Clinical & Translational Oncology最新文献

Purpose: Accurate quantitative survival prediction in advanced non-small cell lung cancer (NSCLC) remains an unmet clinical need. While liquid biopsy is widely used, single circulating tumor DNA (ctDNA) shows limited predictive power. We developed an interpretable deep-learning model to quantitatively predict outcomes.

Methods/patients: We integrated data from 1373 advanced NSCLC patients profiled by two ultra-deep ctDNA sequencing assays (MSK-ACCESS and ctDx Lung). Features associated with overall survival (OS) were incorporated into a deep-learning network (DeepSurv), which estimates time-to-event survival probabilities. Model performance was evaluated by time-dependent area under the curve (AUC). SHapley Additive exPlanations (SHAP) were employed to interpret model output.

Results: A total of 1373 patients were analyzed, with 1012 using MSK-ACCESS (discovery) and 361 using ctDx Lung (validation). Among over 40 clinicopathological features, ctDNA status, cell-free DNA (cfDNA) concentration, age, blood-based TP53, EGFR, PIK3CA, ARID1A, STK11 and MET mutations significantly predicted OS. In ctDNA-positive patients, TP53/PIK3CA/ARID1A/STK11/MET-mutated patients had significantly inferior OS compared with wildtype patients (P < 0.001). Using above variables, DeepSurv was trained and tested in the MSK-ACCESS cohort (12-month AUC = 0.75), outperforming single cfDNA (AUC = 0.66) or ctDNA (AUC = 0.59), and externally validated in the ctDx Lung cohort. Compared with high-risk patients, DeepSurv-identified low-risk patients had significantly longer OS in both discovery (12-month OS 87.8% vs 53.8%, HR 0.32, P < 0.001) and validation cohorts (73.2% vs 48.4%, HR 0.42, P < 0.001). SHAP revealed TP53 and cfDNA concentration > 4.8 ng/mL had the most important contributions.

Conclusions: The interpretable DeepSurv model, integrating multimodal features, enables quantitative survival prediction and risk stratification in advanced NSCLC, facilitating personalized decision-making.

Purpose: To explore the systemic inflammatory biomarker changes throughout the entire treatment period from the perspective of the extent of surgical resection and their possible role in predicting survival in glioblastoma.

Methods: A retrospective analysis was performed on 41 glioblastoma patients who underwent either gross total resection (GTR, n = 14) or subtotal resection (STR, n = 27), followed by adjuvant radiotherapy (60 Gy) with concurrent and adjuvant temozolomide. Inflammatory biomarkers, including neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), systemic inflammatory index (SII), and systemic inflammation response index (SIRI), were calculated from routine blood tests. These biomarkers were measured at specific times: preoperatively, before radiotherapy, after chemoradiotherapy, at the sixth cycle of temozolomide, and at radiological and/or clinical progression. Survival outcomes were analyzed using the Kaplan-Meier method.

Results: Median follow-up was 21 months. Patients with GTR had significantly better 2-year progression-free survival (42.9% vs. 18.5%, p = 0.033) and overall survival (50% vs. 33.3%, p = 0.045) compared to those with STR. Inflammatory biomarker levels remained higher in the STR group both after RT and following the sixth cycle of temozolomide than in the GTR group. Changes in biomarker levels were not affected by the interval between surgery and radiotherapy, Ki-67 status, the number of chemotherapy cycles, age, or gender.

Conclusion: Long-term patterns of systemic inflammatory biomarkers may reflect a higher inflammatory burden and a poorer prognosis in patients with glioblastoma. The predictive role of these biomarkers should be evaluated in prospectively collected, molecularly characterized cohorts.

Background: Squamous cell carcinoma of the head and neck (SCCHN) is the fifth most common cancer in the world. We investigate the general frequency of SCCHN in the Brazilian Amazon to identify the prevalence of HPV, EBV, and HIV among the local population by means of PCR and to examine the evolution and prognosis of patients.

