Accurate prostate cancer (PCa) patient diagnosis and risk assessment are key to ensure the best outcome. Currently, low- and favorable intermediate-risk PCa patients may be offered AS due to the indolent nature of the disease. Nonetheless, deciding between active surveillance and curative-intent treatment remains an intricate task, as a subset of these patients may eventually progress, enduring poorer prognosis. Herein, we sought to construct risk calculators based on cancer biomarkers, enabling more accurate discrimination among patients which may benefit from active interventions.Ki67 immunoscore, GSTP1 and KLF8 promoter methylation levels (me) were assessed in PCa tissues. Study endpoints included overall and biochemical recurrence-free (BCR) survival. Combination with relevant clinicopathological parameters allowed for construction of graphical calculating tools (nomograms).Higher Ki67 index correlated with worse BCR-free survival, whereas higher KLF8me levels were associated with improved overall survival, especially in patients with lower-grade tumors. GSTP1me levels had no prognostic value. Among prognostic models tested, a BCR-risk calculator - ProstARK (including Ki67 and clinicopathologic parameters) - disclosed 79.17% specificity, 66.67% sensitivity, 55% positive predictive value, 86% negative predictive value, and 75.76% accuracy. Similar results were found using an independent PCa biopsy cohort, validating its prognostication ability.Combining clinicopathologic features and Ki67 index into a risk calculator enables easy and accurate implementation of a novel PCa prognostication tool. This nomogram may be useful for a more accurate selection of patients for active surveillance protocols. Nonetheless, validation in a larger, multicentric, set of diagnostic PCa biopsies is mandatory for further confirmation of these results.

UNASSIGNED: One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated.
UNASSIGNED: Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub).
UNASSIGNED: 113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa.
UNASSIGNED: We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.

Digital positron emission tomography/computed tomography (PET/CT) has shown enhanced sensitivity and spatial resolution compared with analog PET/CT. The present study compared the diagnostic performance of digital and analog PET/CT with [68Ga]Ga-PSMA-11 in prostate cancer patients who experienced biochemical recurrence (BCR) after prostatectomy. Forty prostate cancer patients who experienced BCR, defined as serum prostate-specific antigen (PSA) concentrations exceeding 0.2 ng/mL after prostatectomy, were prospectively recruited. These patients were stratified into three groups based on their serum PSA levels. [68Ga]Ga-PSMA-11 was injected into each patient, and images were acquired using both analog and digital PET/CT scanners. Analog and digital PET/CT showed comparable lesion detection rate (71.8% vs. 74.4%), sensitivity (85.0% vs. 90.0%), and positive predictive value (PPV, 100.0% vs. 100.0%). However, digital PET/CT detected more lesions (139 vs. 111) and had higher maximum standardized uptake values (SUVmax, 14.3 vs. 10.3) and higher kappa index (0.657 vs. 0.502) than analog PET/CT, regardless of serum PSA levels. On both analog and digital PET/CT, lesion detection rates and interrater agreement increased with increasing serum PSA levels. Compared with analog PET/CT, digital PET/CT detected more lesions with a higher SUVmax and better interrater agreement in prostate cancer patients who experienced BCR after prostatectomy.

BACKGROUND: 68Ga-PSMA PET/CT is superior to standard-of-care imaging for detecting regional and distant metastatic recurrent prostate cancer. The objective of our study was to evaluate the performance of 68Ga-PSMAPET/CT in our patient population, using the new PSMA-RADS version 2.0.
METHODS: A total of 128 patients scanned with 68Ga-PSMA PET/CT for detection of recurrence after RP were analyzed with PSMA-RADS version 2.0. For the analysis of the detection rate, categories PSMA-RADS 3 to 5 were considered as \"positive for malignancy\" and 1-2 as \"negative\".
RESULTS: According to PSMA-RADS v2.0, we classified patients as follows: 23 patients without PSMA-RADS because they were negative; PSMA-RADS 1: 10 patients; PSMA-RADS 2: 4 patients; PSMA-RADS 3A: 11 patients; PSMA-RADS 3B: 2 patients; PSMA-RADS 3C: 2 patients; PSMA-RADS 3D: 2 patients; PSMA-RADS 4: 13 patients; PSMA-RADS 5: 61 patients.
CONCLUSIONS: The overall detection rate of 68Ga-PSMA PET/CT was 71%. By dividing the patients into fourgroups according to PSA level before examination, we obtained the following detection rates: PSA < 0.2 ng/mL 38%; 0.2 ≤ PSA < 0.5 ng/mL 57%; 0.5 ≤ PSA ≤ 1 ng/mL 77%; and PSA > 1 ng/mL 95%.
CONCLUSIONS: Using PSMA-RADS version 2.0, we obtained detection rate values comparable with recent literature both in absolute terms and in relation to different PSA levels.

