BACKGROUND: The Proactive Molecular Risk Classifier for Endometrial Cancer has identified four risk groups for the prognosis of endometrial cancer. Lenvatinib plus pembrolizumab was recently approved as a second-line treatment for unresectable endometrial cancer, but reports in clinical practice are lacking. The relationship between the efficacy of lenvatinib/pembrolizumab and Proactive Molecular Risk Classifier for Endometrial Cancer classification is unclear.
METHODS: This single-centre retrospective study included patients who underwent lenvatinib/pembrolizumab therapy at Iwate Medical University Hospital between January 2022 and March 2023. Formalin-fixed paraffin-embedded specimens obtained from patients before treatment were collected and classified into the mismatch repair-deficient, p53 abnormal and no specific molecular profile subtypes using immunohistochemistry. The response rate, progression-free survival and adverse events were evaluated using electronic medical records. The study was approved by the hospital\'s ethics committee (approval number: MH2022-093).
RESULTS: This study enrolled 20 patients, who underwent a median follow-up of 17.8 months (95% confidence interval: 16.6-18.9). The best overall response rate was 60.0% (36.1-80.9), and the median progression-free survival was 11.6 months (2.9-20.3). The median progression-free survival in the p53 abnormal group (n = 9) was 3.4 months (3.0-3.8); however, progression-free survival did not reach the median (P < 0.001) in the mismatch repair-deficient/no specific molecular profile group (n = 11). Symptomatic immune-related adverse events (except hypothyroidism) occurred in 4/20 (25.0%) patients, and partial responses were observed in all cases. No treatment-related deaths occurred.
CONCLUSIONS: The p53abn group in the Proactive Molecular Risk Classifier for Endometrial Cancer classification has a poor prognosis even after treatment with lenvatinib/pembrolizumab.

[This corrects the article DOI: 10.3389/fmed.2022.1051309.].

BACKGROUND: Recently approved treatments and updates to genetic testing recommendations for prostate cancer have created a need for correlated analyses of patient outcomes data via germline genetic mutation status. Genetic registries address these gaps by identifying candidates for recently approved targeted treatments, expanding clinical trial data examining specific gene mutations, and understanding effects of targeted treatments in the real-world setting.
METHODS: The PROMISE Registry is a 20-year (5-year recruitment, 15-year follow-up), US-wide, prospective genetic registry for prostate cancer patients. Five thousand patients will be screened through an online at-home germline testing to identify and enroll 500 patients with germline mutations, including: pathogenic or likely pathogenic variants and variants of uncertain significance in genes of interest. Patients will be followed for 15 years and clinical data with real time patient reported outcomes will be collected. Eligible patients will enter long-term follow-up (6-month PRO surveys and medical record retrieval). As a virtual study with patient self-enrollment, the PROMISE Registry may fill gaps in genetics services in underserved areas and for patients within sufficient insurance coverage.
RESULTS: The PROMISE Registry opened in May 2021. 2114 patients have enrolled to date across 48 US states and 23 recruiting sites. 202 patients have met criteria for long-term follow-up. PROMISE is on target with the study\'s goal of 5000 patients screened and 500 patients eligible for long-term follow-up by 2026.
CONCLUSIONS: The PROMISE Registry is a novel, prospective, germline registry that will collect long-term patient outcomes data to address current gaps in understanding resulting from recently FDA-approved treatments and updates to genetic testing recommendations for prostate cancer. Through inclusion of a broad nationwide sample, including underserved patients and those unaffiliated with major academic centers, the PROMISE Registry aims to provide access to germline genetic testing and to collect data to understand disease characteristics and treatment responses across the disease spectrum for prostate cancer with rare germline genetic variants.