Methods: This study included 190 individuals with SCCHN and was conducted in the outpatient and inpatient units of the Surgical Clinic of the Department of Head and Neck Surgery of a Hospital in the Brazilian Amazon. We performed HPV detection through PCR and sequencing, EBV detection through RNA in situ hybridization (ISH), and HIV detection through RNA amplification. Statistical analysis included survival estimates through the Kaplan‒Meier curve.

Results: Most participants were male (77.9%, 95% CI 72.0-83.8), while 22.1% (95% CI 16.2-28.0) were female. The mean age was 62.2 years (± 12.6; 95% CI 60.4-63.9), with a median age of 64.0 years (range: 27.0-89.0; 95% CI 60.4-63.9). EBV was not significantly associated with SCCHN and may have only been a contaminant at the evaluated sites. Individuals with mutations in the TP53 and EGFR genes developed more aggressive cancer phenotypes, leading to a 2.6-fold increase in the risk of death. SCCHN was present in the sample, affecting 3.5 times more men than women, with stage IV being the most frequent.

Conclusions: TP53 and EGFR gene mutations were associated with more aggressive cancer phenotypes, leading to a 2.6-fold increase in the risk of death.

Background: Trilaciclib is a cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor that has shown promise in mitigating chemotherapy-induced myelosuppression (CIM). This meta-analysis aims to provide a comprehensive and clinically relevant quantification of trilaciclib's effectiveness in reducing CIM and its potential impact on outcomes in adult patients with solid tumors.

Methods: We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) and observational studies evaluating trilaciclib administered along with chemotherapy in adult patients (≥ 18 years) with advanced or metastatic solid tumors. Databases searched included PubMed, Embase, the Cochrane Library, and major trial registries (ClinicalTrials.gov, EU Clinical Trials Register, ICTRP) up to May 21, 2025. Primary outcomes were incidence of grade 3/4 neutropenia, febrile neutropenia (FN), need for granulocyte-colony stimulating factors (G-CSF)/erythropoiesis-stimulating agents (ESA), and need for red blood cell/platelet transfusions. Efficacy endpoints included progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). Pooled odds ratios (OR) or hazard ratios (HR) were calculated using a random-effects model. Heterogeneity was assessed with the I² statistic. Sensitivity and subgroup analyses were conducted to explore the robustness of results and sources of heterogeneity.

Results: Ten studies with a total of 979 patients were included, with 586 receiving trilaciclib alongside chemotherapy and 393 receiving chemotherapy alone. Pooled analysis showed that trilaciclib decreased the incidence of grade 3/4 neutropenia by 79% (OR = 0.21; 95% CI: 0.08-0.52; I² = 71%), febrile neutropenia (FN) by 75% (OR = 0.25; 95% CI: 0.14-0.46; I² = 0%), grade 3/4 anemia by 60% (OR = 0.40; 95% CI: 0.28-0.57; I² = 0%), and reduced ESA use by 56% (OR = 0.44; 95% CI: 0.26-0.77; I² = 0%). Significant improvements were also observed in PFS (HR = 0.77; 95% CI: 0.66-0.90; I² = 0%) and OS (HR = 0.58; 95% CI: 0.36-0.94; I² = 72%). Trilaciclib use was not associated with a significant increase in the incidence of adverse events.

Conclusion: Trilaciclib significantly reduced CIM and the need for hematopoietic support during chemotherapy. It also showed a positive impact on efficacy outcomes without compromising chemotherapy effectiveness or increasing toxicity. Overall, our findings support trilaciclib's evolving role as a promising adjunct to chemotherapy protocols in appropriately selected patients.

Background: Several PET/CT-based criteria have been developed to assess immunotherapy (IT) response, but their correlation with overall survival (OS) and mutual concordance in non-small-cell lung cancer (NSCLC) remains unclear.

