Cancers最新文献

Background: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. Methods: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature selection was performed using LASSO regression, followed by the construction of a multivariate-Cox-regression-based prognostic prediction model. In vitro validation was performed using a cell viability assay, colony formation, cell cycle analysis, apoptosis detection, γH2AX immunofluorescence staining and comet electrophoresis. In vivo validation was performed utilizing a subcutaneous tumor-bearing mouse model, where radiosensitivity was assessed by monitoring tumor volume post-irradiation. Results: We constructed a robust prognostic prediction model based on five TP53-signaling-pathway-related genes (MDM2, THBS1, TP53I3, ATM, and SESN3), achieving a 5-year AUC of 0.828 in the training set and a 3-year AUC of 0.824 in the validation set. The model exhibited a significant ability to stratify patients into distinct high- and low-risk groups, demonstrating good predictive performance. The poor prognosis observed in the high-risk group was associated with lower infiltration of anti-tumor immune cells but higher infiltration of immunosuppressive cells. Both in vitro and in vivo experiments demonstrated that TP53I3 knockdown significantly enhanced the radiosensitivity of NSCLC through increased DNA damage, cell cycle arrest and apoptosis. Conclusions: In this study, a five-gene signature derived from the TP53 signaling pathway was developed, and the model was shown to effectively predict the prognoses of NSCLC patients undergoing radiotherapy. This signature has the potential to be developed into a clinically applicable tool for personalizing radiotherapy regimens for NSCLC.

Background/Objectives: Diffuse large B-cell lymphoma (DLBCL) is an aggressive and heterogeneous malignancy, for which predicting clinical outcomes remains challenging. Although immune-checkpoint pathways are known to influence tumor biology, the impact of their germline variants on DLBCL susceptibility and prognosis has not been fully elucidated. Methods: Variants in PD-L1 gene CD274 (rs4143815, rs822336), and miR-155 gene MIR155HG (rs767649, rs1893650), assessed by TaqMan assays in 99 DLBCL patients and 113 age- and sex-matched healthy controls, were associated with clinicopathological features, treatment response, overall survival (OS), relapse-free survival (RFS), and disease susceptibility. Results: The PD-L1 variant rs822336 was significantly associated with relapse status (p = 0.005) and RFS (p = 0.008), with the wild-type GG genotype showing the poorest RFS that remained independent in the multivariate Cox analysis (HR = 2.387, p = 0.003). Conversely, rs4143815 showed a nominal association with treatment resistance (p = 0.026), while patients carrying the GG genotype had worse OS (p = 0.006). In susceptibility analyses, miR-155 variant rs767649 showed a nominal association with DLBCL risk, with the rare AA genotype showing an increased risk of DLBCL (OR = 5.234, p = 0.045), which did not remain significant after Bonferroni correction. Conclusions: In a hypothesis-generating manner, these findings suggest that PD-L1 genetic variants may predominantly influence disease progression and outcomes, while miR-155 variation may contribute to DLBCL susceptibility. These findings highlight germline immunogenetic variants as stable, treatment-independent markers that may inform future studies on risk stratification and prognosis in DLBCL.

Background/objectives: Melanoma is the most lethal cutaneous neoplasm, with Breslow thickness being a key prognostic factor. This retrospective cohort study aimed to assess the impact of screening frequency and diagnostic methods on tumour stage at diagnosis and to explore implications for risk-adapted strategies.

Methods: Between 2017 and 2024, 475 cases of melanoma were diagnosed in 397 patients. Screening frequency, diagnostic method, and patient risk were analyzed in relation to tumour stage.

Results: Compared with first-visit cases, patients who underwent screening within two years prior to diagnosis were more often diagnosed with melanoma in situ (32.6% vs. 44-51%; p < 0.05) and had thinner invasive tumours (0.68-0.73 mm vs. 1.8 mm; p ≤ 0.001), though no differences were seen between screening frequencies. Full-body examination was associated with more in situ melanomas (46% vs. 34%; p = 0.016) and thinner invasive tumours (0.92 vs. 2.05 mm; p = 0.2) compared with lesion-directed screening, but this effect disappeared after excluding first-visit cases. Invasive melanomas diagnosed by mole mapping were significantly thinner than by dermoscopy (0.55 vs. 1.07; p = 0.035). In high-risk patients, tumour thickness decreased with more frequent visits (0.905 mm without screening vs. 0.40-0.55 mm with ≥1 visit; p = 0.001). Moreover, mole mapping identified thinner melanomas in the high-risk group compared with dermoscopy (0.47 vs. 0.60 mm; p = 0.02).

