BMC Cancer最新文献

Objective: The New Gastric Cancer Screening Score (NGCSS) has been widely applied in the screening of gastric cancer (GC). The purpose of this study is to establish a novel system for GC screening and early diagnosis by combining NGCSS with serum tumor markers and to validate its robustness.

Methods: Patients with GC and non-GC diseases, including superficial gastritis (SG), atrophic gastritis (AG), and intestinal metaplasia (IM), were included in the study. They were allocated to a discovery dataset and a validation dataset in a 2:1 ratio. All individuals underwent standardized NGCSS scoring. Additionally, serum samples were obtained for tumor marker detection, including three traditional markers (CA724, CEA, and CA199) and five novel GC-related markers (OPN, TEF3, SOX3, IGFBP1, and Leptin).

Results: A total of 106 GC and 143 non-GC patients were included in this study, with 167 assigned to the discovery dataset and 82 to the validation dataset. In the discovery dataset, GC and different types of non-GC patients exhibited distinct NGCSS scores and grade levels (P < 0.01). Furthermore, compared to non-GC, GC patients showed significantly increased levels of CEA, OPN, and IGFBP1 in serum (P < 0.001). Multivariate logistic regression indicated that each marker was an independent indicator of GC incidence related to NGCSS (P < 0.001). Additionally, by selecting cutoff values for CEA, OPN, and IGFBP1, a NGCSS-CS[Changshu] screening and prediction system with a total score of 62 points was constructed. Analysis of the validation dataset revealed that NGCSS-CS had better diagnostic performance (AUC = 0.967, P < 0.001) and effectively differentiated between GC and non-GC patients (P < 0.001).

Conclusion: The new model system based on NGCSS combined with multiple tumor markers is feasible and exhibits improved diagnostic performance. The conclusions of this study require further validation and elaboration through large-sample multicenter follow-up studies.

Background: Advancements in digital pathology and computer technology have spurred artificial intelligence in histopathology, but the complexity of whole slide images (WSIs) poses challenges for manual annotation and traditional supervised learning.

Methods: We propose the Sample-Positive (SP) technique, which utilizes adjacent tissue morphology in WSIs to effectively sample positive examples. By integrating pathological prior information that reflects spatial adjacency of similar tissues with self-supervised learning (SSL) frameworks like SimCLR, MoCo-v3, and SinCLR, we developed an SSL method for WSI. We validated this approach on a dataset of 65 lung squamous cell carcinoma (LSCC) cases, covering four histological categories: necrosis, tumor, stroma, and epithelium. Performance was benchmarked against supervised models and original SSL frameworks using fine-tuning and linear evaluation, with metrics including accuracy (Acc), AUC, and F1 score.

Results: Our proposed SP technique outperformed baseline SSL methods in fine-tuning and linear evaluation tasks on the LSCC dataset. SPSimCLR and SPMoCo-v3 achieved the highest F1 scores, with SPSimCLR (0.9132) showing a 0.7% improvement over SimCLR (0.9067) and SPMoCo-v3 (0.9133) a 0.5% improvement over MoCo-v3 (0.9088) in fine-tuning, and SinCLR (0.9074) performs comparably to the original SSL methods. In linear evaluation, SPSimCLR (0.9082) improved F1 scores by 1.0% over SimCLR (0.8978), and SPMoCo-v3 (0.9060) improved by 1.2% over MoCo-v3 (0.8942), and SinCLR(0.9021) is surpass the original SSL methods. Ablation studies revealed that overlapping sampling slightly outperformed non-overlapping sampling, and that models trained on patches with single tissue types performed better than those trained on patches containing multiple tissue types.

Conclusions: Overall, combining the SP technique with contrastive learning shows significant improvements in distinguishing histological categories in LSCC, making it effective for WSIs of non-diffuse cancers.

Background and aim: Melanomagenesis involves genetic alterations affecting multiple oncogenic pathways, with BRAF and NRAS mutations representing frequently studied drivers. Recent evidence suggests melanoma development encompasses a broader spectrum including KIT mutations and novel variants exhibiting population-specific patterns. This study aimed to characterize the genetic landscape of melanomagenesis by analyzing BRAF, NRAS, KIT and novel mutations across melanoma subtypes in a Turkish cohort.

