Clinical & Translational Oncology最新文献

Cervical cancer (CC) is the fourth most common cancer and the fourth leading cause of mortality in women worldwide. It is strongly associated with high-risk human papillomavirus infection. High-income countries that have implemented human papillomavirus (HPV) vaccination and screening programs have seen dramatic reductions in CC incidence, while developing countries where these programs are not available continue to experience high rates of CC deaths. In early-stage CC, the primary treatment is surgery or radiotherapy, whereas concurrent chemo-radiotherapy (CRT) remains the conventional approach in locally advanced stages until the upcoming approval of immunotherapy. The incorporation of immunotherapy in combination with chemotherapy (with or without bevacizumab) in first line and as monotherapy in second line after platinum-based chemotherapy, has significantly increased overall survival (OS) in recurrent or metastatic CC. The purpose of this guideline is to summarize the most relevant evidence in the diagnosis, treatment, and follow-up of CC and to provide evidence-based recommendations for clinical practice.

Objective: The purpose of this retrospective analysis was to evaluate the clinical presentations, radiological characteristics, patient outcomes, and therapeutic approaches among individuals diagnosed with primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and metastatic brain tumors (METS).

Methods: We assembled a cohort of brain tumor patients from two medical centers, with two oncologists independently reviewing their clinical profiles. A retrospective examination of 87 PCNSL, 87 HGG, and 71 METS cases was performed to assess the aforementioned parameters.

Results: Notable variations were identified in the incidence of epileptic seizures and cognitive impairments between PCNSL and METS patients. Cerebral hemisphere involvement was predominantly observed in HGG and METS cases. PCNSL cases exhibited a higher likelihood of multiple lesions, whereas HGG showed a greater tendency for recurrence. The median survival times were established at 24.3 months for PCNSL, 44.5 months for HGG, and 27.1 months for METS patients. In PCNSL cases, the number of lesions was identified as a significant predictor of mortality (P = 0.008).

Conclusions: Our findings highlight the importance of clinical and imaging features in diagnosing PCNSL, which may present distinct features compared to HGG and METS.

Objective: Glioblastoma (GBM), one of the most common brain tumors, is known for its low survival rates and poor treatment responses. This study aims to create a robust predictive model that integrates multiple feature types, including clinical data, RNA expression, and tumor microenvironment data, using fusion techniques to enhance model performance.

Methods: We obtained data from the SEER database to assess the impact of nine demographic and clinical features on the survival of 58,495 GBM patients and built predictive machine learning models. Additionally, mRNA expression data from 600 GBM patients from TCGA, CGGA, and GEO were analyzed. We used Cox regression and LASSO to create a gene signature, which was compared against 13 published signatures for accuracy. Twenty-one machine learning models were applied to predict survival at multiple time points. Finally, we integrated multiple feature types using fusion techniques and developed a Shiny app to provide survival predictions for GBM patients.

Results: Using the SEER database, we constructed machine learning models based on nine clinical variables: age, gender, marital status, race, tumor site, laterality, surgery, chemotherapy, and radiation therapy. The best-performing model achieved AUC values of 0.775, 0.728, 0.692, and 0.683 for predicting survival at 6, 12, 18, and 24 months in the testing cohort. In the merged TCGA, CGGA, and GEO cohorts, we identified 11 genes to develop predictive models. These 11 genes outperformed 13 other published gene signatures in predicting the prognosis of GBM. When incorporating mRNA features, tumor microenvironment features, and clinical variables into the fusion models, the AUC values for predicting survival at 6, 12, 18, and 24 months were 0.641, 0.624, 0.655, and 0.637, respectively. A user-friendly tool for predicting the survival curve of individual GBM patients is available at https://zzubioinfo.shinyapps.io/mlGBM/ .

Conclusions: Our study provides a web-based tool that includes two modules: one for predicting survival curves using only clinical variables, and another that integrates multiple feature types for more comprehensive predictions.

Shugoshin 1 (SGO1) is one of the Shugoshin (guardian spirit) family proteins, which is reported to be majorly involved in the protection of centromeres and proper segregation of chromosomes during cell division. Recent studies found that the altered expression of SGO1 is associated with various cancers and genetic disorders, and suggested as a target for therapy. In the present study, we have reviewed the available literature on SGO1 gene and protein expression in various cancer-cell lines, animal models and cancer patients, and targeting SGO1 with siRNA/shRNA. A significant increase in the expression of SGO1 mRNA and protein levels were observed in prostate, renal, lung, breast, neuroblastoma, leukemia, hepatocellular, and colon cancer-cell lines and the levels were associated with increased cellular proliferation, invasion, and metastasis. The altered SGO1 levels were observed in SGO1 knockout/haploinsufficient mice compared to wild type and the levels were associated with increased chromosome instability and tumorigenesis. Consistent with cell lines, higher SGO1 expression was also observed in tumor tissues of cancer patients compared to adjacent normal tissue and the levels were positively correlated with tumor stage, grade, size, and hormonal status. Higher SGO1 expression was related to resistance to chemotherapeutic agents and the knockdown of SGO1 increased sensitivity to those agents. Furthermore, targeting SGO1 with siRNA/shRNA reduced the expression of SGO1 and proliferation, and induced apoptosis of cancer cells. Overall, the SGO1 expression levels were significantly higher in various cancers, and targeting SGO1 with siRNA and shRNA reduced the levels of SGO1, proliferation and metastasis of cancers.

