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BACKGROUND: Non-invasive risk stratification for patients with endometrial carcinoma (EC) is important for developing personalised treatment plans. Our study aimed to explore the ability of quantitative MRI parameters to predict the risk stratification of EC patients based on molecular classification. METHODS: Fifty-three patients with histologically proven EC who underwent pelvic MRI and surgical treatment at our hospital between January 2020 and August 2022 were assessed. The tumour volume (TV) and uterine volume (UV) were estimated with the ellipsoid formula and used to calculate the tumour volume ratio (TVR). The mean apparent diffusion coefficient (ADC) of the tumour was measured on a workstation. Quantitative MRI parameters were compared among different risk groups via unpaired Student's t-tests or Mann-Whitney's U-tests. RESULTS: The TV and TVR were significantly different between the low- and high-risk groups (p < 0.001), and cut-off values of 5342 mm3 and 0.055 allowed the differentiation of the high-risk group from the low-risk group, with 77% and 85% sensitivity and 78% and 78% specificity, respectively. There was a significant difference in the ADC between the two groups (p = 0.026), and a cut-off value of 0.65 × 10-3 mm2/s allowed differentiation of the risk groups, with 93% sensitivity and 39% specificity. CONCLUSIONS: Quantitative MRI parameters such as the TV, TVR and ADC may be helpful in preoperatively assessing the risk stratification of patients with EC based on molecular classification.

For patients with endometrial carcinoma (EC), it is important to assess the risk stratification based on molecular classification for developing treatment plans, but risk stratification is obtained most accurately from postoperative samples. We used non-invasive and easily accessible quantitative parameters of magnetic resonance imaging for preoperatively evaluating the risk stratification in these patients. We found that the quantitative parameters may be helpful in preoperatively assessing the risk stratification of patients with EC on the basis of molecular classification.

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BACKGROUND: Crohn's disease (CD), a prominent manifestation of chronic gastrointestinal inflammation, and breast cancer (BC), seemingly disparate in the medical domain, exhibit a shared characteristic. This convergence arises from their involvement in chronic inflammation and immune responses, an aspect that has progressively captivated the attention of investigators but remain controversial. METHODS: We used two-sample Mendelian Randomization (MR) and transcriptomics to explore the relationship between CD and BC. MR assessed causality of CD on different BC subtypes and reverse causality of BC on CD. We identified CD-related differentially expressed genes and their prognostic impact on BC, and developed a new molecular BC classification based on these key genes. RESULTS: MR revealed a causal link between CD and increased BC risk, especially in estrogen receptor-positive (ER+) patients, but not in ER-negative (ER-) cases. BC showed no causal effect on CD. Transcriptomics pinpointed genes like B4GALNT2 and FGF19 that affected BC prognosis in CD patients. A nomogram based on these genes predicted BC outcomes with high accuracy. Using these genes, a new molecular classification of BC patients was proposed. CONCLUSIONS: CD is a risk factor for ER + BC but not for ER- BC. BC does not causally affect CD. Our prognostic model and new BC molecular classifications offer insights for personalized treatment strategies.

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Background: Ubiquitination, a major post-translational modification, significantly impacts tumorigenesis, progression, and prognosis. This study aims to classify colon cancer at the molecular level and create a reliable signature using ubiquitination-related genes (URGs) to assess the immune microenvironment and prognosis. Methods: We employed non-negative matrix factorization to subtype colon cancer based on ubiquitination-related gene (URG) expression patterns. Quantitative scores for 28 immune cell infiltrates and the tumor microenvironment were computed using single-sample gene set enrichment analysis (ssGSEA) and the Estimate algorithm. Subtype feature genes were selected through Lasso logistic regression and SVM-RFE algorithm. The ubiquitination-related signature was constructed using univariate Cox, Lasso, and stepwise regression methods to categorize patients into high and low-risk groups. Validation included log-rank tests, receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and external dataset validation. Immune therapy response was compared using Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenoscore (IPS), and submap analyses. Clinical variables and risk scores were integrated into an enhanced nomogram. The early diagnostic value of four URGs was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry. The cell proliferation was assessed through colony formation, EdU staining, and xenograft tumorigenesis assays. Results: Prognostic ubiquitination-related genes (URGs) stratified patients into subtypes, revealing differences in survival, immune cell infiltration, and pathological staging. A signature of 6 URGs (ARHGAP4, MID2, SIAH2, TRIM45, UBE2D2, WDR72) was identified from 57 subtype-related genes. The high-risk group exhibited characteristics indicative of enhanced epithelial-mesenchymal transition, immune escape, immunosuppressive myeloid-derived suppressor cells, regulatory T cell infiltration, and lower immunogenicity. In contrast, the low-risk group demonstrated the opposite trend but showed a better response to CTLA4 checkpoint inhibitors. The predictive performance of the nomogram significantly improved with the integration of risk score, stage, and age. ARHGAP4 and SIAH2 exhibit promising early diagnostic capabilities. Additionally, WDR72 knockdown significantly inhibited CRC cell proliferation both in vitro and in vivo. Conclusion: Our developed ubiquitination-related signature and genes serve as promising biomarkers for colon cancer prognosis, immune microenvironment, and diagnosis.

