Cancers

Packed red blood cell (PRBC) transfusions are an important part of supportive treatment in oncology; however, when used frequently, they can be a result of transfusion-related iron overload. The aim of the study was to evaluate the role of ferritin as a non-specific marker of neoplastic growth and transfusion-related iron overload in children with lymphomas and solid tumors. We performed a longitudinal analysis of PRBC transfusions and changes in ferritin concentrations during oncological treatment of 88 children with lymphomas and solid tumors. A ferritin concentration above 500 ng/mL was diagnosed in 14.77% of patients at the moment of admission and 18.18% at the end of treatment. No differences were shown in serum ferritin in the context of tumor type-, sex-, and transfusion-related parameters. Those above the age of 10 demonstrated higher ferritin concentrations compared to subjects younger than 5 years of age. In addition, those over than 10 years old or above 30 kg in weight showed a tendency for better survival. All tested patients demonstrated highly significant correlations between ferritin at the 15th month of treatment or after therapy discontinuation and transfusion-related parameters. Interestingly, ferritin levels were found to lower back to the values before therapy shortly after its discontinuation. Transfusion parameters and ferritin levels had no influence on the survival of the studied cancer patients.

Background/Objectives: Colorectal cancer (CRC) with hepatic (CRLM) and pulmonary metastases (CRLU) presents a significant clinical challenge, leading to poor prognosis. Surgical resection of these metastases remains controversial because of limited evidence supporting its long-term benefits. To evaluate the impact of surgical resection of both hepatic and pulmonary metastases on long-term survival in patients with multivisceral metastatic colorectal cancer, this retrospective cohort study included 192 patients with UICC stage IV CRC treated at a high-volume academic center. Methods: Patients were divided into two groups: those who underwent surgical resection of both hepatic and pulmonary metastases (n = 100) and those who received non-surgical treatment (n = 92). Propensity score matching was used to adjust for baseline differences. The primary outcome was overall survival (OS). Results: Unadjusted analysis showed a significant OS benefit in the surgical group (median OS: 6.97 years) compared with the conservative group (median OS: 2.17 years). After propensity score matching, this survival advantage persisted (median OS: 5.58 years vs. 2.35 years; HR: 0.3, 95% CI: 0.18–0.47, p < 0.0001). Conclusions: Surgical resection of hepatic and pulmonary metastases in multivisceral metastatic CRC significantly improves long-term survival, supporting an aggressive surgical approach in selected patients.

Background/Objectives: The purpose of this study was to investigate preoperative interhemispheric differences of the FAT in relation to the onset of postoperative SMA syndrome. Methods: This was a single-center retrospective analysis of patients who underwent surgical resection of diffuse gliomas involving the SMA between 2018 and 2022. Inclusion criteria were availability of preoperative and postoperative Magnetic Resonance Imaging, no previous surgery, and no neurological deficits at presentation. Diffusion-weighted data were processed by spherical deconvolution (SD) and diffusion tensor imaging tractography algorithms, and TrackVis was used to dissect the FAT of both hemispheres. The FAT data were analyzed for correlation with postoperative SMA syndrome onset. Results: N = 25 cases were included in the study, among which n = 23 had preoperative bilaterally identifiable FAT by SD. N = 12 developed an SMA syndrome, 6 demonstrated a motor-only syndrome, 4 had a verbal-only syndrome, and 2 had mixed verbal and motor features. The SMA syndrome incidence was significantly more frequent in lower-grade gliomas (p = 0.005). On the tumor side, the FAT identified by SD was smaller than the contralateral (mean volume 6.53 cm3 and 13.33 cm3, respectively, p < 0.001). In the 6 cases that developed a verbal SMA syndrome, a normalized FAT volume asymmetry (FAT-VA) demonstrated an asymmetry shifted towards the non-dominant side (mean FAT-VA = −0.68), while the cases with no postoperative verbal impairment had opposite asymmetry towards the dominant side (mean FAT-VA = 0.42, p = 0.010). Conclusions: Preoperative interhemispheric FAT volume asymmetry estimated according to functional dominance can predict postoperative onset of verbal SMA syndrome, with proportionally smaller FAT on the affected dominant hemisphere.