Despite recommendations for integrating molecular classification of endometrial cancers (EC) into pathology reporting and clinical management, uptake is inconsistent. To assign ProMisE subtype, all molecular components must be available (POLE mutation status, mismatch repair (MMR) and p53 immunohistochemistry (IHC)) and often these are assessed at different stages of care and/or at different centres resulting in delays in treatment. We assessed a single-test DNA-based targeted next generation sequencing (NGS) molecular classifier (ProMisE NGS), comparing concordance and prognostic value to the original ProMisE classifier.
DNA was extracted from formalin-fixed paraffin embedded (FFPE) ECs that had previously undergone ProMisE molecular classification (POLE sequencing, IHC for p53 and MMR). DNA was sequenced using the clinically validated Imagia Canexia Health Find It™ amplicon-based NGS gene panel assay to assess for pathogenic POLE mutations (unchanged from original ProMisE), TP53 mutations (in lieu of p53 IHC), and microsatellite instability (MSI) (in lieu of MMR IHC),with the same order of segregation as original ProMisE used for subtype assignment. Molecular subtype assignment of both classifiers was compared by concordance metrics and Kaplan-Meier survival statistics.
The new DNA-based NGS molecular classifier (ProMisE NGS) was used to determine the molecular subtype in 164 ECs previously classified with ProMisE. 159/164 cases were concordant with a kappa statistic of 0.96 and an overall accuracy of 0.97. Prognostic differences in progression-free, disease-specific and overall survival between the four molecular subtypes were observed for the new NGS classifier, recapitulating the survival curves of the original ProMisE classifier. ProMisE NGS was 100% concordant between matched biopsy and hysterectomy samples.
ProMisE NGS is feasible on standard FFPE material, demonstrates high concordance with the original ProMisE classifier and maintains prognostic value in EC. This test has the potential to facilitate implementation of molecular classification of EC at the time of first diagnosis.

We evaluated 18 F-DCFPyL test-retest repeatability of uptake in normal organs.
Twenty-two prostate cancer (PC) patients underwent two 18 F-DCFPyL PET scans within 7 days within a prospective clinical trial (NCT03793543). In both PET scans, uptake in normal organs (kidneys, spleen, liver, and salivary and lacrimal glands) was quantified. Repeatability was determined by using within-subject coefficient of variation (wCOV), with lower values indicating improved repeatability.
For SUVmean , repeatability was high for kidneys, spleen, liver, and parotid glands (wCOV, range: 9.0%-14.3%) and lower for lacrimal (23.9%) and submandibular glands (12.4%). For SUVmax , however, the lacrimal (14.4%) and submandibular glands (6.9%) achieved higher repeatability, while for large organs (kidneys, liver, spleen, and parotid glands), repeatability was low (range: 14.1%-45.2%).
We found acceptable repeatability of uptake on 18 F-DCFPyL PET for normal organs, in particular for SUVmean in the liver or parotid glands. This may have implications for both PSMA-targeted imaging and treatment, as patient selection for radioligand therapy and standardized frameworks for scan interpretation (PROMISE, E-PSMA) rely on uptake in those reference organs.

The imaging report is essential for the communication between physicians in patient care. The information it contains must be clear, concise with evidence-based conclusions and sufficient to support clinical decision-making. In recent years, several classification schemes and/or reporting guidelines for PET have been introduced. In this manuscript, we will review the classifications most frequently used in oncology for interpreting and reporting 18F-FDG PET imaging in lymphoma, multiple myeloma, melanoma and head and neck cancers, PSMA-ligand PET imaging for prostate cancer, and 68Ga-DOTA-peptide PET in neuroendocrine tumors (NET).

UNASSIGNED: Malignant pleural effusion (MPE) is a condition, that can be seen in 15% of patients diagnosed with cancer. Because of the short overall survival, it is important to identify the appropriate treatment. In addition to the palliation of secondary symptoms due to MPE, it should also be decided in which cases a more aggressive treatment is to be followed. The purpose of the study was to evaluate the performance of LENT and clinical PROMISE scores in predicting survival in patients with MPE.
UNASSIGNED: Age, sex, smoking history, Eastern Cooperative Oncology Group (ECOG) score, cancer type, history of chemotherapy/radiotherapy, laboratory values, and pleural fluid lactate dehydrogenase were recorded. The LENT and the PROMISE scores were calculated and risk categories were determined. During the follow-up, blood tests and tomography controls were performed on the patients as routine. The overall survival was calculated as the period from the date of diagnosis of MPE to death or until December 31, 2019.
UNASSIGNED: A total of 169 patients were included. The median age was 65 (26-86). In the single-variable analysis, there was a significant increase in mortality risk in the poor performance score and if the LENT risk group progressed from the low-to medium-/high-risk group or PROMISE categories A to B, A to C or A to D. In multivariate analysis, mortality risk in 1, 3, 6, and 12 months increased significantly in poor performance score, in PROMISE category B, C, and D. In high LENT risk-group, an increased mortality risk was shown in only 12 months of survival.
UNASSIGNED: Our data show that poor performance score (ECOG 3-4), PROMISE category B, C, and D significantly increase mortality risk and the LENT score is inadequate in predicting survival.