Oligometastatic patients at [18F]F-Fluorocholine (18F-choline) PET/CT may be treated with metastasis-directed therapy (MDT). The aim of this study was to combine radiomic parameters extracted from 18F-choline PET/CT and clinical data to build machine learning (ML) models able to predict MDT efficacy.
METHODS: Oligorecurrent patients (≤5 lesions) at 18F-choline PET/CT and treated with MDT were collected. A per-patient and per-lesion analysis was performed, using 2-year biochemical recurrence (BCR) after MDT as the standard of reference. Clinical parameters and radiomic features (RFts) extracted from 18F-choline PET/CT were used for training five ML Models for both CT and PET images. The performance metrics were calculated (i.e., Area Under the Curve-AUC; Classification Accuracy-CA).
RESULTS: A total of 46 metastases were selected and segmented in 29 patients. BCR after MDT occurred in 20 (69%) patients after 2 years of follow-up. In total, 73 and 33 robust RFTs were selected from CT and PET datasets, respectively. PET ML Models showed better performances than CT Models for discriminating BCR after MDT, with Stochastic Gradient Descent (SGD) being the best model (AUC = 0.95; CA = 0.90).
CONCLUSIONS: ML Models built using clinical parameters and CT and PET RFts extracted via 18F-choline PET/CT can accurately predict BCR after MDT in oligorecurrent PCa patients. If validated externally, ML Models could improve the selection of oligorecurrent PCa patients for treatment with MDT.

UNASSIGNED: Aurora kinase A (AURKA) and tumor-infiltrating lymphocytes (TILs) are both known to play an essential role in tumorigenesis. However, the expression and prognostic value of the AURKA and TILs in medullary thyroid carcinoma (MTC) have not yet been investigated.
UNASSIGNED: Surgical specimens and clinical data of 137 patients diagnosed with MTC were collected. AURKA expression and TILs infiltration were quantified by immunohistochemistry and hematoxylin-eosin staining. Subsequently, the prognostic value of AURKA expression and TIL infiltration in MTC was evaluated.
UNASSIGNED: AURKA was highly expressed in patients with multifocal tumor, cervical lymph node metastasis, and an advanced TNM stage, indicating a high probability of recurrence. AURKA further exhibited a positive correlation with TILs (R = 0.44, P < 0.001). High expression of AURKA combined with a low numbers of TILs (AURKAhigh/TILslow) was identified as an independent prognostic factor for biochemical recurrence (odds ratio: 4.57, 95% confidence interval: 1.54-14.66, P < 0.01) and recurrence-free survival (hazard ratio: 3.64, 95% confidence interval: 1.52-8.71, P < 0.001). The combination of AURKA and TILs apparently improves the prognostic value for biochemical recurrence (area under the curve: 0.751) and structural recurrence (area under the curve: 0.836) of MTC. Notably, AURKAhigh/TILslow demonstrated a high value for prediction of distant or unresectable locoregional recurrence, with an overall accuracy of 86.9%.
UNASSIGNED: AURKAhigh is associated with the MTC malignancy. The combination of AURKAhigh/TILslow was identified as novel independent prognostic marker in MTC, predicting incurable disease recurrence with high accuracy.

BACKGROUND: Considering the age relevance of prostate cancer (PCa) and the involvement of the cGAS-STING pathway in aging and cancer, we aim to classify PCa into distinct molecular subtypes and identify key genes from the novel perspective of the cGAS-STING pathway. It is of significance to guide personalized intervention of cancer-targeting therapy based on genetic evidence.
METHODS: The 430 patients with PCa from the TCGA database were included. We integrated 29 key genes involved in cGAS-STING pathway and analyzed differentially expressed genes and biochemical recurrence (BCR)-free survival-related genes. The assessments of tumor stemness and heterogeneity and tumor microenvironment (TME) were conducted to reveal potential mechanisms.
RESULTS: PCa patients were classified into two distinct subtypes using AURKB, TREX1, and STAT6, and subtype 1 had a worse prognosis than subtype 2 (HR: 21.19, p < 0.001). The findings were validated in the MSKCC2010 cohort. Among subtype 1 and subtype 2, the top ten mutation genes were MUC5B, DNAH9, SLC5A10, ZNF462, USP31, SIPA1L3, PLEC, HRAS, MYOM1, and ITGB6. Gene set variation analysis revealed a high enrichment of the E2F target in subtype 1, and gene set enrichment analysis showed significant enrichment of base excision repair, cell cycle, and DNA replication in subtype 1. TME evaluation indicated that subtype 1 had a significantly higher level of T cells follicular helper and a lower level of plasma cells than subtype 2.
CONCLUSIONS: The molecular subtypes mediated by the cGAS-STING pathway and the genetic risk score may aid in identifying potentially high-risk PCa patients who may benefit from pharmacologic therapies targeting the cGAS-STING pathway.

