Prognostic value of translationally controlled tumor protein in colon cancer

The translationally controlled tumor protein (TCTP) is a highly conserved protein involved in a variety of normal cell functions and disease processes. Preclinical studies revealed that TCTP has anti-apoptotic properties, promotes cell growth and division and is involved in cancer progression by promoting invasion and metastasis. The present study explored the potential value of TCTP as a prognostic marker in colon cancer. A retrospective analysis of 74 patients with colon cancer was performed. Using immunohistochemistry, TCTP levels in the primary tumor were assessed semi-quantitatively by the calculation of cytoplasmic and nuclear H-score. Cytoplasmic TCTP levels in the primary tumor had no statistically significant association with disease-free survival (DFS), progression-free survival (PFS) and overall survival (OS) in the present patient population. Patients whose primary tumors had a negative nuclear TCTP expression had significantly improved clinical outcomes. The PFS for the negative nuclear TCTP expression group was 7.7 months [95% confidence interval (CI), 5.8-9.5] compared with 5.5 months (95% CI, 3.2-7.8) in the group with positive nuclear expression (P=0.023, Mantel-Cox log-rank). Patients with a negative nuclear expression of TCTP had a significantly higher median OS (22.2 months; 95% CI, 16.1-28.3) compared with those with positive TCTP nuclear expression (median 13.2 months; 95% CI, 10.1-16.3; P=0.008, Mantel-Cox log-rank). In a multivariate Cox regression model, a positive nuclear TCTP H-score was an independent risk factor for worse PFS and OS. The 1-year OS rate in the group with negative nuclear TCTP expression was 86.3% compared with 56.5% in patients with positive nuclear TCTP expression (P=0.008). The present study suggested that semiquantitative H-score measurement of TCTP levels in the nuclei of tumor cells from the primary tumor is a potential prognostic marker for clinical outcomes in patients with colon cancer.

Circulating Histones to Detect and Monitor the Progression of Cancer

Liquid biopsies have emerged as a minimally invasive cancer detection and monitoring method, which could identify cancer-related alterations in nucleosome or histone levels and modifications in blood, saliva, and urine. Histones, the core component of the nucleosome, are essential for chromatin compaction and gene expression modulation. Increasing evidence suggests that circulating histones and histone complexes, originating from cell death or immune cell activation, could act as promising biomarkers for cancer detection and management. In this review, we provide an overview of circulating histones as a powerful liquid biopsy approach and methods for their detection. We highlight current knowledge on circulating histones in hematologic malignancies and solid cancer, with a focus on their role in cancer dissemination, monitoring, and tumorigenesis. Last, we describe recently developed strategies to identify cancer tissue-of-origin in blood plasma based on nucleosome positioning, inferred from nucleosomal DNA fragmentation footprint, which is independent of the genetic landscape.

Impact of travel burden on overall survival in patients with lung cancer

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Background: High-volume specialized centers are more efficient at managing patients with lung cancer than low-volume centers. Centralization of cancer treatment has the potential to improve patient outcomes and quality of treatment. However, the growing centralization also increases patient’s travel burden (measured as travel distance or travel time) and may negatively impact access to specialist services. The aim of our study was to evaluate the potential impact of travel burden on clinical outcomes in patients with lung cancer. Methods: A retrospective analysis of a single Bulgarian center was performed. A total of 9240 lung cancer patients treated between 2005-2020 were included in the study. Travel distance between patients’ city of residence and the treating facility was calculated with an online tool to determine the shortest route for travel using the existing road network. The mean of travel time values for every workday of the week was calculated to control for daily changes in typical traffic. The probability of survival was estimated using the Kaplan-Meier method and differences in survival in each subgroup were evaluated with a log-rank test. Results: About one third of all included patients were living in the same city as the treating facility (n = 2746, 29.7%). The medians for travel distance and travel time were used to stratify patients into subgroups. According to travel distance the patients were grouped into three strata – same city, < 50 km and ≥ 50 km. A cut-off of 60 min was used to stratify patients into three groups by travel time – same city, < 60 min and ≥ 60 min. Overall survival in our patient population was significantly lower with increasing travel distance (p < 0.001, Mantel-Cox log rank) and travel time (p < 0.001, Mantel-Cox log rank). The 1-year OS rate according to travel distance was 27.1% in the same city group, 22.4% in < 50 km group and 20.5% in ≥ 50 km group (p < 0.001). The corresponding values for the 5-year OS rate were: 2.9%, 2.6% and 1.4% (p < 0.001). Conclusions: In this retrospective study we discovered significant differences in overall survival of patients with lung cancer depending on travel distance and travel time to the treating oncological facility. Despite having similar clinical and pathological characteristics (age, sex, stage at initial diagnosis, histologic subtype), the median overall survival was significantly lower in those subgroups of patients with a higher travel burden. [Table: see text]

Impact of travel burden on clinical outcomes in lung cancer

PURPOSE

Our study explores the influence of travel burden (measured as travel distance and travel time) on clinical outcomes in lung cancer patients.

METHODS

A retrospective analysis of a single Bulgarian center was performed. A total of 9240 lung cancer patients were included in the study. Travel distance and travel time between patients' city of residence and the treating facility were calculated with an online tool to determine the shortest route for travel using the existing road network. The probability of survival was estimated using the Kaplan-Meier method, and differences in survival in each subgroup were evaluated with a log-rank test.

RESULTS

About one third of all included patients were living in the same city as the treating facility (n = 2746, 29.7%). Overall survival in our patient population was significantly lower with increasing travel distance (p < 0.001, Mantel-Cox log rank) and travel time (p < 0.001, Mantel-Cox log rank). The 1-year OS rate according to travel distance was 27.1% in the same city group, 22.4% in < 50-km group, and 20.5% in ≥ 50-km group (p < 0.001). The corresponding values for the 5-year OS rate were 2.9%, 2.6%, and 1.4% (p < 0.001).

CONCLUSION

In this retrospective study, we discovered significant differences in the overall survival of patients with lung cancer depending on travel distance and travel time to the treating oncological facility. Despite having similar clinical and pathological characteristics (age, sex, stage at initial diagnosis, histologic subtype), the median overall survival was significantly lower in those subgroups of patients with a higher travel burden.