Purpose: Detecting spinal metastases is highly relevant in patients with oncological disorders as it can affect the staging and treatment of their disease. We aimed to evaluate the diagnostic performance of computed tomography (CT), magnetic resonance imaging (MRI), FDG positron emission tomography (PET)/CT, bone scintigraphy (BS), and single-photon emission computed tomography (SPECT) for spinal metastases detection.

Methods: Medline, EMBASE, and Web of Science were systematically searched until March 2024 for diagnostic accuracy studies on spinal metastases detection (PROSPERO-registration: CRD42024540139). Data extraction and quality assessment using the QUADAS-2 tool were performed by two independent reviewers. Using bivariate random effects modeling, pooled sensitivities, specificities, and diagnostic odds ratios (DOR) were calculated, and hierarchical summary operating curves were constructed.

Results: Twenty-five studies (49 datasets), encompassing 3102 patients were included. Per-patient pooled sensitivities of CT, MRI, PET/CT, BS and SPECT were 70%, 93%, 82%, 75%, and 84%, respectively. Pooled specificities were 74%, 85%, 75%, 92%, and 81%, respectively. Per-lesion pooled sensitivities of CT, MRI, PET/CT, BS and SPECT were 76%, 91%, 92%, 77%, and 92%, respectively. Pooled specificities were 91%, 94%, 85%, 52%, and 86%, respectively. MRI had the highest DOR in per patient and lesion analyses.

Conclusion: MRI had highest diagnostic accuracy for spinal metastases detection on patient and lesion level, suggesting a broader use in addition to the routine staging CT, at least in patients at high risk and where the detection of a spinal metastasis could alter therapy decisions. Herein, results should be considered with the limitations of each modality.

Purpose: Breast cancer is a leading cause of cancer-related deaths among women worldwide. The presence and function of CD8 + T cells in the tumor microenvironment have been associated with better patient outcomes. Drug toxicity has posed a significant challenge to the clinical implementation of chemotherapy-based strategies in cancer treatment.

Methods: In this study, we employed flow cytometry to investigate the potential synergistic immunomodulatory effects on CD8 + T cells in a mouse model of breast cancer by combining metformin, an anti-diabetic medication, with doxorubicin.

Results: Through flow cytometry analysis, we observed that the combination of the two drugs led to an increased percentage of CD8 + T cells compared to either drug alone. The modulation of HIF-1α and  STAT3 gene expression in the combination group further confirmed the efficacy of this approach.

Conclusions: Our findings suggest that combining metformin with doxorubicin can enhance the anticancer activity of doxorubicin and decrease its cytotoxicity in a 4T1 breast cancer mouse model.

Aim: To assess for the first time the safety and feasibility of combining photon-intraoperative radiotherapy (ph-IORT) with hypofractionated whole breast irradiation (h-WBI) in patients referred to primary systemic therapy (PST).

Methods: From March 2019 to December 2020, patients referred for breast conservative surgery (BCS) after PST in our institution were prospectively included in the present trial. PST was prescribed to all patients according the ESMO-SEOM guidelines. Once the PST was completed, BCS was discussed in the multidisciplinary tumor board (MTB). 20 Gy were prescribed to the surface of the applicator of an Intrabeam®photon-IORT during BCS. h-WBI (40.5 Gy/2.67 Gy/15frx) was planned to be administered 3-5w after BCS. All patients were treated with hWBI VMAT-Rapid-Arc&Daily Exac-Trac-IGRT. The primary end points of the study were feasibility and safety (grade 3 toxicity rate CTCAE.5.0-scale) of the proposed treatment protocol. The secondary end points included cosmetic results (Harvard Scale), local relapse rate and overall survival.

Results: Thirty-five patients were included in the trial. The median age was 54 years. Tumor size was > 2 cm in all cases. Eighteen patients were N + (51.4%). There was no disease progression during PST. All patients received the planned 20 Gy-ph-IORT boost at the time of BCS and the proposed h-WBI. 31/35 (88,6%) patients started h-WBI within the predefined time period (3-5w after BCS). No patient showed ≥ G3 acute toxicity 3 months after the end of h-WBI. No ≥ G3 late toxicity was observed at 12 months of follow-up and thereafter. Cosmetic results were scored excellent/good in 26 patients (74.2%). After a median follow-up of 52 months, a TNBC patient locally relapsed at 13 months of follow-up.

