BMC Cancer最新文献

Background: We developed a prognostic model to evaluate the overall survival (OS) and progression-free survival (PFS) of patients with unresectable hepatocellular carcinoma (u-HCC) treated with Hepatic arterial infusion chemotherapy of infusion oxaliplatin, fluorouracil and leucovorin (FOLFOX-HAIC).

Methods: This model was based on a retrospective study of u-HCC patients treated with the FOLFOX-HAIC (oxaliplatin 130 mg/m², leucovorin 400 mg/m², fluorouracil bolus 400 mg/m² on day 1, and fluorouracil infusion 2,400 mg/m² for 23-46 h, once every 3-4 weeks). We divided the patients into a training cohort and a validation cohort, used LASSO regression construct prognostic models, predict patient's OS and PFS based on nomograms of models. Patients were divided into high-risk, medium-risk, and low-risk groups according to their respective model risk scores. Kaplan-Meier survival analysis was used to assess the survival time between the three patient cohorts.

Results: A total of 333 patients were enrolled in the study and divided into a training cohort and a verification cohort at a ratio of 7:3 (233 in the training cohort and 100 in the validation cohort). The prognostic model we established contained nine prognostic variables. The results of concordance index (C-index) of the OS and PFS prognostic model was 0.75 and 0.71, respectively, higher than that of the TNM staging (0.57 and 0.55, p < 0.001), time-dependent ROC (td-ROC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) also showed that the model was better than the TNM staging for u-HCC predicting OS and PFS. Subsequently, the model was used to develop a nomogram to predict the individualized prognosis of patients with u-HCC treated with the FOLFOX-HAIC, with a higher net benefit than the TMN staging. According to the risk score, patients were divided into a low-risk group (risk score ≤ 0.458), the medium-risk group (risk score: 0.458-0.799) and the high-risk group (risk score > 0.799). There were significant differences in the OS and PFS between the three groups.

Conclusions: The model developed by our team enables risk stratification and personalized prognosis assessment for u-HCC patients undergoing FOLFOX-HAIC treatment, exhibiting superior predictive accuracy and discriminative capability compared to TNM staging.

Background: Cutaneous melanoma (CM) is strongly associated with ultraviolet (UV) radiation, which contributes to the transformation of melanocytes into melanoma by inducing specific DNA damage. Here, we investigated the causal relationship between CM and genes related to sun-damaged skin, exploring specific target genes through various bioinformatics analyses.

Methods: The Gene Expression Omnibus (GEO) database was used to obtain differential genes for CM and normal skin, and the Genome-Wide Association Studies (GWAS) analysis offered summary-level melanoma data for CM. Mendelian randomization (MR) analyses were used to examine the correlated linkage between CM and sun-exposed skin genes. The MR studies were conducted mainly using Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, simple and weighted patterns to predict the correlation between sun-exposed skin and CM. Finally, the role of target genes in CM was revealed by pan-cancer analysis, expression and immune-infiltration evaluations, immuno-checking targeting analysis, immunotherapy response analysis, survival analysis, and protein-protein interactions (PPI) network and enrichment analyses.

Result: Using matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. MR analysis indicated that only CTSS has a deleterious effect linking skin exposure to sunlight and CM. Analysis of CTSS expression in tumors and tissues, along with the construction of a prognostic model, revealed that CTSS expression was higher in both primary CM and metastatic CM compared to normal skin tissue. However, patients with higher CTSS expression had a higher prognosis. In addition, high CTSS expression was significantly and positively correlated with tumor mutation rate, tumor microenvironment, immune cell infiltration, immune checkpoints and immunotherapy efficacy.

Conclusion: Using MR analysis, we found a positive causal relationship between the CTSS gene in sun-exposed skin and CM. Additionally, increased CTSS may provide a basis for biomarker prediction of CM prognosis, immune status and immunotherapy.

Background: Pancreatic cancer (PDAC: pancreatic ductal adenocarcinoma, the commonest form), a lethal disease, is best treated with surgical excision but is feasible in less than a fifth of patients. Around a third of patients presentlocally advanced, inoperable, non-metastatic (laPDAC), whose stadrd of care is palliative chemotherapy; a small minority are down-sized sufficiently to enable surgical excision. We propose a phase II clinical trial to test whether a combination of standard chemotherapy (gemcitabine & nab-Paclitaxel: GEM-NABP) and repurposing All Trans Retinoic Acid (ATRA) to target the stroma may extend progression-free survival and enable successful surgical resection for patients with laPDAC, since data from phase IB clinical trial demonstrate safety of GEM-NABP-ATRA combination to patients with advanced PDAC with potential therapeutic benefit.

