American journal of cancer research最新文献

Objective: To evaluate clinical, molecular, and immunological predictors of response to immunotherapy among patients with advanced endometrial cancer and to develop a combined biomarker model for predicting treatment outcomes.

Methods: This retrospective case-control study included 590 advanced endometrial cancer patients treated at the Affiliated Hospital of Hebei University of Engineering between December 2024 and May 2025. Eligible women underwent total hysterectomy, pelvic lymph node dissection, and received immune checkpoint inhibitors alongside standard chemotherapy. Patients were stratified into good and poor response groups based on 1-year post-treatment prognosis and response evaluation criteria in solid tumors. Baseline blood biomarkers, gene mutation status (breast cancer gene [BRCA] 1, BRCA2, DNA polymerase epsilon, tumor protein p53 [TP53], mutS homolog 6), and immunophenoscore (IPS) were assessed. Logistic regression and receiver operating characteristic (ROC) analyses were performed. A random forest model was constructed for combined biomarker prediction.

Results: No significant differences in baseline demographic or clinical characteristics were found between response groups. Good responders had significantly lower baseline levels of C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), neutrophil-lymphocyte ratio (NLR), cancer antigen 125 (CA125), and IPS, and higher frequencies of gene mutations. Multivariate regression identified elevated CRP, IL-6, TNF-α, NLR, CA125, and IPS as independent predictors of poor response; BRCA2 and TP53 mutations were independently associated with favorable outcomes. The combined biomarker model achieved an area under the ROC curve of 0.812, demonstrating strong predictive accuracy.

Conclusion: Inflammatory and tumor biomarkers, IPS, and specific gene mutations are independently associated with immunotherapy response in advanced endometrial cancer. A combined biomarker model may enhance the prediction of treatment outcomes and guide individualized therapy.

Lung cancer is one of the most common cancers and the leading cause of cancer death worldwide. Opportunistic infections (OI) are increasingly recognized in this population due to disease-related immune dysfunction and treatment-induced immunosuppression. Compared with the chemotherapy era, the use of immune checkpoint inhibitors and targeted agents has shifted the OI profile. Pneumocystis jirovecii pneumonia (PJP) and invasive pulmonary aspergillosis (IPA) are reported more often in older adults and patients with lymphopenia, while tuberculosis (TB) and nontuberculous mycobacteria (NTM) cluster in those with structural lung disease (e.g., bronchiectasis, cavities) and prolonged immunosuppression. High-risk features include absolute lymphocyte count <500/µL, corticosteroids ≥20 mg prednisone-equivalent for ≥4 weeks, airway obstruction, prior TB, chronic obstructive pulmonary disease/interstitial lung disease (ILD), and recent broad-spectrum antibiotics. Diagnosis should integrate high-resolution computed tomography (HRCT) patterns (e.g., diffuse ground-glass for PJP; nodules with halo sign for IPA), microbiology [bronchoalveolar lavage fluid (BALF) culture/microscopy, galactomannan (GM)/β-D-glucan (BDG)], and metagenomic next-generation sequencing, interpreted against host factors and treatment timeline, while carefully distinguishing immune-related pneumonitis and TKI-associated ILD. Prophylaxis with TMP-SMX is recommended for high-risk patients; voriconazole (or isavuconazole) is first-line for IPA with attention to drug-drug interactions; TB/NTM regimens require coordination with anticancer therapy, especially where rifamycins interact with TKIs. Vaccination (influenza, pneumococcus, zoster) and antimicrobial stewardship are essential. Future work should validate risk scores prospectively and clarify microbiome-immunotherapy-infection relationships.

Advances in radiomics and machine learning techniques have facilitated the extraction of quantitative radiomic features that can be correlated with genomic data. Breast MRI-based radiogenomics, which combines MRI radiomics and genomics, is an emerging field that non-invasively reflects tumor heterogeneity and assesses the biological behaviour of breast cancer. Studies have shown that radiogenomics has the potential to replace traditional genetic testing for breast cancer, reducing the need for invasive procedures such as biopsies. In the future, the clinical application of radiogenomics as a tool for molecular subtype identification, treatment response and prognosis prediction, and recurrence risk assessment is both necessary and feasible.