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BACKGROUND: Genome instability (GI) is a hallmark of esophageal squamous cell carcinoma (ESCC) while factors affecting GI remain unclear. METHODS: Here, we aimed to characterize genomic events representing specific mechanisms of GI based on 201 ESCC samples and validated our findings at the patient, single-cell and cancer cell-line levels, including a newly generated multi-omics dataset of the trial NCT04006041. RESULTS: A two-gene (AHNAK and AHNAK2) mutation signature was identified to define the "AHNAK1/2-mutant" cancer subtype. Single-cell-assisted multi-omics analysis showed that this subtype had a higher neoantigen load, active antigen presentation, and proficient CD8 + T cell infiltrations, which were validated at pan-cancer levels. Mechanistically, AHNAK1/2-mutant ESCC was characterized by impaired response of TGF-ß and the inefficient alternative end-join repair (Alt-EJ) that might promote GI. Knockdown of AHNAK in ESCC cell lines resulted in more Alt-EJ events and increased sensitivities to cisplatin. Furthermore, this two-gene signature accurately predicted better responses to DNA-damaging therapy in various clinical settings (HR ≈ 0.25). The two-gene signature predicted higher pCR rates in ESCCs receiving neoadjuvant immunotherapy-involved treatment. Finally, a molecular classification scheme was built and outperformed established molecular typing models in the prognosis stratification of ESCC patients. CONCLUSION: Our study extended our understanding of the AHNAK family in promoting GI and selecting treatment responders of ESCC.

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Background: Head and neck paragangliomas (HNPGLs) are rare neuroendocrine tumors that pose significant challenges in both diagnosis and treatment. The pathogenic mechanism remains unclear, and there is no proteomic analysis-based molecular classification. Therefore, gaining a deeper understanding of this disease from the protein level is crucial because proteins play a fundamental role in the occurrence and development of tumors. Methods: We collected 44 tumor samples from patients diagnosed with HNPGL. The adrenal paraganglioma tissue (N = 46) was used as the disease control group and the chorda tympani nerves (N = 18) were used as the control group. High-pH reversed-phase liquid chromatography and liquid chromatography with tandem mass spectrometry analyses were used to build an integrated protein database of tumor samples. We then obtained two sets of differentially expressed proteins between the tumor group and the control group to identify the unique proteomic signatures of HNPGLs. Ingenuity pathway analysis annotations were used to perform the functional analysis. Subsequently, we developed a clinically relevant molecular classification for HNPGLs that connected the clinical characteristics with meaningful proteins and pathways to explain the varied clinical manifestations. Results: We identified 6,640 proteins in the HNPGL group, and 314 differentially expressed proteins unique to HNPGL were discovered via inter-group comparison. We identified two HNPGL subgroups that significantly differed in clinical manifestation and proteomic characteristics. On the basis of the proteomic results, we proposed a pathogenic mechanism underlying HNPGL. Conclusion: We conducted a comprehensive analysis of the molecular mechanisms of HNPGL to build, for the first time, a clinically relevant molecular classification. By focusing on differential proteomic analyses between different types of paragangliomas, we were able to obtain a comprehensive description of the proteomic characteristics of HNPGL, which will be valuable for the search for significant biomarkers as a new treatment method for HNPGL.

