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Objective: To investigate the clinical features and prognostic implications of different subtypes of cervical adenocarcinoma.

Methods: We examined 13,353 adenocarcinoma (AC) cases from the SEER database to identify distinct clinical characteristics and prognostic factors among various histological subtypes. Using the WHO classification and International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) codes, we categorized patients and assessed overall survival (OS) and cancer-specific survival (CSS) via Kaplan-Meier and Cox regression analyses. A nomogram was constructed to predict patient survival across subtypes.

Results: Patients with non-usual type show a significantly poorer prognosis. Our analysis revealed that serous carcinoma patients had the most adverse outcomes (OS: hazard ratio (HR) = 2.69, 95% confidence interval (CI): 2.23-3.23, P < 0.001; CSS: HR = 1.78, 95% CI: 1.34-2.36, P < 0.001), while villous adenocarcinoma patients had the most favorable (OS: HR = 0.43, 95% CI: 0.29-0.65, P < 0.001; CSS: HR = 0.32, 95% CI: 0.17-0.60, P < 0.001), compared to the usual type. Multivariable Cox regression identified age, marital status, race, tumor grade, FIGO stage, and treatment as independent prognostic factors. In patients with serous carcinoma, advanced FIGO stage was a risk factor (stage IV vs stage I: HR = 4.06, 95% CI: 1.35-12.22, P = 0.013), and surgery was a protective factor (HR = 0.22, 95% CI: 0.10-0.49, P < 0.001). We also created a prognostic model incorporating diverse histological subtypes, internally validated for high predictive accuracy and discrimination via the receiver operating characteristic (ROC) curve and calibration plots.

Conclusion: Clinical characteristics and prognostic features in cervical adenocarcinoma vary significantly by histological subtype, with serous carcinoma being associated with the worst outcomes.

Purpose: Most patients with cancer do not participate in a clinical trial. Understanding clinical participation rates, and the barriers and motivators that influence participation may help identify opportunities for improvement in accrual.

Methods: A cross-sectional analysis of cancer survivors was conducted using the Health Information National Trends Survey (HINTS) administered in 2020. Primary outcome was clinical trial participation amongst patients with cancer. Secondary outcomes were motivators and barriers to influence clinical trial participation. Logistic regression was employed to assess the association of clinical trials being discussed as a cancer treatment option with social determinants.

Results: Six hundred and eighteen respondents (weighted population estimate 22,723,047) with a self-reported history of cancer were included. Overall, 15.7% reported an invitation to participate in a clinical trial, of which 37.8% participated. Clinical trials were discussed as a cancer treatment option amongst 13.5% of respondents. Knowledge of clinical trials was low (9.3%). Reported motivators included trying new care (72.3%), wanting to get better (88.9%), getting paid (40.1%), helping other people (73.0%), and encouragement from the doctor (73.7%) or family/friends (59.5%). Reported barriers included getting transportation, childcare or paid time off work (42.4%), and standard care not covered by insurance (69.6%). Race (Other, OR 3.84) and income (<$35k, OR 5.84) were associated with discussion of clinical trials as a cancer treatment option.

Conclusion: Clinical trial treatment discussion, invitation, and participation are low among patients with a history of cancer. Although the study identified multiple motivators and barriers to participation, improvement in the rates of discussion and invitation to participate in a clinical trial are required. Nevertheless, addressing the identified barriers and motivators that influence clinical trial participation may be a strategy to optimize patient enrollment.

To improve precision medicine in breast cancer (BC) decision-making, radio-genomics is an emerging branch of artificial intelligence (AI) that links cancer characteristics assessed radiologically with the histopathology and genomic properties of the tumour. By employing MRIs, mammograms, and ultrasounds to uncover distinctive radiomics traits that potentially predict genomic abnormalities, this review attempts to find literature that links AI-based models with the genetic mutations discovered in BC patients. The review's findings can be used to create AI-based population models for low and middle-income countries (LMIC) and evaluate how well they predict outcomes for our cohort.Magnetic resonance imaging (MRI) appears to be the modality employed most frequently to research radio-genomics in BC patients in our systemic analysis. According to the papers we analysed, genetic markers and mutations linked to imaging traits, such as tumour size, shape, enhancing patterns, as well as clinical outcomes of treatment response, disease progression, and survival, can be identified by employing AI. The use of radio-genomics can help LMICs get through some of the barriers that keep the general population from having access to high-quality cancer care, thereby improving the health outcomes for BC patients in these regions. It is imperative to ensure that emerging technologies are used responsibly, in a way that is accessible to and affordable for all patients, regardless of their socio-economic condition.

