Search Results (8)

Backgrounds: The incidence of gastrointestinal cancers (GICs), though decreased in recent years, still accounts for 35% of all cancer-related mortality. The proper identification of risk factors, early diagnosis, and therapy optimization represent the three cornerstones of GIC treatment. In four-stage diseases, chemotherapy embodies target therapy that may prolong patients’ expectancy when suitably applied. Patients and Methods: There were 133 (82 (62%) male and 51 (38%) female) consecutive patients with a median age of 70 (64–74) years who underwent palliative treatment due to four-stage colorectal cancer (CRC) between 2022 and 2024. The demographic, clinical, and laboratory data and applied chemotherapeutic protocols were evaluated regarding the response to applied therapy, resulting in complete or partial tumor regression. The advancement of the tumor was based on computed tomography (CT) performed before and 6 months after the chemotherapy. Results: The multivariable model revealed red cell distribution width (RDW) from peripheral blood analysis (OR: 0.81, 95% CI: 0.65–1.00, p = 0.049) as a possible predictor for systemic treatment response in colorectal cancer. The receiver operating characteristic curve revealed a predictive value of male sex and RDW prior to systemic therapy, with an area under the curve of 0.672, yielding a sensitivity of 70.0% and specificity of 58.1%. Conclusions: The results of our analysis point out the possible modulatory impact of RDW on six-month systemic therapy in colorectal terminal cancer management. Further studies are required to confirm the presented results. Full article

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO–Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan–Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients’ response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy. Full article

Butyrate, one of the major products of the gut microbiota, has played notable roles in diverse therapies for multiple tumors. Our study aimed to determine the roles of genes that modulate butyrate metabolism (BM) in predicting the clinical prognosis and responses to systemic therapies in hepatocellular carcinoma (HCC). The genes modulating BM were available from the GeneCard database, and gene expression and clinical information were obtained from TCGA-LIHC, GEO, ICGC-JP, and CCLE databases. Candidate genes from these genes that regulate BM were then identified by univariate Cox analysis. According to candidate genes, the patients in TCGA were grouped into distinct subtypes. Moreover, BM- related gene signature (BMGs) was created via the LASSO Cox algorithm. The roles of BMGs in identifying high-risk patients of HCC, assessing the prognoses, and predicting systematic therapies were determined in various datasets. The statistical analyses were fulfilled with R 4.1.3, GraphPad Prism 8.0 and Perl 5.30.0.1 software. In the TCGA cohort, most butyrate-related genes were over-expressed in the B cluster, and patients in the B cluster showed worse prognoses. BMGs constructed by LASSO were composed of eight genes. BMGs exhibited a strong performance in evaluating the prognoses of HCC patients in various datasets, which may be superior to 33 published biomarkers. Furthermore, BMGs may contribute to the early surveillance of HCC, and BMGs could play active roles in assessing the effectiveness of immunotherapy, TACE, ablation therapy, and chemotherapeutic drugs for HCC. BMGs may be served as novel promising biomarkers for early identifying high-risk groups of HCC, as well as assessing prognoses, drug sensitivity, and the responses to immunotherapy, TACE, and ablation therapy in patients with HCC. Full article

Necroptosis is a type of programmed necrosis that is different from apoptosis and necrosis. Lung cancer has the highest incidence and mortality worldwide, and lung adenocarcinoma is the most common subtype of lung cancer. However, the role of necroptosis in the occurrence and development of LUAD remains largely unexplored. In this paper, four NRGs and nine NRGs determined by big data analysis were used to effectively predict the risk of early LUAD (AUC = 0.994) and evaluate the prognostic effect on LUAD patients (AUC = 0.826). Meanwhile, ESTIMATE, single-sample gene set enrichment analysis (ssGSEA), genomic variation analysis (GSVA), gene set enrichment analysis (GSEA), and immune checkpoint analysis were used to explore the enrichment characteristics and immune research related to the prognostic model. In deep data mining, we were surprised to find that prognostic models also regulate the immune microenvironment, cell cycle, and DNA damage repair mechanisms. Thus, we demonstrated a significant correlation between model evaluation results, ICI treatment, and chemotherapeutic drug sensitivity. The low-risk population has a stronger tumor immune response, and the potential for ICI treatment is greater. People at high risk respond less to immunotherapy but respond well to chemotherapy drugs. In addition, PANX1, a core gene with important value in immune regulation, prognosis assessment, and early diagnosis, has been identified for the first time, which provides a new target for the immunotherapy of LUAD as well as a new theoretical basis for the basic research, clinical diagnosis, and individualized treatment of LUAD. Full article