Methods: Sixty-six genetic materials from 55 melanoma patients (2000-2016) were analyzed using targeted next-generation sequencing of 17 melanoma-relevant genes. Mutation profiling characterized genetic diversity across histological subtypes, with associations between molecular alterations and clinicopathological parameters evaluated using Fisher's exact test and Kruskal-Wallis test.

Results: Significant genetic diversity was observed, with 60% of cases harboring mutations. Analysis identified 22 wild-type cases, 13 BRAF mutations (23.6%), 4 NRAS mutations (7.3%), 6 KIT mutations (10.9%), and various alterations in TP53, KNSTRN, KRAS, PIK3CA, CDKN2A, OXA1L, and RAC1. Multiple concurrent mutations occurred in 5 cases (9.1%). Notably, BRAF mutation patterns differed substantially from Western populations: complete absence in superficial spreading melanomas (0.0% versus 50-70% in Caucasian cohorts) with enrichment in nodular melanomas (36.4%). KIT mutations showed significant enrichment in mucosal melanomas (33.3%, P = 0.003). A novel OXA1L frameshift mutation (p.A54Sfs*100) was identified.

Conclusion: Melanomagenesis in the Turkish population demonstrates substantial genetic diversity with population-specific mutation patterns that diverge from Western paradigms. The absence of BRAF mutations in superficial spreading melanomas suggests distinct genetic pathways potentially related to different UV exposure patterns, genetic susceptibility, or gene-environment interactions. These findings have important implications for precision medicine, as therapeutic strategies developed in Western populations may require adaptation for diverse ethnic groups. Comprehensive genomic profiling including NF1 in larger multi-institutional cohorts is needed to fully characterize population-specific melanomagenesis mechanisms.

Background: The enhanced recovery after surgery (ERAS) program is a combined perioperative bundle designed to reduce perioperative stress. However, whether these programs are safe and effective for older patients who have undergone free-flap reconstruction for locally advanced oral cancers remains unclear. This study retrospectively evaluated the risk factors associated with delayed postoperative recovery and prolonged hospital length of stay (LOS) in older patients with locally advanced oral cancer who underwent resection and free-flap reconstruction from an ERAS perspective.

Methods: Sixty-one patients who underwent resection and free-flap reconstruction for locally advanced oral cancer were included. LOS, complications, nutritional intake, and mobilization were evaluated.

Results: The older group exhibited a longer LOS, delayed oral feeding, and more aspiration pneumonia than the non-older group. Analysis of older adults only revealed delayed oral feeding, not chronological age, as a risk factor for prolonged LOS.

Conclusions: Older patients were safely managed using ERAS; however, dysphagia may have interfered with the enhanced recovery.

Background: Uterine leiomyosarcoma (uLMS) has a poor prognosis owing to its resistance to chemotherapy. Therefore, novel therapeutic targets for uLMS should be identified. Suppressor license of variegation 3-9 homolog 2 (SUV39H2) is a histone methyltransferase that promotes the repair of double-strand DNA breaks by recruiting phosphorylated H2AX (γH2AX). In this study, we investigated the potential therapeutic targets of SUV39H2 in uLMS and the mechanism of synthetic lethality between PARP inhibitors and the SUV39H2 inhibitor OTS186935.

Methods: First, we analyzed the mRNA and protein expression of SUV39H2 in the clinical tissues of uLMS, normal myometrium, and leiomyomas using real-time polymerase chain reaction and immunohistochemistry, respectively. Next, we conducted drug sensitivity assays for OTS186935 alone and in combination with olaparib, a poly (ADP-ribose) polymerase inhibitor, using the uLMS cell lines SK-LMS-1 and SK-UT-1. We performed western blotting, immunofluorescence, and chromatin immunoprecipitation sequencing (ChIP-seq) to investigate γH2AX following OTS186935 treatment in addition to in vivo experiments using nude mice with subcutaneously implanted uLMS.

Results: SUV39H2 expression in uLMS was significantly higher than that in the normal myometrium and leiomyomas. OTS186935 decreased the viability of both cell lines, and its combination with olaparib resulted in synthetic lethality in SK-UT-1 cells (combination index = 0.88). After treatment with OTS186935, γH2AX accumulation decreased. ChIP-seq also showed downregulation of γH2AX following OTS186935 treatment. Notably, the combination of OTS186935 and a PARP inhibitor was significantly more effective in vivo.