Conclusions: Screening is associated with thinner melanomas and more in situ diagnoses. Digital mole mapping offers additional benefits, with high-risk patients profiting most, while low-risk individuals could be managed with less resource-intensive approaches. These findings support risk-adapted screening strategies focusing on intensive, digitally supported modalities for high-risk groups.

Purpose: Proton beam therapy (PBT) offers superior dosimetric sparing of organs at risk compared to photon radiotherapy for non-small cell lung cancer (NSCLC); however, comparative clinical evidence regarding survival benefits remains conflicting. This systematic review and meta-analysis aimed to evaluate the clinical outcomes and toxicity profiles of PBT versus photon radiotherapy, with a specific focus on time-dependent survival patterns.

Methods: We searched PubMed, EMBASE, and Cochrane CENTRAL databases for comparative studies published up to 10 October 2025. Primary outcomes were overall survival (OS), progression-free survival (PFS), and local progression-free survival (LPFS). Individual patient data (IPD) were reconstructed from Kaplan-Meier curves when hazard ratios (HRs) were not reported. Odds ratios (ORs) were calculated for survival at fixed time points (1, 3, and 5 years) and for toxicity endpoints.

Results: Seven studies comprising 244,604 patients were included, encompassing retrospective cohorts, multi-institutional datasets, and one randomized trial. In the overall pooled analysis, PBT showed no statistically significant superiority over photon radiotherapy for OS (HR = 0.91, 95% CI: 0.69-1.19, p = 0.483), PFS (HR = 1.09, 95% CI: 0.81-1.47, p = 0.572), or LPFS (HR = 0.89, 95% CI: 0.47-1.69, p = 0.732). Sensitivity and subgroup analyses restricted to Stage I and Stage I-II NSCLC similarly failed to demonstrate significant differences in survival outcomes. However, exploratory time point analysis utilizing ORs revealed a distinct temporal pattern: PBT was associated with improved odds of all-cause mortality at 1 year (OR = 0.60, 95% CI: 0.49-0.73, p < 0.001). This survival advantage dissipated over time, with no significant differences observed at 3 years or 5 years. Regarding safety, PBT did not significantly reduce the odds of grade ≥ 2 radiation pneumonitis (OR = 0.98, 95% CI: 0.41-2.33, p = 0.967) or grade ≥ 3 events (OR = 1.40, p = 0.540) compared to photons.

Conclusions: While long-term oncologic control appears comparable between proton and photon radiotherapy, exploratory analyses suggest that PBT is associated with improved odds of 1-year overall survival. This potential early benefit, observed in retrospective cohorts, likely reflects the mitigation of acute treatment-related mortality. These findings are hypothesis-generating and support the use of PBT for patients at high risk of toxicity and advocate for a model-based approach to patient selection.

