phenotype. The optimal management of patients with NSCLC following primary resistance to ICIs represents a significant challenge in current thoracic oncology. Research in this field includes exploring other immunotherapeutic approaches, such as cancer vaccines, and investigating novel antibody-drug conjugates in patients with NSCLC.

Background: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC) with EGFR mutations. However, NSCLC heterogeneity leads to differences in efficacy; thus, potential biomarkers need to be explored to predict the prognosis of patients. Recently, the prognostic importance of pre-treatment malnutrition and systemic inflammatory response in cancer patients has received increasing attention.

Methods: In this study, clinical information from 363 NSCLC patients receiving EGFR-TKI treatment at our clinical center was used for analysis.

Results: High nutritional risk index (NRI) and systemic inflammation response index (SIRI) were significantly associated with poor overall survival (OS) and progression-free survival (PFS) in NSCLC patients (P < 0.05). Importantly, NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients and independent OS and PFS predictors. Moreover, a nomogram model was constructed by combining NRI/SIRI, sex, smoking history, EGFR mutation, TNM stage, and surgery treatment to visually and personally predict the 1-, 2-, 3-, 4-, and 5-year OS of patients with NSCLC. Notably, risk stratification based on the nomogram model was better than that based on the TNM stage.

Conclusion: NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients receiving EGFR-TKI treatment, which may be a novel biomarker for supplement risk stratification in NSCLC patients.

Purpose: The objective of this study is to assess the prognostic efficacy of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these ¹⁸F-FDG PET/CT parameters and clinical variables.

Method: A cohort of 678 patients diagnosed with NPC between 2016 and 2020 was analyzed in this study. The model was constructed using four advanced ML algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Least Absolute Shrinkage and Selection Operator (LASSO), and multifactor COX step-up regression. Statistical significance of the models was assessed using Kaplan-Meier (K-M) curves, with a significance level established at P < 0.05. The prognostic efficacy of the models was evaluated through the analysis of receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) serving as a criterion for model selection. The decision curve analysis (DCA) and concordance index (C-index) were employed to assess the precision of the optimal model.

Results: Multivariate analysis revealed age, T stage, and metabolic tumor volume (MTV) for the primary nasopharyngeal tumor (MTVT) as significant independent prognostic factors for overall survival (OS) in NPC patients. Additionally, the LASSO model identified six key variables, including peak standardized uptake value (SUV-peak) for the primary nasopharyngeal tumor (SUV-peak(T)), MTVT, heterogeneity index for neck lymph nodes (HIN), age, pathological type, and T stage. Remarkably, the LASSO model demonstrated superior performance with a 5-year AUC of 0.849 compared to other models. Further assessment using the C-index and DCA confirmed the accuracy of the LASSO model. Subgroup analysis revealed notable risk factors, such as a high heterogeneity index (HI) for the primary nasopharyngeal tumor (HIT), MTV values for neck lymph nodes (MTVN), and HIN.

Conclusions: We developed a novel prognostic machine learning model that integrates ¹⁸F-FDG PET-CT parameters and clinical characteristics, significantly enhancing prognosis prediction in NPC.

Objective: To explore the influence of mindfulness-based stress reduction (MBSR) training on the negative emotions and social functioning of patients with laryngeal cancer post-operation.

Methods: Sixty-five patients with laryngeal cancer admitted to our hospital from January 2017 to December 2019 were selected and divided into an observation group of 33 cases and a control group of 32 cases according to the patient's wishes. The control group received routine intervention, while the observation group received mindfulness decompression training in addition to the control group. Both groups were evaluated after 8 weeks of intervention. The research tools included the self-rating anxiety scale (SAS), self-rating depression scale (SDS), Pittsburgh Sleep Quality Index (PSQI), Social Disability Screening Schedule (SDSS), Social Support Rating Scale (SSRS), and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30), all of the scores of them were used to verify the foregoing scale. The effects of MBSR were evaluated by the differences between the post- and pre-intervention scores in each scale. T-test was used for mean comparison and Pearson test was used for rate comparison χ2 inspection.