Colorectal cancer (CRC) is among the most prevalent malignancies worldwide, with approximately 40% of the patients carrying KRAS mutations. Among these, the KRAS G12C mutation accounts for approximately 4% of the cases. This mutation introduces a unique cysteine residue at codon 12, enabling covalent binding and rendering KRAS G12C a tractable therapeutic target. Recently, selective small-molecule inhibitors of KRAS G12C, including sotorasib and adagrasib, have shown encouraging activity in early clinical trials, indicating potential clinical benefits for this subset of patients. However, their translation into routine clinical practice has been challenged by intrinsic and acquired resistance, treatment-related toxicities, and the absence of reliable predictive biomarkers. The aim of this study is to construct a clear knowledge framework that could inform the design of future clinical trials and optimize clinical practice. Future studies should focus on developing more potent next-generation inhibitors, exploring and optimizing rational combination strategies with other targeted agents or immunotherapies, investigating innovative therapeutic methods, and systematically identifying and validating predictive biomarkers. Collectively, with these efforts, we aim to enhance the efficacy, overcome resistance, and advance precision therapy for patients with KRAS G12C-mutant CRC.

Gynecological tumors represent a significant health burden worldwide. Protein lactylation has emerged as a novel post-translational modification (PTMs) that directly links metabolic reprogramming to epigenetic and functional regulation. Lactylation occurs when lactate covalently modifies the lysine residues of proteins. Initially discovered on histones, lactylation was shown to influence gene transcription; however, accumulating evidence reveals its broader impact on nonhistone proteins, affecting diverse processes. Elevated lactate levels in the tumor microenvironment increase protein lactylation. Evidence suggests a dynamic interplay between tumor metabolism and cancer progression. In this review, we provide an overview of the fundamental aspects of protein lactylation, including the key enzymes that catalyze the addition and removal of lactyl groups. We further emphasize recent discoveries on how lactylation influences the development and progression of gynecological malignancies. Finally, we explore the potential of targeting protein lactylation as an emerging therapeutic strategy in the management of gynecological cancers.

The spine is a common site for metastases in lung cancer. Precise identification of factors associated with survival and reliable prediction of prognosis are essential for clinical decision-making in patients with spinal metastasis from lung cancer. A retrospective analysis was conducted on 148 lung cancer patients with spinal metastases between January 2018 and December 2020 to identify prognostic factors and develop a nomogram for predicting survival outcomes. Another 30 patients with spinal metastases due to lung cancer, treated between January 2021 and February 2022, served as an external validation cohort to assess the nomogram's predictive performance. Multivariate analysis identified Karnofsky Performance Status (KPS) score, carbohydrate antigen 125 (CA125), radiotherapy, chemotherapy, and targeted therapy as independent prognostic factors. The nomogram achieved a concordance index of 0.713. The AUCs for the nomogram in predicting 1-, 2-, and 3-year survival were 0.834, 0.750, and 0.733 in the training set; 0.803, 0.738, and 0.713 in the internal validation set; and 0.749, 0.738, and 0.729 in the external validation set. Calibration curves showed good agreement between predicted and observed outcomes. Compared with the modified Tokuhashi and Tomita scores, the nomogram demonstrated superior predictive accuracy and provided greater net clinical benefit in decision curve analysis, indicating good clinical utility. This model may aid individualized prognosis assessment and treatment planning in lung cancer patients with spinal metastases.

Metastasis, the leading cause of death in patients with solid tumors, involves the spread of cancer cells to distant organs. While genetic and environmental factors contribute, chronic stress is a crucial factor in metastatic progression by disrupting neuroendocrine, immune, metabolic, and microbial homeostasis. This review synthesizes evidence linking chronic stress to tumor metastasis through three pathways: (1) direct effects on tumor cell metabolism, (2) remodeling of the tumor microenvironment, and (3) dysregulation of the gut microbiota. Describe how activation of the hypothalamic-pituitary-adrenal axis and sympathetic nervous system influence epithelial-mesenchymal transition, immune evasion, and angiogenesis via β-adrenergic and glucocorticoid receptor signaling. Explore how microbial metabolites and barrier dysfunction influence immune and neuroendocrine circuits, creating a pro-metastatic loop. Finally, we highlight therapeutic strategies, including psychological interventions and pharmacologic approaches, to alleviate chronic stress. This review proposes a mechanistic framework linking neuroendocrine signaling, metabolic reprogramming, and the microbiome-immune axis.