Conclusion: We demonstrated for the first time that ph-IORT + hWBI is feasible and safe in patients referred to BCS after PST.

Background: Geriatric patients account for nearly half of new colorectal cancer (CRC) cases. This study compares clinicopathological features, treatments, outcomes, and frailty in elderly (≥ 70) and younger (< 70) CRC patients at our center.

Materials and methods: Patients diagnosed with non-metastatic or de novo metastatic CRC between January 2015 and April 2024 were included. Demographic, pathological, and survival data were retrospectively collected. Analyses were performed using SPSS version 25, with statistical significance set at P < 0.05.

Results: Of the 414 non-metastatic CRC patients, 26.6% were aged ≥ 70. Elderly patients received less perioperative chemotherapy (60% vs. 81.6%, P < 0.001) and had more dose reductions (41.6% vs. 19.2%, P < 0.001). Frailty reduced perioperative chemotherapy in elderly non-metastatic patients (54.5% vs. 92.1%, P < 0.001) but did not affect dose reduction (37.9% vs. 33.3%, P = 0.764) or treatment duration (median 24 weeks for both groups, P = 0.909). In metastatic patients, frailty shortened chemotherapy duration (9.5 vs. 15.5 weeks, P = 0.129). Elderly patients had lower 5- and 8-year overall survival (OS) rates (64.7%, 60.1% vs. 83.0%, 78.8%, P = 0.004). In the de novo metastatic cohort (135 patients), age did not affect OS (19.4 vs. 17.3 months, P = 0.590) or PFS (9.8 vs. 7.5 months, P = 0.209). Rectal cancer (HR: 2.751, P = 0.005) and early chemotherapy termination (HR: 4.138, P < 0.001) worsened OS in non-metastatic CRC, while absence of RAS (HR: 2.043, P = 0.047), BRAF mutations (HR: 8.263, P = 0.010), and metastasectomy (HR: 3.650, P = 0.036) improved OS in metastatic CRC.

Conclusion: Age does not independently worsen CRC survival, though early chemotherapy discontinuation impacts outcomes. Reduced-dose chemotherapy or monotherapy can help minimize adverse effects in elderly patients.

Lung cancer (LC) is the leading cause of cancer-related deaths and the second most commonly diagnosed malignancy worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell LC (LUSCC) are the most common subtypes of non-small cell LC (NSCLC). Early diagnosis of LC can be challenging due to a lack of biomarkers. The overall survival (OS) of patients with NSCLC is still poor despite the enormous efforts that have been made to develop novel treatments. Understanding fundamental molecular and genetic mechanisms is necessary to develop new therapeutic approaches for NSCLC. A recently identified type of programmed cell death known as ferroptosis is one potential approach. Ferroptosis causes oxidative damage and the death of cancerous cells by peroxidizing unsaturated phospholipids and accumulating reactive oxygen species (ROS) in an iron-dependent manner. Ferroptosis-related gene (FRG) signatures have recently been evaluated for their ability to predict patient OS and prognosis. These analyses show FRGs are involved in cancer progression, and may serve as promising biomarkers for tumor diagnosis and therapy. Moreover, we summarize the current pharmaceutical options of ferroptosis induction and their underlying molecular mechanism in LC. Therefore, this review aims to provide a comprehensive summary of FRG-based prognostic models, their associated metabolic and signaling pathways, and promising therapeutic options for ferroptosis induction in NSCLC.

Esophageal cancer (EC) ranks among the most prevalent cancers worldwide, with a particularly high incidence in the Asian population. Due to the inconspicuous nature of early symptoms, patients with esophageal cancer are typically diagnosed in the middle to late stages, resulting in suboptimal overall treatment outcomes. Consequently, there is an urgent need to explore and refine therapeutic strategies. Microorganisms have been identified in numerous tumor tissues, including EC, and these microorganisms are referred to as the intratumoral microbiome. Intratumoral microbiota and their metabolic byproducts can influence the progression and treatment of esophageal cancer through various mechanisms, such as modulating tumor cell metabolism and local immune responses. Therefore, the intratumoral microbiota may potentially serve as a target for the treatment of esophageal cancer. This review delineates the composition, origin, and diagnostic significance of intratumoral microbiota in esophageal cancer tissue, and discusses the mechanisms by which intratumoral microbiota contribute to the onset of esophageal cancer. In addition, the impact of intratumoral microbiota on the treatment of esophageal cancer and its intervention measures are also addressed.