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As water reuse applications expand, there is a need for more comprehensive means to assess water quality. Microbiome analysis could provide the ability to supplement fecal indicators and pathogen profiling toward defining a "healthy" drinking water microbiota while also providing insight into the impact of treatment and distribution. Here, we utilized 16S rRNA gene amplicon sequencing to identify signature features in the composition of microbiota across a wide spectrum of water types (potable conventional, potable reuse, and nonpotable reuse). A clear distinction was found in the composition of microbiota as a function of intended water use (e.g., potable vs nonpotable) across a very broad range of U.S. water systems at both the point of compliance (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.71) and point of use (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.41). Core and discriminatory analysis further served in identifying distinct differences between potable and nonpotable water microbiomes. Taxa were identified at both the phylum (Desulfobacterota, Patescibacteria, and Myxococcota) and genus (Aeromonas and NS11.12_marine_group) levels that effectively discriminated between potable and nonpotable waters, with the most discriminatory taxa being core/abundant in nonpotable waters (with few exceptions, such as Ralstonia being abundant in potable conventional waters). The approach and findings open the door to the possibility of microbial community signature profiling as a water quality monitoring approach for assessing efficacy of treatments and suitability of water for intended use/reuse application.

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OBJECTIVE: The 2023 International Federation of Gynecology and Obstetrics classification with molecular classification shows superior discriminatory ability compared to staging systems lacking molecular data. However, the accuracy of endometrial biopsy data in molecular classification remains uncertain. This study aimed to assess the concordance of molecular classifications between preoperative biopsy and hysterectomy to predict prognosis before surgical staging. METHODS: Endometrial biopsies and corresponding hysterectomy specimens were collected at the National Cancer Center Hospital between 2012 and 2023. Immunohistochemistry for p53 and mismatch repair (MMR) proteins and next-generation sequencing of all exons of polymerase epsilon (POLE) were performed. Given the limited number of POLE mut cases in prior studies, we prepared a POLE mut-enriched cohort. Cohen's kappa estimates were used to determine concordance for molecular and clinicopathological subgroup assignments. RESULTS: Among 70 patients classified into four molecular subtype groups, 33 exhibited POLE mutations, 15 showed loss of MMR protein expression, 13 had p53-abnormality, and 9 had no specific molecular profile. Concordance between biopsy and hysterectomy specimens was 100% (κ = 1.000). In contrast, histological types and grades between biopsy and surgical specimens showed moderate and substantial agreement (κ = 0.420 and κ = 0.780, respectively). CONCLUSIONS: Molecular subtypes were completely consistent with those derived from surgical specimens, demonstrating high concordance between preoperative and postoperative molecular classifications. This suggests that endometrial biopsies could reliably predict prognosis. Future studies should investigate how biopsy-based molecular profiling influences treatment planning and patient outcomes.

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BACKGROUND: Palmoplantar pustulosis (PPP) is an inflammatory disease characterized by relapsing eruptions of neutrophil-filled, sterile pustules on the palms and soles that can be clinically difficult to differentiate from non-pustular palmoplantar psoriasis (palmPP) and dyshidrotic palmoplantar eczema (DPE). OBJECTIVE: We sought to identify overlapping and unique PPP, palmPP, and DPE drivers to provide molecular insight into their pathogenesis. METHODS: We performed bulk RNA sequencing of lesional PPP (n = 33), palmPP (n = 5), and DPE (n = 28) samples, as well as 5 healthy nonacral and 10 healthy acral skin samples. RESULTS: Acral skin showed a unique immune environment, likely contributing to a unique niche for palmoplantar inflammatory diseases. Compared to healthy acral skin, PPP, palmPP, and DPE displayed a broad overlapping transcriptomic signature characterized by shared upregulation of proinflammatory cytokines (TNF, IL-36), chemokines, and T-cell-associated genes, along with unique disease features of each disease state, including enriched neutrophil processes in PPP and to a lesser extent in palmPP, and lipid antigen processing in DPE. Strikingly, unsupervised clustering and trajectory analyses demonstrated divergent inflammatory profiles within the 3 disease states. These identified putative key upstream immunologic switches, including eicosanoids, interferon responses, and neutrophil degranulation, contributing to disease heterogeneity. CONCLUSION: A molecular overlap exists between different inflammatory palmoplantar diseases that supersedes clinical and histologic assessment. This highlights the heterogeneity within each condition, suggesting limitations of current disease classification and the need to move toward a molecular classification of inflammatory acral diseases.