BACKGROUND: The 17-gene Genomic Prostate Score (GPS) test has been clinically employed to predict adverse prognosis in prostate cancer. In this meta-analysis, we aimed to evaluate the prognostic value of the 17-gene GPS in patients with prostate cancer.
METHODS: Potentially relevant studies were obtained by searching PubMed, Web of Science, Embase databases from their inception to December 1, 2023. Studies were considered eligible if they evaluated the association of the 17-gene GPS with distant metastases, biochemical recurrence, or prostate cancer-specific mortality (PCSM) in prostate cancer patients. To estimate the prognostic value, we pooled the adjusted hazard ratio (HR) with 95% confidence intervals (CI) for the high versus low GPS group or per 20-unit increase in GPS.
RESULTS: Seven cohort studies that reported on 8 articles comprising 1,962 patients satisfied the eligibility criteria. Meta-analysis showed that per 20-unit increase in GPS was significantly associated with distant metastases (HR 2.99; 95% CI 1.97-4.53), biochemical recurrence (HR 2.18; 95% CI 1.64-2.89), and PCSM (HR 3.14; 95% CI 1.86-5.30). Moreover, patients with high GPS (> 40 points) had an increased risk of distant metastases (HR 5.22; 95% CI 3.72-7.31), biochemical recurrence (HR 4.41; 95% CI 2.29-8.49), and PCSM (HR 3.81; 95% CI 1.74-8.33) than those with low GPS (≤ 40 points).
CONCLUSIONS: A higher 17-gene GPS significantly predicts distant metastases, biochemical recurrence, and PCSM in men with clinically localized prostate cancer. However, large-scale multicenter prospective studies are necessary to further validate these findings.

18F-rhPSMA-7.3 (18F-flotufolastat) is a high-affinity prostate-specific membrane antigen-targeted diagnostic radiopharmaceutical for PET imaging in patients with prostate cancer. Here, we report findings from the SPOTLIGHT study (NCT04186845), assessing the performance of 18F-flotufolastat PET/CT for identifying prostate-specific membrane antigen-positive lesions confirmed by standard of truth (SoT) in men with biochemical recurrence of prostate cancer and negative conventional imaging at baseline. Methods: Men with biochemical recurrence received 296 MBq of 18F-flotufolastat intravenously and then underwent PET/CT 50-70 min later. 18F-flotufolastat PET/CT findings were evaluated by 3 masked central readers and verified using histopathology or follow-up confirmatory imaging (CT, MRI, bone scan, or 18F-fluciclovine PET/CT) as the SoT. The present analysis evaluated all patients who had negative conventional imaging at baseline, underwent 18F-flotufolastat PET/CT, and had SoT verification by histopathology or follow-up confirmatory imaging to report detection rate (DR), which is the number of patients with at least 1 PET-positive lesion, divided by the number of evaluable patients, and verified DR (VDR), which is the proportion of patients with at least 1 true-positive lesion as verified by SoT, of all patients scanned (PET-positive and PET-negative scans). DR and VDR were calculated and stratified according to prior therapy. Majority read data (agreement between ≥2 readers) are reported. Results: In total, 171 patients with negative baseline conventional imaging and SoT by histopathology or post-PET confirmatory imaging were evaluated. By majority read, the overall 18F-flotufolastat DR among these patients was 95% (163/171; 95% CI, 91.0%-98.0%), and 110 of 171 of these patients had at least 1 true-positive lesion identified (VDR, 64%; 95% CI, 56.7%-71.5%). In the postprostatectomy group (133/171), 8.3% of patients had at least 1 true-positive lesion in the prostate bed, 28% in pelvic lymph nodes, and 35% in other sites. Among those who had received radiotherapy (36/171), 50% of patients had true-positive detections in the prostate, 8.3% in pelvic lymph nodes, and 36% in other sites. Conclusion: 18F-flotufolastat frequently identified true-positive prostate cancer lesions in patients with negative conventional imaging. 18F-flotufolastat may help to better define sites of disease recurrence and inform salvage therapy decisions than does conventional imaging, potentially leading to improved outcomes.

Ovarian cancer is a prevalent malignant tumor of the female reproductive system, often remaining concealed until it reaches an advanced stage. The standard treatment protocol includes cytoreductive surgery for ovarian cancer plus postoperative consolidation chemotherapy and maintenance therapy, although it carries a high recurrence rate. During the treatment period, chemotherapy can lead to bone marrow suppression, a condition known as Chemotherapy-Induced Myelosuppression (CIM). This suppression may necessitate dose reduction or chemotherapy treatment cycle delay. In severe cases, CIM can result in infection, fever, and potential harm to the patient\'s life. Here, we report a case of a female patient with ovarian malignant tumor of biochemical recurrence who treated with chemotherapy combined with Trilaciclib, following previous perioperative chemotherapy with occurrence of severe CIM. It involves an intravenous injection of Trilaciclib before chemotherapy, which significantly abates the side effects of chemotherapy, reduces the occurrence of severe CIM, improves the patients\' quality of life, and decreases the economic burden of hospitalization. We hope that this retrospective analysis of the case may serve as a reference in preventing and treating severe CIM during chemotherapy in some patients with malignant tumors, ultimately benefiting more patients with tumors.