Literature review: Patients will have negative emotions during the surgical treatment of laryngeal malignancies (Literature 1), which will affect their mental health (literature 2, 3, 4, 5, 6, 7). Mindfulness decompression training (literature 10, 11) can reduce the depression and anxiety of patients with malignant tumors (literature 14, 15). According to the inclusion criteria and exclusion criteria (literature 16 and 17), two groups of patients were selected in this study, and the scores were obtained using research tools including SAS (literature 19), SDS (literature 20), PSQI (literature 21), SDSS (literature 22) and QLQ-C30 (literature 24 and 25). The effect of MBSR was evaluated by the difference before and after the intervention scores in each scale.

Results: After the intervention, the scores of the SAS and SDS in the two groups were lower than before (P < 0.05), the PSQI score of the two groups was lower than before (P < 0.05), the SDSS score of the two groups was lower than before (P < 0.05), and the scores of the QLQ-C30 in the two groups were higher than before intervention (P < 0.05).

Conclusion: Mindfulness-based stress reduction training can reduce the negative emotions of patients with laryngeal cancer and improve their quality of sleep, social functioning, and quality of life. It is worthy of clinical application.

Purpose: Colorectal cancer is the most common malignancy worldwide. A number of pathological and molecular genetic criteria are currently used as predictors of the disease. They include assessment of MMR deficiency or MSI/MSS status, which among others, determine the immunogenicity of the tumor. In this regard, the evaluation of PD-L1, CTLA-4, and LAG-3 immune checkpoint molecules in different tumor compartments according to MMR status deserves special attention.

Methods: Multiplex immunohistochemistry was used to evaluate the expression of immune checkpoint molecules in the tumor core and at the invasive margin.

Results: Data analysis showed the predominance of PD-L1 (p = 0.011), CTLA-4 (p = 0.004), and LAG-3 (p = 0.013) expression at the invasive margin of dMMR carcinomas compared to pMMR samples. Quantitative analysis of TILs population in the tumor core and at the invasive margin allowed establishment of the predominance of CD3+ and CD8+ lymphocytes at the invasive margin of dMMR carcinomas. Study of the CD163+ macrophages population in the same tumor compartments revealed the predominance of the studied TAMs in the core and at the invasive margin of dMMR carcinomas and the predominance of CD163+ macrophages with PD-L1-phenotype in the tumor stroma.

Conclusion: This study revealed a significant predominance of PD-L1, CTLA-4, LAG-3, and CD 3+ ,CD8+ lymphocytes in dMMR colorectal carcinomas. Further research on the immune landscape in different tumor compartments will likely have high prognostic value for CRC patients, as it might expand the criteria for prescribing immunotherapy.

Introduction: The lung immune prognostic index (LIPI) is a biomarker that combines the lactate dehydrogenase (LDH) value and the derived neutrophil/lymphocyte ratio (dNLR). Its prognostic ability has been reported in non-small cell lung cancer (NSCLC) with immunotherapy. In the context of extensive-stage small cell lung cancer (ES-SCLC) with chemoimmunotherapy, its role remains to be determined.

Methods: A retrospective, multicenter study of patients with ES-SCLC who received atezolizumab plus chemotherapy as first-line treatment was conducted. 101 patients were divided into three groups: LIPI good (n = 33), LIPI intermediate (n = 41), and LIPI poor (n = 27). The Kaplan-Meier method was used for analysis of overall survival (OS) and progression-free survival (PFS), using the log-rank test for comparisons. Univariate and multivariate Cox models were developed to assess the LIPI as an independent predictor of survival.