Objective: Mutations in the gene encoding isocitrate dehydrogenase 1 (IDH1) occur in approximately 6-10% of acute myeloid leukemia (AML) patients. Ivosidenib (IVO) is a small-molecule inhibitor of mutant IDH1. This study delves into the mechanism of IVO with hypomethylating agents (HMAs) (azacitidine or decitabine) for treating IDH1-mutated AML through the PI3K/AKT pathway.

Methods: IDH1^R132H-mutated MOLM-13 (IDH1^R132H-MOLM-13) cells were constructed. The effects of the drugs, both individually and in combination, on IDH1^R132H-MOLM-13 cell proliferation and apoptosis were assessed using 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide and flow cytometry, with combination index (CI) values calculated using CompuSyn software. IDH1, DNMT1, PI3K and AKT gene mRNA levels, and the PI3K/AKT pathway- and histone lysine methylation-related protein levels in IDH1^R132H-MOLM-13 cells were determined by RT-qPCR and Western blot.

Results: IDH1^R132H-mutated MOLM-13 cells (IDH1^R132H-MOLM-13) were successfully constructed. The IDH1 inhibitor, either as a monotherapy or combined with HMAs, effectively inhibited IDH1^R132H-MOLM-13 cell proliferation, and the combination therapy exhibited synergistic effects (CI < 1). The combination therapy increased cell proportion in the G2/M phase and apoptotic rate. Both treatment modalities reduced IDH1, DNMT1, PI3K and AKT mRNA levels and histone lysine methylation levels (H3K4me3, H3K9me3, H3K27me3); besides, PI3K and AKT phosphorylation levels were reduced, with the reductions being more significant in cells undergoing combination therapy. The indexes did not differ significantly between cells undergoing the two modalities of combined treatments.

Conclusion: The IDH1 inhibitor with HMAs suppressed IDH1^R132H-MOLM-13 cell proliferation and viability and decreased the methylation level by repressing the phosphorylation of the PI3K/AKT pathway, showing a synergistic inhibitory effect.

Background: Overexpression of Aurora B is linked to poor prognosis in various malignancies; however, its prognostic role remains debatable. Conducting a meta-analysis is essential to reach a definitive conclusion.

Methods: Various databases were searched. Aurora B protein expression was assessed for prognostic significance using pooled hazard ratio (HR) with a 95% confidence interval (CI). Meta-regression and subgroup analysis identified the source of heterogeneity.

Results: The study comprised 1384 cancer patients from 10 articles. The result with multivariate data (pooled HR=1.18, 95% CI= 0.71-1.95, p=0.52, I²=83%) and univariate data (pooled HR=1.81, 95% CI=0.92, 3.57, p=0.09, I²=89%) showed that increased Aurora B expression was not linked with poor overall survival (OS). Subgroup analysis showed that sample size, follow-up time, cut-off value, non-Chinese patients, antibody source were not associated with unfavorable OS.

Conclusions: Aurora B expression could not be used as a prognostic marker in cancer.

Objective: We aimed to explore the application effects of humanistic nursing combined with Neuman's nursing in oncology patients.

Methods: One hundred oncology patients were randomly divided into the observation and control groups, with 50 patients in each. Comparisons were made between both groups in terms of SF-36 scores, treatment compliance, nursing quality scores, Self-Rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS) scores, and Pittsburgh Sleep Quality Index (PSQI) scores.

Results: The observation group showed higher scores in the physical domain, physiological function, material life, and overall health of the SF-36 scale (P < 0.05). The observation group also exhibited higher treatment compliance rate (X² = 9.470), and higher scores in nurse-patient communication, nursing system, nursing service, and nursing environment of the nursing quality assessment (P < 0.05). After nursing, the observation group performed lower SAS and SDS scores (t = 17.556, 10.004), and higher scores in sleep quality, sleep duration, sleep disturbance, sleep onset latency, sleep efficiency, hypnotic medication use, and daytime dysfunction based on the PSQI (P < 0.05).

Conclusion: The combination of humanistic nursing and Neuman's nursing improves the quality of life and treatment compliance in oncology patients, with improvements in negative emotions and sleep quality. However, this study's small sample of 100 cancer patients may not fully represent the diverse characteristics of various cancer types and stages, limiting conclusion generalizability. Furthermore, the short duration may have missed later-stage nursing intervention impacts. Thus, large-scale, long-term research is needed to provide reliable clinical evidence.