Background: Breast cancer is one of the most frequently diagnosed cancers worldwide, with metastasis contributing to high mortality rates. Current treatments for metastatic disease are limited, emphasizing the urgent need for novel therapeutic approaches. Methods: We conducted a small-molecule drug screen utilizing patient-derived circulating tumor cells (CTCs) as a platform to identify potential anti-cancer agents. We used a dye combination and a high-content imaging microscope to evaluate cellular viability upon compound treatment. Among the 250 small molecules tested, potential hits were identified. The efficacy of these compounds was investigated using in vitro and in vivo studies in mouse breast cancer models. Bulk RNA sequencing of treated cancer cells was performed to identify differentially expressed genes, with Gene Ontology enrichment analyses conducted for their functional characterization. Results: Our screen of a 250 small-molecule library led to the identification of five hits, derivatives of meriolins known to display cyclin-dependent kinase (CDK-2/9) inhibitory activity. Subsequent in vitro and in vivo studies validated the efficacy of these compounds in inhibiting cell cycle, tumor growth, and consequently, metastatic colonization in mouse breast cancer models. Treatment with single agents (15 mg/kg) in breast cancer mouse models demonstrated good tolerability in vivo. Transcriptome profiling of treated cancer cells revealed alterations in pathways associated with cell cycle regulation, providing mechanistic insights into the anti-cancer effects of the compounds. Conclusions: By integrating drug screens, transcriptomic analysis, and in vivo validation, our study contributes to the identification of novel promising candidates for the treatment of breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by high immunogenicity and specific immune signatures. Although these molecular features including elevated tumor-infiltrating lymphocytes (TILs) and programmed death-ligand 1 (PD-L1) expression provide a strong rationale for immunotherapy, clinical response remains limited due to multiple mechanisms of immune escape. This review summarizes current and emerging immunotherapeutic strategies in TNBC, including immune checkpoint inhibitors (PDL-1 and cytotoxic T-lymphocyte-associated protein 4 (CTL-4) blockade), adoptive cell therapy (ACT) (chimeric antigen receptor T-cell therapy (CAR-T) and TIL therapy), oncolytic virotherapy, and antibody-based approaches. We also discuss the mechanisms of resistance including DNA damage response alterations, anti-apoptotic signaling, and tumor microenvironment-mediated resistance. Finally, we highlight rational combination strategies, immunotherapy with chemotherapy, targeted therapy, or additional immunotherapies that aim to enhance response to immunotherapy. Ongoing advances in immunotherapy hold significant potential to improve outcomes for patients with TNBC.

Cancer remains a leading cause of morbidity and mortality worldwide, and effective strategies for cancer prevention are urgently needed to complement therapeutic advances. While dietary factors are known to influence cancer risk, the molecular mechanisms that mediate inter-individual responses to nutritional exposures remain poorly defined. Emerging evidence identifies long non-coding RNAs (lncRNAs) as pivotal regulators of gene expression, chromatin organization, metabolic homeostasis, immune signaling, and cellular stress responses, the core processes that drive cancer initiation and progression and are highly sensitive to nutritional status. In parallel, advances in precision nutrition have highlighted how variability in genetics, metabolism, microbiome composition, and epigenetic landscapes shape dietary influences on cancer susceptibility. This review integrates these rapidly evolving fields by positioning lncRNAs as molecular conduits that translate dietary exposures into transcriptional and epigenetic programs governing cancer development, progression, and therapeutic vulnerability. We provide mechanistic evidence demonstrating how dietary bioactive compounds and micronutrients, including polyphenols [such as curcumin, resveratrol, epigallocatechin gallate (EGCG)], flavonoids, alkaloids such as berberine, omega-3 (ω-3) fatty acids, folate, vitamin D, probiotic metabolites (such as butyrate and propionate), and trace elements (such as selenium and zinc), modulate oncogenic and tumor-suppressive lncRNAs. These nutrient-lncRNA interactions influence cancer-relevant pathways controlling proliferation, epithelial-mesenchymal transition (EMT), inflammation, oxidative stress, and metabolic rewiring. We further discuss emerging lncRNA signatures that reflect nutritional and metabolic states, their potential utility as biomarkers for individualized dietary interventions, and their integration into liquid biopsy platforms. Leveraging multi-omics datasets and systems biology, we outline AI-driven frameworks to map nutrient-lncRNA regulatory networks and identify targetable nodes for cancer chemoprevention. Finally, we address translational challenges, including compound bioavailability, inter-individual variability, and limited clinical validation, and propose future directions for incorporating lncRNA profiling into precision nutrition-guided cancer prevention trials. Together, these insights position lncRNAs at the nexus of diet and cancer biology and establish a foundation for mechanistically informed precision nutrition strategies in cancer chemoprevention.