Breast cancer has been one of the main causes of death among women recently, and it has been the focus of attention of many specialists and researchers in the health field. Because of its seriousness and spread speed, breast cancer-resisting methods, early diagnosis, diagnosis, and treatment have been the points of research discussion. Many computers-aided diagnosis (CAD) systems have been proposed to reduce the load on physicians and increase the accuracy of breast tumor diagnosis. To the best of our knowledge, combining patient information, including medical history, breast density, age, and other factors, with mammogram features from both breasts in craniocaudal (CC) and mediolateral oblique (MLO) views has not been previously investigated for breast tumor classification. In this paper, we investigated the effectiveness of using those inputs by comparing two combination approaches. The soft voting approach, produced from statistical information-based models (decision tree, random forest, K-nearest neighbor, Gaussian naive Bayes, gradient boosting, and MLP) and an image-based model (CNN), achieved 90% accuracy. Additionally, concatenating statistical and image-based features in a deep learning model achieved 93% accuracy. We found that it produced promising results that would enhance the CAD systems. As a result, this study finds that using both sides of mammograms outperformed the result of using only the infected side. In addition, integrating the mammogram features with statistical information enhanced the accuracy of the tumor classification. Our findings, based on a novel dataset, incorporate both patient information and four-view mammogram images, covering multiple classes: normal, benign, and malignant.

Background and Objectives: Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. Methods: In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibodies, CYFRA 21-1, and anti-CYFRA 21-1 autoantibodies in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. Results: The test demonstrated a sensitivity of 78.4% (95% CI: 75.7–81.1) and specificity of 93.1% (95% CI: 90.0–96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. Conclusions: The Lung Cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.

Background: The aim of this study was to determine the differences in diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE) parameters between patients with peritoneal high-grade serous ovarian cancer (HGSOC) recurrence with BRCA mutations (BRCAmut) or BRCA wild type (BRCAwt). Materials and Methods: We retrospectively analyzed the abdominal and pelvic magnetic resonance (MR) images of 43 patients suspected of having recurrent HGSOC, of whom 18 had BRCA1/2 gene mutations. Patients underwent MRI examination via a 1.5 T MRI scanner, and the analyzed parameters were as follows: apparent diffusion coefficient (ADC), time to peak (TTP) and perfusion maximum enhancement (Perf. Max. En.). Results: The mean ADC in patients with BRCAwt was lower than that in patients with BRCAmut: 788.7 (SD: 139.5) vs. 977.3 (SD: 103), p-value = 0.00002. The average TTP value for patients with BRCAwt was greater than that for patients with mutations: 256.3 (SD: 50) vs. 160.6 (SD: 35.5), p-value < 0.01. The Perf. Max. En. value was lower in the BRCAwt group: 148.6 (SD: 12.3) vs. 233.6 (SD: 29.2), p-value < 0.01. Conclusion: Our study revealed a statistically significant correlation between DWI and DCE parameters in examinations of peritoneal metastasis in patients with BRCA1/2 mutations. Adding DCE perfusion to the MRI protocol for ovarian cancer recurrence in patients with BRCAmut may be a valuable tool.

Glioblastoma (GBM) is the most common primary brain malignancy in the U.S. with a 5-year overall survival < 5% despite an aggressive standard of care. Laser interstitial thermal therapy (LITT) is a surgical approach to treating GBM that has gained traction, providing a safe option for reducing intracranial tumor burden. LITT is believed to potentially modulate GBM immune responses; however, the biochemical mechanisms underlying the modulation of immune checkpoints in GBM cells have been poorly characterized. The present study aimed to preliminarily evaluate the effects of thermal therapy and radiation on PD-L1 modulation in vitro, as a function of IDH mutational status. U87 cells and their IDH-mutant counterpart (U87R132H), which was generated using a crispr-cas9 knock-in approach, were utilized for this preliminary evaluation. Cell heating was achieved by harvesting with trypsin centrifugation where the cell pellets were treated on a heat block for the associated time and temperature. Following thermal therapy, cells were resuspended and irradiated using a 37-Cesium irradiator at 0.6 Gy min−1. Immediately following treatment, cells were either plated as single cells to allow colonies to form, and stained with Coomassie blue to be counted approximately 10–14 days later or harvested for Western blot analysis. Cell lysates were analyzed for PD-L1 expression with respect to various iron metabolic parameters (mortalin (HSPA9), transferrin receptor, and ferritin heavy chain) using a Western blotting approach. In both U87 and U87R132H cell lines, thermal therapy showed a temperature-dependent cell-killing effect, but U87R132H cells appeared more sensitive to thermal treatment when treated at 43 °C for 10 min. Moreover, thermal therapy had minimal effects on cell responses to 2 Gy irradiation. Treatment with thermal therapy downregulated PD-L1 expression in U87R132H cells, which was associated with increased expression of the mitochondrial iron metabolic enzyme, HSPA9. Thermal therapy reversed the radiation-induced overexpression of PD-L1, transferrin receptor, and ferritin heavy chain in U87R132H cells. No effects were observed in wild-type U87 cells. Moreover, Ga(NO3)3 depleted mitochondrial iron content which, in turn, significantly enhanced the sensitivity of U87R132H cells to thermal therapy and 2 Gy irradiation and caused a significant increase in PD-L1 expression. These results suggest that thermal therapy alone can modulate the immune checkpoint PD-L1. This effect was more pronounced when thermal therapy was combined with radiation. Mechanistically, mitochondrial iron trafficking through HSPA9 may coordinate the regulation of PD-L1 in the context of thermal therapy and ionizing radiation, which can be targeted with gallium-based therapy. These novel, preliminary findings warrant further mechanistic investigations in pre-clinical models of LITT.