Methods: Pre-treatment and first post-treatment 18F-FDG PET/CT scans of 35 metastatic NSCLC patients receiving second-line or later IT were analyzed using four criteria: PERCIST, PECRIT, PERCIMT, and imPERCIST5. According to each criterion, treatment response was classified as complete metabolic response (CMR), partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD). The primary endpoint was the association with OS, and the secondary was inter-criteria concordance. Patients were stratified by objective response rate (responders: CMR + PMR vs. non-responders: SMD + PMD) and disease control rate (disease control: CMR + PMR + SMD vs. no disease control: PMD).

Results: The mean age was 65 ± 6 years, with 94.3% male patients. Three received pembrolizumab and 32 nivolumab. Median OS after immunotherapy was 12 months (95% CI 8.9-15.1). Responders showed significantly better OS across all four PET/CT criteria. Disease control by PERCIST (HR 0.27, 95% CI 0.10-0.70, p = 0.007) and PERCIMT (HR 0.38, 95% CI 0.16-0.88, p = 0.023) was significantly associated with improved OS, unlike PECRIT and imPERCIST5. Overall concordance among the criteria was good (Fleiss' kappa: 0.70). Concordance was excellent for ORR evaluation (kappa: 0.92), but lower for DCR (kappa: 0.62).

Conclusion: In this retrospective exploratory study, PERCIST and PERCIMT demonstrated a stronger association with OS compared with PECRIT and imPERCIST5 when disease control was considered. While agreement across criteria was high for objective response assessment, concordance for disease control was lower.

Purpose: Glioblastoma (GB) is the most common and aggressive primary brain tumor in adults, with its significant inter- and intra-tumoral heterogeneity being a major factor in its treatment resistance and overall prognosis. GB diagnosis typically involves magnetic resonance imaging, confirmed by histology after surgical resection or biopsy. Recurrence is almost expected despite adjuvant therapies. Extracellular vesicles (EVs) may represent promising cancer biomarkers for diagnosis, prognosis, and therapeutic monitoring.

Methods: In this work, we monitored 21 GB patients at different time intervals performing a quantitative and dimensional analysis of plasma-derived EVs, with the aim of finding correlations with their clinical course.

Results: Our analyses revealed a slight correlation with patients' clinical conditions during follow-up, such as tumor time recurrence over time, but no significant difference in plasma EV concentration in GB patients and healthy control subjects (HC), contrary to previously published data.

Conclusions: Although based on a limited number of patients, our methodological study highlights the need for a universal analysis method to compare data from large patient populations in order to use EVs as a biomarker for the diagnosis of recurrence by liquid biopsy, especially in GB, a tumor known for its heterogeneity.

Introduction: The indicators of surgical outcomes are handy tools in health management. Futility is a very interesting indicator, because it defines those patients who have undergone a surgical procedure with its morbidity and mortality and who have not benefited from the treatment. Knowledge of the factors that influence futility can help us better select patients with carcinomatosis of ovarian origin.

Methods: Multicenter study was performed.

Inclusion criteria:  > 18 years old, with ovarian cancer and peritoneal carcinomatosis, who underwent scheduled surgery after response to neoadjuvant therapy. The definition of Futility in ovarian peritoneal carcinomatosis was: all patients with non-CC-0, death in the first 90 days in the postoperative period or within the first year after surgery were considered futile patients.

Results: We included 365 patients. 84 patients (23.6%) were in the futility group compared with 279 (73.4%) who were not in the futility group. We obtained that non-obtaining CC-0 was the main factor of futility (61.6%). The 2º crucial factor of futility was mortality in the first year after surgery. The incidence of futility in the series is 23.6%. Comparing futility and non-futility groups, we could observe statistically significant differences in hospital stay, higher levels of CA125 (52 vs. 35), and higher postoperative PCI. Patients in the futility group had almost twice PCIs as those who were not. When performing univariate regression, we could observe that PCI and the PCI distributed by categories (< 10; 11-20; > 20) were independent variables associated with futility.