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP^® Global Profiling and MxP^® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC. Full article

Surface-exposed calreticulin (ecto-CRT) plays a crucial role in the phagocytic removal of apoptotic cells during immunotherapy. Ecto-CRT is an immunogenic signal induced in response to treatment with chemotherapeutic agents such as doxorubicin (DOX) and mitoxantrone (MTX), and two peptides (KLGFFKR (Integrin-α) and GQPMYGQPMY (CRT binding peptide 1, Hep-I)) are known to specifically bind CRT. To engineer CRT-specific monobodies as agents to detect immunogenic cell death (ICD), we fused these peptide sequences at the binding loops (BC and FG) of human fibronectin domain III (FN3). CRT-specific monobodies were purified from E. coli by affinity chromatography. Using these monobodies, ecto-CRT was evaluated in vitro, in cultured cancer cell lines (CT-26, MC-38, HeLa, and MDA-MB-231), or in mice after anticancer drug treatment. Monobodies with both peptide sequences (CRT3 and CRT4) showed higher binding to ecto-CRT than those with a single peptide sequence. The binding affinity of the Rluc8 fusion protein–engineered monobodies (CRT3-Rluc8 and CRT4-Rluc8) to CRT was about 8 nM, and the half-life in serum and tumor tissue was about 12 h. By flow cytometry and confocal immunofluorescence of cancer cell lines, and by in vivo optical bioluminescence imaging of tumor-bearing mice, CRT3-Rluc8 and CRT4-Rluc8 bound specifically to ecto-CRT and effectively detected pre-apoptotic cells after treatment with ICD-inducing agents (DOX and MTX) but not a non-ICD-inducing agent (gemcitabine). Using CRT-specific monobodies, it is possible to detect ecto-CRT induction in cancer cells in response to drug exposure. This technique may be used to predict the therapeutic efficiency of chemo- and immuno-therapeutics early during anticancer treatment. Full article

Circulating tumour DNAs and non-coding RNAs present in body fluids have been under investigation as tools for cancer diagnosis, disease monitoring, and prognosis for many years. These so-called liquid biopsies offer the opportunity to obtain information about the molecular make-up of a cancer in a minimal invasive way and offer the possibility to implement theranostics for precision oncology. Furthermore, liquid biopsies could overcome the limitations of tissue biopsies in capturing the complexity of tumour heterogeneity within the primary cancer and among different metastatic sites. Liquid biopsies may also be implemented to detect early tumour formation or to monitor cancer relapse of response to therapy with greater sensitivity compared with the currently available protein-based blood biomarkers. Most colorectal cancers are often diagnosed at late stages and have a high mortality rate. Hence, biomolecules as nucleic acids present in liquid biopsies might have prognostic potential and could serve as predictive biomarkers for chemotherapeutic regimens. This review will focus on the role of circulating tumour DNAs and non-coding RNAs as diagnostic, prognostic, and predictive biomarkers in the context of colorectal cancer. Full article

Pancreatic cancer (PC) is the most lethal type of gastrointestinal cancer, and early detection and monitoring is an urgent problem. Circulating tumor cells (CTCs) are emerging as a non-invasive biomarker for tumor detection. However, the low sensitivity is a main problem in the traditional CellSearch System for detecting CTCs, especially in patients with PC. In this study, we used negative enrichment (NE), immunofluorescence and in situ hybridization (FISH) of chromosome 8 (NE-iFISH) to capture and identify CTCs in PC patients. We showed that the NE-iFISH system exhibited a dramatically high detection rate of CTCs in PC patients (90%). The diagnostic rate of PC reached 97.5% when combining CTCs ≥ 2 and carbohydrate antigen 19-9 (CA19-9) > 37 µmol/L. The 1-year survival in the group of CTCs < 3 was significantly higher than that of CTCs ≥ 3 (p = 0.043). In addition, we analyzed the role of chromosomal instability in CTCs detection. The group of triploid (three hybridization signals of chromosome 8) CTCs ≥ 3 showed a shorter 1-year survival (p = 0.0279) and overall survival (p = 0.0188) than the group with triploid CTCs < 3. Importantly, the triploid CTC number but not the overall CTC counts could be a predictor of chemo-sensitivity. Moreover, circulating tumor microembolus (CTMs) were found in stage IV patients, and were positively related to the poor response to chemotherapy. In conclusion, the NE-iFISH system significantly improved the positive detection rate of CTCs and triploid CTC could be used to predict prognosis or the response to the chemotherapy of PC patients. CTM is a potential indicator of the chemotherapeutic effect in advanced PC patients. Full article