Background/Objectives: Head and neck cancer (HNC) is among the most common cancer types globally, with its incidence expected to increase significantly in the coming years. Oral squamous cell carcinoma (OSCC), the predominant subtype, exhibits significant heterogeneity and resistance to treatment. Current therapies, including surgery, radiation, and chemotherapy, often result in poor outcomes for advanced stages. Cetuximab, an EGFR inhibitor, is widely used but faces limitations. This study explores the combined inhibition of EGFR and mitotic proteins to enhance treatment efficacy. Methods: We analyzed the effects of co-treating OSCC cells with small molecules targeting MPS-1 (BAY1217389), Aurora-B (Barasertib), or KSP (Ispinesib), alongside Cetuximab. The rationale is based on targeting EGFR-mediated survival pathways and the mitotic checkpoint, addressing multiple cell cycle phases and reducing resistance. Results: Our findings indicate that inhibiting MPS-1, Aurora-B, or KSP enhances Cetuximab’s therapeutic potential, promoting increased cancer cell death. Additionally, we examined EGFR, MPS-1, Aurora-B, and KSP expression in OSCC patient samples, revealing their clinicopathologic significance. Conclusions: This combinatorial approach suggests a promising strategy to improve treatment outcomes in OSCC.

Melanoma remains a formidable challenge in oncology, causing the majority of skin cancer deaths in the United States, with brain metastases contributing substantially to this mortality. This paper reviews the current therapeutic strategies for melanoma brain metastases, with a focus on delayed and concurrent stereotactic radiosurgery (SRS). While surgery and traditional chemotherapy offer limited efficacy, recent advances in immunotherapy, particularly immune checkpoint inhibitors (ICIs), have played a major role in the advancement and improved efficacy of the treatment of cancers, including brain metastases. Recent studies indicate that monotherapy with ICIs may lead to a higher median overall survival compared to historical benchmarks, potentially allowing patients to delay radiosurgery. Other studies have found that combining SRS with ICIs demonstrates promise, with results indicating improved intracranial control. Ongoing clinical trials explore novel combinations of immunotherapies and radiotherapies, aiming to optimize treatment outcomes while minimizing adverse effects. As treatment options expand, future studies will be necessary to understand the interplay between therapies and their optimal sequencing to improve patient outcomes.

Background/Objectives: To evaluate an end-to-end pipeline for normo-fractionated prostate-only and whole-pelvic cancer treatments that requires minimal human input and generates a machine-deliverable plan as an output. Methods: In collaboration with TheraPanacea, a treatment planning pipeline was developed that takes as its input a planning CT with organs-at-risk (OARs) and planning target volume (PTV) contours, the targeted linac machine, and the prescription dose. The primary components are (i) dose prediction by a single deep learning model for both localizations and (ii) a direct aperture VMAT plan optimization that seeks to mimic the predicted dose. The deep learning model was trained on 238 cases, and a held-out set of 86 cases was used for model validation. An end-to-end clinical evaluation study was performed on another 40 cases (20 prostate-only, 20 whole-pelvic). First, a quantitative evaluation was performed based on dose–volume histogram (DVH) points and plan parameter metrics. Then, the plan deliverability was assessed via portal dosimetry using the global gamma index. Additionally, the reference clinical manual plans were compared with the automated plans in terms of monitor unit (MU) numbers and modulation complexity scores (MCSv). Results: The automated plans provided adequate treatment plans (or minor deviations) with respect to the dose constraints, and the quality of the plans was similar to the manual plans for both localizations. Moreover, the automated plans showed successful deliverability and passed the portal dose verification. Despite higher median total MUs, no statistically significant correlation was observed between any of the gamma criteria tested and the number of MUs or MCSv. Conclusions: This study shows the feasibility of a deep learning-based fully automated treatment planning pipeline that generates high-quality plans that are competitive with manually made plans and are clinically approved in terms of dosimetry and machine deliverability.