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Background: Gastric cancer (GC) is one of the most common malignant tumors in the world. It has become increasingly difficult to meet the needs of precision therapy using the existing molecular typing system. Therefore, developing a more effective molecular typing system for GC is urgent. Methods: In this study, 100 Chinese GC patients were included. Whole-exome sequencing (WES) and metabolomics analysis were performed to reveal the characteristics of genomic and metabolic changes. Results: In WES, nonsynonymous mutations accounted for the majority. Based on metabolomics, GC has been divided into three subtypes with distinct metabolic features. Importantly, we ultimately divided GC into four subtypes with different metabolic characteristics, genomic alterations, and clinical prognoses by incorporating biomics analysis. Conclusions: Integrating biological features, we constructed a novel molecular system for GC that was closely related to genetics and metabolism, providing new insights for further understanding the heterogeneity and formulating precise treatment strategies.

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BACKGROUND: International Federation of Gynaecology and Obstetrics (Fédération Internationale de Gynécologie et d'Obstétrique - FIGO) introduced a new staging system for endometrial carcinoma - FIGO 2023 - in June 2023. OBJECTIVE: The new staging system differs significantly from previous versions. The new system represents a significant departure from the traditional staging systems for other gynaecological cancers, as the definition of individual stages includes not only the traditional anatomical extent of the tumour, but also the molecular profile of the tumour and other histopathological parameters - histological type of tumour, tumour grade and the presence of substantial lymphovascular invasion. The new system defines stages I and II in a completely different way and expands the definition of stages III and IV, allowing for different types of tumour spread outside the uterus. The introduction of molecular testing is the main change in the new staging system. When certain molecular markers are detected, stage I or II is completely changed. By including these non-anatomical parameters, the FIGO 2023 staging system improves the accuracy of a patient's prognosis at a specific stage with better options for individualized treatment, including the use of immunotherapy. Another goal was to synchronise staging as much as possible with the recommendations of three professional societies: the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO) and the European Society of Pathology (ESP). The staging system for carcinosarcoma remains identical to the staging system for endometrial cancer. CONCLUSION: This article presents an overview of the new FIGO 2023 endometrial cancer staging system and discusses its advantages and disadvantages for clinical practice.

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BACKGROUND: With the significant shift in the classification, risk stratification, and standards of care for gliomas, we sought to understand how the overall survival of patients with these tumors is impacted by molecular features, clinical metrics, and treatment received. METHODS: We assembled a cohort of patients with a histopathologically diagnosed glioma from The Cancer Genome Atlas, Project Genomics Evidence Neoplasia Information Exchange, and Dana-Farber Cancer Institute/Brigham and Women's Hospital. This incorporated retrospective clinical, histological, and molecular data alongside prospective assessment of patient survival. RESULTS: 4,400 gliomas were identified: 2,195 glioblastoma, 1,198 IDH1/2-mutant astrocytoma, 531 oligodendroglioma, 271 other IDH1/2-wildtype glioma, and 205 pediatric-type glioma. Molecular classification updated 27.2% of gliomas from their original histopathologic diagnosis. Examining the distribution of molecular alterations across glioma subtypes revealed mutually exclusive alterations within tumorigenic pathways. Non-TCGA patients had significantly improved overall survival compared to TCGA patients, with 26.7%, 55.6%, and 127.8% longer survival for glioblastoma, IDH1/2-mutant astrocytoma, and oligodendroglioma respectively (all p<0.01). Several prognostic features were characterized, including NF1 alteration and 21q loss in glioblastoma, and EGFR amplification and 22q loss in IDH1/2-mutant astrocytoma. Leveraging the size of this cohort, nomograms were generated to assess the probability of overall survival based on patient age, the molecular features of a tumor, and the treatment received. CONCLUSIONS: By applying modern molecular criteria, we characterize the genomic diversity across glioma subtypes, identify clinically applicable prognostic features, and provide a contemporary update on patient survival to serve as a reference for ongoing investigations.