Background/Objectives: Cutaneous metastases from primary bone sarcomas are exceedingly rare and poorly characterized, often posing diagnostic challenges due to their atypical presentation. This systematic review aimed to describe the clinical patterns, temporal relationships, and prognostic implications of cutaneous metastases across major bone sarcoma histologies. Methods: A comprehensive literature search was conducted to identify all reported cases of cutaneous metastases from osteosarcoma, chondrosarcoma, Ewing sarcoma, and chordoma. Data on patient demographics, primary tumor site, cutaneous lesion characteristics, latency periods, synchronous metastases, morphology, and clinical outcome were extracted and analyzed descriptively. Results: 102 cases were identified, with chordoma representing the most frequent histology. Cutaneous metastases showed histology-specific patterns: osteosarcoma and Ewing sarcoma typically presented with multiple lesions in the context of widespread systemic disease and poor prognosis, whereas chordoma more often exhibited solitary or skin-dominant metastases with longer latency and occasional favorable outcomes, including complete responses after local treatment. Conclusions: Cutaneous metastases in bone sarcomas display heterogeneous behavior, with chordoma demonstrating a more indolent and potentially manageable pattern compared to other histologies. Increased clinical awareness is essential to avoid diagnostic delays and optimize management.

Body composition, specifically the quantification of skeletal muscle and adipose tissue using preoperative computed tomography (CT) imaging, is a clinically significant predictor of postoperative complications after lung cancer surgery. The main features of CT-derived body composition analysis are: skeletal muscle index, muscle density, adipose tissue quantification and automated or semi-automated segmentation. Low skeletal muscle mass (sarcopenia) independently increases the risk of perioperative complications, including respiratory complications, and is associated with longer hospital length of stay and worse long-term survival. Sarcopenic obesity-characterized by low muscle mass in the context of high adiposity-further elevates complication risk and prolongs recovery. CT-derived measures such as muscle cross-sectional area, muscle density, and adipose tissue distribution (visceral, subcutaneous, and intramuscular) provide more precise risk stratification than BMI alone. Skeletal muscle area and density are inversely correlated with postoperative complications and recurrence risk; patients with lower muscle mass and density experience more adverse outcomes. In men, age and reduced skeletal muscle area are particularly strong predictors of complications after pneumonectomy. Obesity, when not accompanied by sarcopenia or myosteatosis, may confer a survival advantage-the so-called "obesity paradox"-but this protective effect is lost in patients with low muscle mass or poor muscle quality. Systemic inflammation and nutritional status further modulate the impact of body composition on surgical risk. This review highlights the critical role of CT-derived body composition analysis in predicting postoperative outcomes following lung cancer surgery.

Background/Objectives: Mycosis fungoides (MF) and Sézary syndrome (SS) are cutaneous T-cell lymphomas (CTCLs) with variable clinical outcomes. Peripheral blood (PB) involvement in MF/SS is an independent predictor of prognosis. Accurate laboratory determination of PB involvement by MF/SS cells, however, is an ongoing challenge. Both flow cytometry (FC) and morphology-based quantification are limited by the overlap of CTCL cells and reactive T-cells. This study looks at the optimization over time of CTCL blood burden evaluation. Methods: This retrospective study reviews CTCL blood assessment at Northwestern Memorial Hospital from 2012 to 2021. Test ordering and reporting practices for morphology-based Sézary cell counts and FC were evaluated. For each assay, quantitative and qualitative results were analyzed and compared including percentages and absolute counts of abnormal T-cell populations and pathologist interpretations. Results: A total of 514 patients were evaluated, with increasing numbers of both tests ordered over time. FC quantitative metrics showed a moderate to high correlation with morphology metrics, especially for absolute CD4+/CD7- counts (correlation coefficient = 0.901, p-value < 0.001). Qualitative pathologist interpretations had moderate agreement between methods (kappa = 0.58). The recent addition of TRBC1 clonality assessment to our FC assay further optimizes the evaluation for CTCL blood burden. Conclusions: Flow cytometry offers a reliable approach for blood staging in MF/SS, and morphologic assessment may be redundant. This study provides a foundation for designing a new FC approach with TRBC1. This comprehensive review of the evolution of our laboratory practices may serve as a guide for other institutions with similar clinical needs.