Methods: Patients with laPDAC will receive at least six cycles of GEM-NABP with 1:1 randomisation to receive this with or without ATRA to assess response, until progression or intolerance. Those with stable/responding disease may undergo surgical resection. Primary endpoint is progression free survival (PFS) defined as the time from the date of randomisation to the date of first documented tumour progression (response evaluation criteria in solid tumours [RECIST] v1.1) or death from any cause, whichever occurs first. Secondary endpoints include objective response rate (ORR), overall survival (OS), safety and tolerability, surgical resection rate, R0 surgical resection rate and patient reported outcome measures (PROMS) as measured by questionnaire EQ-5D-5L. Exploratory endpoints include a decrease or increase in CA19-9 and serum Vitamin A over time correlated with ORR, PFS, and OS.

Discussion: STARPAC2 aims to assess the role of stromal targeting in laPDAC.

Trial registration: EudraCT: 2019-004231-23; NCT04241276; ISRCTN11503604.

Background: Patients need to be supported in combining treatment with daily life. However, measurement of supportive care indicators related to treatment-related side effects is under-reported. This review aimed to identify a list of quality indicators for managing cancer treatment-induced toxicities for adult patients with cancer.

Methods: A review was conducted on PubMed, the Cumulative Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and Embase from September 26, 2013 to December 26, 2023. Published English articles that developed or analyzed quality indicators of managing cancer treatment-induced toxicities for adult patients with cancer were selected. The identified indicators were classified according to Donabedian's model for quality of care in healthcare.

Results: Forty-two indicators (4 structural, 27 process, and 11 outcome indicators) in 18 articles were identified. Eight articles (44.4%) were from North America, four (22.2%) from Europe, two (11.1%) from Oceania, two (11.1%) from Asia, and one (5.6%) from Africa; 64.3% of the indicators were process indicators based on guidelines. The prevalence of patient symptoms determined using a patient-reported outcome measure was proposed as an outcome indicator. In seven studies (38.9%), these indicators were selected by multidisciplinary experts. None of the studies involved patients or family members in the indicator selection process.

Conclusion: The quality of supportive care should be improved by measuring these indicators, considering the patient's needs for supportive care at each hospital such that patients can continue their lives while undergoing treatment.

Esophageal cancer is a grave malignant condition. While radiotherapy, often in conjunction with chemotherapy, serves as a cornerstone in the management of locally advanced or metastatic cases, patient tolerance and treatment resistance frequently hinder its efficacy. Cell-in-cell structures, prevalent in various tumors, have been linked to prognosis. Hence, investigating the prognostic significance and regulatory mechanisms of genes related to these intracellular structures in esophageal cancer is imperative. The Cancer Genome Atlas (TCGA) Esophageal Cancer (ESCA) dataset served as the training set for the analysis. Differentially expressed genes (DEGs) in ESCA samples were identified, with those related to intercellular structures designated cell-in-cell-related differential expression genes (CIC-related DEGs). Cox regression analysis was employed to identify prognostic genes, categorizing samples into high- and low-risk groups based on median risk scores. Validation was conducted using the GSE53624 risk model. Established methodologies included morphological mapping, enrichment analysis, immune infiltration analysis, prognostic gene expression validation, molecular docking, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) validation. Thirty-eight intersecting genes were identified between the disease and normal groups in ESCA samples. Stepwise multivariate Cox analysis pinpointed three prognostic genes: androgen receptor (AR), C-X-C motif chemokine ligand 8 (CXCL8), and epidermal growth factor receptor (EGFR). The risk model's applicability was confirmed in the GSE53624 dataset, revealing eight significantly different immune-related gene sets. Prognostic gene expression validation demonstrated significant differences between the disease and normal groups in both datasets. The proteins corresponding to the three prognostic genes interacted with gefitinib and osimertinib. RT-PCR results corroborated the differential expression of prognostic genes in esophageal cancer tissues. This study identified AR, CXCL8, and EGFR as prognostic genes and demonstrated their molecular interactions with gefitinib and osimertinib, providing a foundation for ESCA diagnosis and treatment.

Introduction: Colorectal cancer is a significant cause of mortality globally, with several factors impacting patient outcomes, including access to healthcare, early detection, and treatment. Despite this, the specific factors affecting incidence of death among colorectal cancer patients in the Amhara region have not been thoroughly investigated. Thus, this study seeks to assess incidence and determinants of mortality among colorectal cancer patients in Amhara Region oncology centers.

Results: The mean age of the participants was 48.6 years (SD ± 15). Median survival time was 23.8 months. The overall incidence rate or incidence density of a colorectal cancer mortality rate was 2.9 per 100 person-months (95% CI: 2.5-3.4). Survival rates of colorectal cancer patients 1and 5 year was 69.78% and 16.1%, respectively. The result of the multivariable analysis showed that colorectal cancer patients who had presenting symptoms [AHR = 2.67 (95% CI: 1.95, 3.67)], Base line HGB level < 12.5 mg/dl [AHR = 1.63 (95% CI: 1.12, 2.37)], WHO or ECOG poor performance status [AHR = 2.99 (95% CI: 2.17, 4.12), late stage of cancer [AHR = 2.32 (95% CI: 1.42, 3.79)] and location of tumor on colorectal [AHR = 1.76 (95% CI: 1.20, 2.55)] were significantly associated with mortality of colorectal cancer.