To identify prognostic factors in patients with grade 3 (high-grade) endometrial endometrioid carcinoma, we evaluated the spectrum of genomic alterations and examined whether previously reported molecular subtypes of endometrial carcinoma were adapted to clinical outcome prediction. Seventy-five Japanese patients with grade 3 endometrial endometrioid carcinoma, who underwent a potentially curative resection procedure between 1997 and 2018 at the National Cancer Center Hospital, were included. We classified the patients into four risk groups of the disease based on the Proactive Molecular Risk Classifier for Endometrial Cancer. Genomic alterations in PTEN, ARID1A, TP53, and PIK3CA were detected in more than 30% of the patients. Overall survival and recurrence-free survival of patients with genomic alterations in CTNNB1 were poorer than those of patients with wild-type CTNNB1 (p = 0.006 and p = 0.004, respectively). Compared with that of alterations prevalent in Caucasians, the frequency of genomic alterations in POLE and TP53 was higher in our study than in The Cancer Genome Atlas dataset (p = 0.01 and p = 0.01, respectively). The tendency for recurrence-free survival in the POLE exonuclease domain mutation group was better than that in the TP53 mutation and mismatch repair-deficient groups (p = 0.08 and p = 0.07, respectively), consistent with the Proactive Molecular Risk Classifier for Endometrial Cancer risk classifier definition. The CTNNB1 mutation is a potential novel biomarker for the prognosis of patients with grade 3 endometrial endometrioid carcinoma, and prognosis classification using Proactive Molecular Risk Classifier for Endometrial Cancer may help screen Japanese patients with the disease.

The 2020 ESGO/ESTRO/ESP guidelines stratify the prognosis of endometrial carcinoma (EC) patients combining The Cancer Genome ATLAS (TCGA) molecular signature and pathological factors, including lymphovascular space invasion (LVSI). However, little is known about the prognostic independence of LVSI from molecular signature.
To assess whether the prognostic value of LVSI is independent from the TCGA signature.
A systematic review and meta-analysis was performed by searching 5 electronic databases from their inception to March 2021. All peer-reviewed studies reporting assessing LVSI as a prognostic factor independent from the TCGA groups in EC were included. Multivariate HRs with 95% confidence interval (CI) were pooled separately for overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS). The absence of LVSI was considered as a reference. In DFS analyses, locoregional and distant recurrence were separately considered for one study.
Six studies with 3331 patients were included in the systematic review and three studies with 2276 patients in the meta-analysis. LVSI showed a pooled multivariate HR of 1.818 (CI 95%, 1.378-2.399) for OS, 1.849 (CI 95%, 1.194-2.863) for DSS, 1.377 (CI 95%, 1.008-1.880) for DFS excluding one study, 1.651 (CI 95%, 1.044-2.611) for DFS additionally considering locoregional recurrence from one study, and 1.684 (CI 95%, 1.05-2.701) for DFS additionally considering distant recurrence from the same study.
LVSI has a prognostic value independent of TCGA signature, as well as age and adjuvant treatment, increasing the risk of death of any cause, death due to EC and recurrent or progressive disease by 1.5-2 times.

Endometrial cancer is the most common gynecological malignancy of the female reproductive organs. Historically it was divided into type I and type II, until 2013 when the Cancer Genome Atlas molecular classification was proposed. Here, we applied the different classification types on our endometrial cancer patient cohort in order to identify the most predictive one. We enrolled 117 endometrial cancer patients available for the study and collected the following parameters: age, body mass index, stage, menopause, Lynch syndrome status, parity, hypertension, type of localization of the lesion at hysteroscopy, type of surgery and complications, and presence of metachronous or synchronous tumors. The tumors were classified according to the European Society for Medical Oncology, Proactive Molecular Risk Classifier for Endometrial Cancer, Post-Operative Radiation Therapy in Endometrial Carcinoma, and Cancer Genome Atlas classification schemes. Our data confirmed that European Society for Medical Oncology risk was the strongest predictor of prognosis in our cohort. The parameters correlated with poor prognosis were the histotype, FIGO stage, and grade. Our study cohort shows that risk stratification should be based on the integration of histologic, clinical, and molecular parameters.