Bone cancer pain (BCP) is a frequent and debilitating complication in patients with malignant tumors, arising from a multifactorial interplay of bone destruction, neural injury, and inflammatory responses. Microglia can polarize into either an M1 phenotype, which aggravates nociception, or an M2 phenotype, which facilitates pain resolution. Activation of the TLR4/NF-κB signaling cascade is known to drive M1 polarization, thereby amplifying inflammation and neuronal damage. This study aimed to investigate whether macrophage-derived exosomes could mitigate BCP by modulating the TLR4/NF-κB pathway, suppressing M1 polarization, and enhancing M2 microglial polarization. In vitro, RAW264.7 macrophages were polarized to the M2 phenotype via IL-4 stimulation, and exosomes were subsequently isolated and applied to LPS-challenged BV2 microglial cultures. Polarization profiles were analyzed using flow cytometry, immunofluorescence, qRT-PCR, and Western blotting. In vivo, a rat BCP model was established, and exosome treatments were administered. Behavioral assays were performed to assess pain responses, followed by evaluation of microglial polarization and TLR4/NF-κB pathway activity in spinal cord tissue. Results demonstrated that IL-4 treatment effectively induced M2 polarization in RAW264.7 cells, and the isolated exosomes displayed characteristic morphology and marker expression. BV2 microglia internalized these vesicles, leading to pronounced inhibition of LPS-induced M1 polarization, promotion of M2 polarization, suppression of pro-inflammatory cytokine release, and downregulation of TLR4/NF-κB activation. In vivo, exosome administration elevated the mechanical pain threshold and attenuated pain-related behaviors, while spinal cord analyses revealed reduced expression of M1 markers, increased M2 markers, and marked suppression of TLR4/NF-κB signaling. Collectively, these findings indicate that macrophage-derived exosomes alleviate BCP through coordinated regulation of TLR4/NF-κB signaling and microglial polarization, suggesting their potential as a novel therapeutic option for managing bone cancer pain.

In non-small cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR) is one of the most prevalent driver gene, whose expression and recurrent mutations are closely related to the prognosis of patients. EGFR tyrosine kinase inhibitors (EGFR-TKIs) are ones of the most used among the first line treatment of NSCLC, but their efficacy is significantly reduced due to the inevitable development of acquired EGFR-TKI resistance. Consequently, searching for innovative drugs to overcome this challenge is urgent. Immune checkpoint inhibitors such as antibodies against the programmed cell death protein-1 (PD-1) or its ligand (PD-L1), have exhibited remarkable potential in NSCLC therapy. While the response rates of PD-1/PD-L1 blockade in EGFR-mutated NSCLC patients remain controversial. To gain deeper insights, we first analyzed the different therapeutic effect of PD-1/PD-L1 blockade between EGFR wild-type and mutated NSCLC patients. Meanwhile, the factors and the mechanisms that affect therapeutic effect of PD-1/PD-L1 blockade were summarized, including PD-1/PD-L1 expression levels, the tumor microenvironment (TME), and the adoption of combination therapy strategies. Furthermore, we comprehensively evaluated the combinatorial therapeutic effect with established synergistic potential within these factors. Moreover, we further explored the potential of PD-1/PD-L1 as a predictive biomarker for EGFR mutations by conducting a systematic and multidimensional analysis, aiming to refine therapeutic decision-making and facilitate personalized treatment strategies for EGFR-mutated NSCLC. Additionally, we also discussed the novel strategies that could alleviate the EGFR-TKIs resistance in NSCLC base on PD-1/PD-L1 immune inhibitors, shedding light on challenges facing future research.

IDH1 and ATRX mutations frequently co-occur in several glioma subtypes, including secondary glioblastomas (GBMs), suggesting that these alterations may function cooperatively during tumor development. However, the molecular basis of their interaction remains poorly defined. In present study, we demonstrate that the IDH1-R132H mutation acts synergistically with ATRX loss to upregulate pro-proliferative genes while suppressing interferon (IFN) signaling. This coordinated effect supports the notion that the two mutations jointly promote tumor growth and attenuate anti-tumor immune responses. Notably, we also found that the combined IDH1/ATRX mutations increase GBM cell sensitivity to various forms of cell death, particularly ferroptosis. Mechanistically, the dual IDH1/ATRX alteration upregulates pro-ferroptotic genes (HMOX1 and ACSL4) while downregulating anti-ferroptotic genes (SLC7A11 and GPX4), thereby sensitizing GBM cells to ferroptosis induction. Together, our findings provide new biological insights into IDH1/ATRX-driven GBM pathogenesis and highlight ferroptosis as a potential therapeutic vulnerability in this aggressive tumor subtype.