Conclusion: PCI is a relevant factor in futility in ovarian cancer.

The evolution of cancer therapies has dramatically improved patient survival but has also revealed a critical challenge: the long-term genotoxic effects that can lead to secondary primary malignancies (SPMs). This review synthesizes current knowledge on how diverse treatment modalities, including chemotherapy, radiotherapy, targeted agents, and immunotherapies, induce DNA damage in normal tissues. It details the distinct mechanisms of genotoxicity, from the direct DNA lesions caused by cytotoxic drugs and ionizing radiation to the indirect damage mediated by oxidative stress and inflammation from newer therapies. The article identifies a range of multifactorial risk factors for SPMs, encompassing patient-specific variables such as age, genetic predisposition, and lifestyle, as well as therapy-related factors such as dose, duration, and combination regimens. It then evaluates the progression of monitoring methods, from traditional cytogenetic assays to advanced molecular and multi-omics biomarkers, highlighting their potential to predict individual susceptibility and inform risk stratification. By exploring pharmacogenomics and its role in genotype-guided dosing, the review proposes a framework for personalized prevention strategies. These strategies include risk-adapted regimens, prophylactic interventions, and the use of AI-driven predictive models. Ultimately, this comprehensive analysis underscores the urgent need to advance personalized prevention in oncology to balance therapeutic efficacy with long-term genomic safety for cancer survivors.

Ovarian cancer is a deadly gynecological malignancy, often detected late with frequent recurrence and treatment resistance. Non-coding RNAs, particularly long non-coding RNAs (lncRNAs), are now recognized as crucial regulators of cancer pathogenesis. This review synthesizes current literature to elucidate the molecular and functional roles of the lncRNA HAGLROS in ovarian cancer, focusing on its interactions within competing endogenous RNA (ceRNA) networks. HAGLROS, located at 2q31.1, is an oncogenic lncRNA that promotes ovarian cancer progression. It drives enhanced cell proliferation, metastasis, and chemotherapy resistance while inhibiting apoptosis. Its oncogenic activity is primarily mediated through intricate sponging interactions with microRNAs (miRNAs), disrupting post-transcriptional gene regulation and influencing epigenetic and transcriptional processes. The dysregulation of HAGLROS underscores its significant role in ovarian tumorigenesis. Its ability to modulate key cancer hallmarks via miRNA interactions reveals complex regulatory axes central to the disease's pathogenesis. HAGLROS represents a promising candidate for early diagnostic biomarkers and novel therapeutic interventions. Further investigation into the HAGLROS-miRNA-mRNA network is essential for defining its clinical utility and developing targeted treatments for ovarian cancer.

Purpose: To evaluate the disproportionality, time to onset, reporting frequency, and outcomes of hematologic AEs associated with trastuzumab deruxtecan (T-DXd) using data from the Japanese Adverse Drug Event Report database (JADER).

Methods: We analyzed data for the period from April 2004 to December 2024. Data on hematologic AEs were extracted, and the disproportionality of T-DXd-associated AEs was assessed by calculating reporting odds ratios.

Results: Among the 3,221,393 reports analyzed, 1561 were associated with T-DXd, including 433 hematologic AEs. Signals were detected for six AEs, including febrile neutropenia, anaemia, neutrophil count decreased, neutropenia, platelet count decreased, and myelosuppression. All had fatal cases, with particularly high fatality rates observed for febrile neutropenia and platelet count decreased. A histogram of median times to onset showed that febrile neutropenia and platelet count decreased typically occurred within 8 to 10.5 days after administration. Weibull distribution analysis indicated that febrile neutropenia showed an early-onset tendency (early failure type), whereas platelet count decreased occurred in a dose-dependent manner (wear-out failure type).

Conclusions: Some hematologic AEs associated with T-DXd can be fatal and may occur not only early in treatment but also later in the course. Continuous monitoring is essential for their timely detection and appropriate management.