Conclusion: OTS186935 inhibited double-strand DNA break repair, as evidenced by γH2AX downregulation by ChIP-seq and other assays. Combining OTS186935 with olaparib demonstrated activity resembling synthetic lethality; however, further validation is required before clinical translation.

Background: Colorectal cancer (CRC) is a prevalent gastrointestinal tract disease with atypical manifestations. The objective of this study was to employ serum metabolomics for the identification of potential biomarkers in CRC diagnosis and treatment.

Methods: A total of 136 healthy controls and 134 CRC patients were enrolled in our study. In total, 270 serum samples were analyzed using liquid chromatography-mass spectrometry (LC-MS) and divided into the discovery group and validation group. Meanwhile, we collected 65 CRC patients one week after surgery to systematically monitor postoperative metabolite changes. Statistical analysis and functional annotation were conducted to identify potential biomarker panels and altered metabolic pathways. Mfuzz expression pattern clustering analysis was employed to reveal the changing trends of metabolites across stages 1-4 of CRC.

Results: A total of 118 differential metabolites were identified in this study, demonstrating distinct separation between patients and controls based on serum metabolic profiles. Further functional annotation revealed associations between the differential metabolites and lipid metabolism, amino acid metabolism, nucleic metabolism, as well as pentose and glucuronate interconversions. Moreover, a panel consisting of Guanosine and Tyr Ser exhibited excellent predictive performance for CRC diagnosis with an AUC of 0.961 in the discovery group and an AUC of 0.948 in the validation group. The analysis of these differential metabolites in pre-and postoperative CRC serum samples showed that their levels returned to a healthy state after the operation, suggesting their potential specificity for CRC and highlighting their potential utility in monitoring therapeutic response. Furthermore, clustering analysis using Mfuzz identified dynamic metabolic expression patterns across CRC stages I to IV, with several metabolites exhibiting consistent upregulation or downregulation trends, implying a close association with CRC progression.

Conclusion: This study highlighted significant differences in CRC serum metabolomic profiles, which may have potential value for distinguishing CRC patients from controls and for assessing pre- and post-operative states. The establishment of potentially diagnostic biomarker panels and alerted metabolic pathways provided valuable insights into deeper metabolic disorders associated with CRC. Our data showed that serum metabolomics might be used for CRC diagnosis, prognosis and classification.

Background: Imaging techniques for breast cancer identify distant organ metastasis, but can be time-consuming and costly. This study compares clinicopathological and laboratory data between metastatic and nonmetastatic breast cancer patients at initial diagnosis and evaluates CA 15 - 3's predictive value for distinguishing distant metastases.

Methods: This retrospective study examined 232 untreated breast cancer patients diagnosed between January 2021 and January 2022. They were divided into distant organ metastatic (Group I) and nonmetastatic (Group II) at the initial diagnosis. We analyzed laboratory data, including CA 15 - 3 and CEA levels, and used Receiver Operating Characteristic (ROC) curves to find optimal cut-off values for predicting distant organ metastasis.

Results: Forty-nine patients (21.1%) had distant organ metastases at initial diagnosis. Significant differences were found between groups in tumor diameter, neutrophil and lymphocyte counts, T-stage, N-stage, CA 15 - 3, CEA, albumin, alkaline phosphatase, neutrophil-to-lymphocyte ratio, and the systemic immune inflammation index (SII) (all p < 0.05). CA 15 - 3 demonstrated excellent discriminatory ability (AUC = 0.950; 95% CI: 0.924-0.975; p < 0.001). A CA 15 - 3 cutoff value of 25.8 U/mL had 100% sensitivity, 82.5% specificity, 60.5% positive predictive value, and 100% negative predictive value. No patient with a CA 15 - 3 level below 25.8 U/mL presented with distant organ metastasis.

Conclusions: CA 15 - 3 demonstrated promising performance in ruling out distant metastases in newly diagnosed breast cancer patients. Further prospective studies are needed to confirm whether using CA 15 - 3 may reduce the time loss and costs associated with routine imaging for distant organ metastasis.