Conclusion and recommendation: The study highlights significant findings on the survival and mortality of colorectal cancer patients. The overall mortality rate was 2.9 per 100 person-months. Multivariable analysis identified presenting symptoms, low baseline hemoglobin levels, poor performance status, late-stage cancer, and tumor location as significant predictors of mortality. Highlighting the need for early detection and targeted care strategies.

Background: As a member of the tumor necrosis factor (TNF) superfamily, tumor necrosis factor superfamily member 4 (TNFSF4) is expressed on antigen-presenting cells and activated T cells by binding to its receptor TNFRSF4. However, tumorigenicity of TNFSF4 has not been studied in pan-cancer. Therefore, comprehensive bioinformatics analysis of pan-cancer was performed to determine the mechanisms through which TNFSF4 regulates tumorigenesis.

Methods: RNA-seq data for 33 cancers were analyzed from UCSC XENA database. Online websites and databases were used to investigate TNFSF4's biological function, epigenetic modifications, genetic alterations, and tumor immunity. Furthermore, cell phenotype experiment and tumor xenotransplantation experiment were performed to determine the biological functions of TNFSF4.

Results: The pan-cancer analysis showed that TNFSF4 was upregulated in several tumors. Significant relationships between TNFSF4 expression and single-cells data were also observed in numerous cancer types. TNFSF4 expression correlated with the expression of immune checkpoint genes and could influence various drug sensitivity. Vitro and vivo experiments showed that TNFSF4 could promote the development and progression of Hepatocellular Carcinoma (HCC).

Conclusions: TNFSF4 was upregulated in multiple cancer types and promoted the development and progression of cancers through several mechanisms including regulation of the tumor-infiltration of immune cells. Our study shows that TNFSF4 is a promising prognostic and immunotherapeutic biomarker in some malignant tumors.

Background: Cancer is a complex set of diseases, and many have decades-long lag times between possible exposure and diagnosis. Environmental exposures, such as per- and poly-fluoroalkyl substances (PFAS) and area-level risk factors (e.g., socioeconomic variables), vary for people over time and space. Evidence suggests PFAS exposure is associated with several cancers; however, studies to date have various limitations. Few studies have used rigorous spatiotemporal approaches, and, to our knowledge, none have assessed cumulative exposures given residential histories or incorporated chemical mixture modeling. Thus, spatiotemporal analysis using advanced statistical approaches, accounting for spatially structured and unstructured heterogeneity in risk, can be a highly informative strategy for addressing the potential health effects of PFAS exposure.

Methods: Using population-based incident cancer cases and cancer-free controls in a 12-county area of southeastern Pennsylvania, we will apply Bayesian spatiotemporal analysis methods using historically reconstructed PFAS-contaminated water exposure given residential histories, and other potential cancer determinants over time. Bayesian group index models enable assessment of various mixtures of highly correlated PFAS chemical exposures incorporating mobility/residential history, and contextual factors to determine the association of PFAS-related exposures and cancer incidence.

Discussion: The purpose of this paper is to describe the Enhanced PFAS Spatial Analysis study rationale, study design, and methods.

The pro-tumor effects of mast cell (MC) in the tumor microenvironment (TME) are becoming increasingly clear. Recently, MC were shown to contribute to tumor malignancy by supporting the migration of tumor-associated macrophages (TAMs), suggesting a relationship with tumor immunity. In the current study, we aimed to examine the correlation between MC infiltration and neoadjuvant chemoradiotherapy (nCRT) response for locally advanced rectal cancer (LARC). Ninety-five LARC patients who recieved nCRT were enrolled in this study. Protein levels of the MC marker tryptase and TAM marker CD206 were evaluated with immunohistochemistry (IHC). The correlation between MC infiltration and prognostic factors was evaluated. The effects of MCs on the malignant potential were examined using in vitro proliferation and invasion assays with a colorectal cancer (CRC) cell line (HCT-116). Following nCRT, 31.6% of resected LARC patient specimens were positive for MC infiltration by tryptase IHC analysis. MC infiltration was significantly correlated with nCRT response. The 5-year disease-free survival (DFS) rate was significantly lower in the MC-positive group compared with the MC-negative group (52.3% vs. 76.8%). Univariate and multivariate analyses revealed that MC infiltration was the independent prognostic indicator for DFS. MC infiltration was significantly correlated with CD206 expression, and therefore TAMs. In vitro experiments suggested that tumor activated mast cells could promote CRC cell malignant behavior via production of macrophage inhibitory factor. MC infiltration in LARC patients was positively correlated with TAM infiltration and resistance to nCRT, and was also an independent poor prognostic indicator.