Objective: To identify outcome differences between extended nodal radiotherapy (ENRT) with simultaneous integrated boost (SIB) and stereotactic body radiotherapy (SBRT), performed with advanced radiotherapy techniques, both of which were 18F-Fluoro-Deoxy-Glucose (FDG) PET/CT guided, for lymph-node (LN) relapses of gynecological tumors, and to identify the most important determining factors.

Methods: Records of gynecologic patients treated in a single-institution with FDG PET/CT guided intensity-modulated radiotherapy (IMRT), image-guided radiotherapy (IGRT), or SBRT, were reviewed, and only patients at first salvage radiotherapy for LN relapses were considered. Local relapse-free- (LRFS), regional relapse-free- (RRFS), distant metastasis-free- (DMFS), disease-free-(DFS) and overall-survival (OS), as well as acute and late toxicity (with CTCAE v5.0 score), were determined.

Results: Fifty-eight patients (23 ENRT+SIB; 35 SBRT) treated for 178 LNs from February 2007-April 2023, were identified. Median biological equivalent dose (BED10) delivered to PET-positive LNs was 76.5 Gy (Interquartile range-IQR- 74.4;78.7) for ENRT, and 72 Gy (IQR 59.5;75.6) for SBRT. Median follow-up was 81.1(IQR 48.5; 117.2) and 37.0 (IQR 21.3; 58.4) months for ENRT and SBRT, respectively. Thirty-six-month estimated LRFS was 90.2% for ENRT and 82.6% for SBRT; RRFS was 69% and 63.4%, DMFS 26.1% and 44.3%, and OS 73.7% and 60.4%; no statistically significant differences were found between the two groups (logrank test, p= 0.29). ENRT recorded more acute (p⩽0.033), but not late, toxicities.

Conclusions: ENRT+SIB and SBRT for gynecological LN tumor relapses obtain similar results in terms of disease-free and OS, with fair toxicity. Prospective studies with higher patient numbers are needed.

Background: The clinical significance of fibroblast growth factor receptors (FGFRs) and their ligands in hepatocellular carcinoma (HCC) is extensively studied. Recently, regulation of voltage-gated sodium channels by FGFs in cancer has been reported.

Materials and methods: We investigated the relationship between FGF family genes and voltage-gated sodium channel genes (SCN) using three independent microarray and RNA-seq cohorts HCC patients. In vitro validation of 100 tissues of HCC patients with 50 control samples was performed. Statistical validation included the Wilcoxon test, Mann-Whitney U-test, correlation, Kaplan-Meier survival, and univariate and multivariate Cox regression survival analyses.

Result: The initial analysis of intracrine FGF (iFGF) ligands showed dysregulation of iFGF genes in HCC with strong association with each other in all datasets. According to in vitro analysis, overexpression of FGF14 was also observed in HCC patients suggesting potential role of FGF14 in HCC.Furthermore, network analysis showed that FGF14 was strongly interacting with SCN genes. Interestingly, SCN genes were also found in HCC samples with a positive correlation with FGF14 expression. The clinical analysis showed that FGF14, SCN2A and SCN11A are significantly associated with better disease-free survival, whereas multivariate regression analysis showed SCN11A as an independent predictor of disease-free survival in HCC patients.

Conclusion: The dysregulation of FGF14 and SCN family genes suggests a new molecular mechanism in the regulation of HCC. Furthermore, SCN11A was identified as a possible predictor for disease-free survival in HCC. Investigating these gene families using clinical studies may lead to new therapeutic approaches for HCC treatment.

Objective: The Clinical Trials Regulation EU 536/2014 (CTR) has presented challenges for adapting experimental centres. To address this regulatory change, in 2023, the Italian Sarcoma Group (ISG) established a Federated Trial Centre (FTC) model, including Clinical Research Coordinators (CRCs) and Research Nurses (RNs).

Methods: To explore the CTR's impact, a 40-question survey was launched in April 2023, distributed among 48 FTC members from 27 Italian institutions, with 30 responding.

Results: 46.6% of responders reported the progress of their institutions in adapting to the regulation, 70% had good knowledge of the updates, 60% confirmed staff training on the CTIS (Clinical Trials Information System). However, 63.3% noted that administrative personnel were not aligned with new contract deadlines, and only in 26.6% of cases institutions offered CTR-specific training. Additionally, 53.4% expressed concerns that the CTR does not support academic research.

Conclusion: The ISG's FTC model was assessed as promoting collaboration between clinicians, staff, and CRCs to improve the management of academic studies and raise awareness within the sarcoma research community, by defining roles for CRCs and RNs and proposing collaborative projects and meetings.