Results: The good LIPI group had a significantly longer median PFS than the intermediate and poor LIPI groups: 9.6 vs 5.4 vs 5.2 months, respectively (p < 0.001). Significant differences in OS between good, intermediate, and poor LIPI were also observed, with median OS of 23.4 vs 9.8 vs 6.0 months, respectively (p < 0.001). Multivariate Cox regression analysis for PFS identified liver metastases and intermediate and poor LIPI as worse prognostic factors (p < 0.050). For OS, a worse prognosis was confirmed in both the intermediate LIPI group (HR: 2.18, 95% CI: 1.07-4.41, p = 0.031) and the poor LIPI group (HR: 5.40, 95% CI: 2.64-11.07, p < 0.001).

Conclusions: In patients with ES-SCLC treated with chemoimmunotherapy, an intermediate and poor pretreatment LIPI score was associated with worse PFS and OS prognosis.

Purpose: The aim of this study is to investigate the expression of TET3 in prostate cancer and its effect on the efficacy of anti-androgen therapy (ADT).

Methods: The expression of TET3 in 1965 cases of prostate cancer and 493 cases of normal prostate tissues were analyzed. The CIBERSORT algorithm evaluated the abundance of 22 tumor-infiltrating immune cells in 497 prostate cancers. Subsequently, the expression of TET3 in prostate cancer TAMs was analyzed using 21,292 cells from single-cell RNA sequencing (scRNAseq). In addition, the trajectory of the differentiation process was reconstructed based on pseudotime analysis. Sensitivity prediction of prostate cancers to ADT was evaluated based on GDSC2 and CTRP databases. Another dataset GSE111177 was employed for further analysis.

Results: TET3 was over-expressed in prostate cancer, and the expression of TET3 in metastatic prostate cancer was higher than that in non-metastatic prostate cancer. The scRNAseq analysis of prostate cancer showed that TET3 was mainly expressed in TAM. TET3 expressed in early and active TAMs, with the activation of signaling pathways such as energy metabolism, cell communication, and cytokine production. Prostate cancer in TET3 high expression group was more sensitive to ADT drugs such as Bicalutamide and AZD3514, and was also more sensitive to chemotherapy drugs such as Cyclophosphamide, Paclitaxel, and Vincristine, and MAPK pathway inhibitors of Docetaxel and Dabrafenib.

Conclusions: The efficacy of ADT in prostate cancer is related to the expression of TET3 in TAMs, and TET3 may be a potential therapeutic target for coordinating ADT.

Objective: To examine the prevalence of cancer-related cognitive impairment (CRCI) and its contributing factors in patients with nasopharyngeal carcinoma (NPC) and explore the relationship between various assessment methods.

Methods: A cross-sectional study was conducted with 367 patients with NPC between March 2022 and April 2024 at Chongqing University Cancer Hospital. The data gathered from the demographic questionnaire, Montreal Cognitive Assessment (MoCA), Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) were analyzed using logistic regression.

Results: Out of 367 participants, males accounted for 271 (73.84%). There were 217 (59.13%) individuals aged between 35-55 years. Cognitive impairment incidence was 58.04% using MoCA and 47.98% using FACT-Cog. Years of education, work condition, age and time since diagnosis (≥ 11 months) were all significantly associated with cognitive impairment using MoCA, the strongest being time since diagnosis (≥ 11 months) (OR = 2.672, 95% CI = 1.191-5.997, P = 0.017). Gender, marital status (married), place of residence (township), place of residence (city), alcohol history, SAS and SDS were all significantly associated with FACT-Cog, the strongest being marital status (married) (OR = 4.100, 95% CI = 1.130-14.87, P = 0.032).

Conclusion: Patients diagnosed with NPC exhibit susceptibility to CRCI. There was a weak correlation between some aspects of the subjective tests and the objective test scores. Advanced age and disease diagnosis longer than 10 months are associated with a heightened risk of objective cognitive impairment. Furthermore, residing in rural areas, female, married, alcohol history, SAS and SDS increases the likelihood of subjective cognitive impairment. These findings highlight the need to select appropriate assessment scales for different needs and take targeted interventions to address CRCI in patients with NPC.