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Background: Until now, limited clinical significance had been reported for disseminated tumor cells (DTCs) in gynecologic malignancies. DTCs were previously reported not to be associated with established risk factors, L1CAM immunoreactivity, and outcome in endometrial carcinoma (EC). This study's primary objective was to investigate potential correlations of DTCs in the bone marrow (BM) of EC patients with disease-related survival, and a secondary objective was to evaluate associations between molecular classification of EC and DTCs. Methods: Patients treated for primary EC at Tuebingen University women's hospital between 2003 and 2016 were identified. A total of 402 patients with a complete set of BM cytology, molecular, and clinical data were evaluable. Results: DTC occurrence was distributed equally among all four molecular groups (p = 0.651). DTC positivity was associated with a less favorable disease-free survival (HR: 1.86, 95% CI: 1.03-3.36, p = 0.036) and progression-free survival (HR: 1.86, 95% CI: 1.01-3.44, p = 0.045). Presence of DTCs was associated with a higher frequency of distant disease recurrence (p = 0.017). Conclusions: In line with our previous findings, tumor cell dissemination is not associated with molecular features in our large cohort of primary EC patients. Since DTCs seem to be associated with survival and location of disease recurrence, further studies are needed to decisively define their role in EC survival.

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OBJECTIVE: The treatment for stage IB grade 3 endometrioid endometrial adenocarcinoma is challenging with variable practice. Molecular characterization may help identify adjuvant therapy strategies beyond stage. We aimed to better understand the molecular features of these tumors by characterizing them by ProMisE classification, mutational signature, and commonly mutated genes. METHODS: Patients with stage IB grade 3 EEC at two institutions were included. Immunohistochemistry and whole exome sequencing were performed on archival FFPE tissue sections to determine ProMisE classification. Personal Cancer Genome Reporter was used for somatic variant annotation, and mutational signatures were generated based on COSMIC single base substitution mutational signatures. RESULTS: 46 patients were included with variable adjuvant treatment. Nine patients recurred (19.6%), most with extra-abdominal disease (n = 5, or 55.6%). 10 had POLE mutations (21.7%), 18 were MMR deficient (39.1%), 6 had abnormal p53 (13.0%), and 12 were p53 wildtype (26.1%). There were no recurrences in the POLE subgroup. A dominant mutational signature was identified in 38 patients: 17 SBS5 signature (44.7%), 10 SBS15 or SBS44 signature (26.3%), 7 SBS10a or SBS10b signature (18.4%), 3 SBS14 signature (7.9%), and 1 SBS40 signature (2.6%). The six patients that recurred had a SBS5 signature. Frequently mutated genes included ARID1A (n = 30, 65%), PTEN (n = 28, 61%), MUC16 (n = 27, 59%), and PIK3CA (n = 25, 54%). CONCLUSIONS: This comprehensive evaluation found a molecularly diverse cohort of tumors, despite the same histology, stage and grade. Mutational signature SBS5 correlated with a high risk of recurrence. Further refining of endometrial cancer classification may enable more precise patient stratification and personalized treatment approaches.

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Gastric cancer (GC) is highly heterogeneous and prone to metastasis, which are obstacles to the effectiveness of treatment. The basement membrane (BM) acts as a barrier to tumor cell invasion and metastasis. It is critical to investigate the relationship between BM status, metastasis, and patient prognosis. In several large cohorts, we investigated BM gene expression-based molecular classification and risk-prognosis models for GC, examined tumor microenvironment (TME) differences among different molecular subtypes, and developed risk models in predicting prognosis, immunotherapy effectiveness, and chemotherapy resistance. Three GC subtypes (BMclusterA/B/C) based on BM gene expression status were discovered. Each of the three GC subtypes has unique immune infiltration and activated oncogenic signals. Moreover, a 6-gene score (BMscore) predictive model was developed. The low BMscore group had a high tumor mutation burden, high immunogenicity, and low RHOJ expression levels, implying that individuals with GC in this category may be more susceptible to immunotherapy and treatment. The EMT subtype showed a considerably higher BMscore than the other subtypes in the Asian Organization for Research on Cancer (ACRG) molecular classification. Endothelial cells, smooth muscle cells, and fibroblasts may be engaged in regulating BM reorganization in GC progression, according to single-cell transcriptome analyses. In conclusion, we defined a novel molecular classification of GC based on BM genes, developed a prognostic risk model, and elucidated the cell subpopulations involved in BM remodeling at the single-cell level. This study has deepened the understanding of the relationship between GC metastasis and BM alterations, achieved prognostic stratification, and guided therapy.

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Pancreatic cancer (PC) is one of the most common malignant tumors of the digestive tract and has a very high mortality rate worldwide. Different PC patients may respond differently to therapy and develop therapeutic resistance due to the complexity and variety of the tumor microenvironment. The Eph/ephrin signaling pathway is extensively involved in tumor-related biological functions. However, the key function of the Eph/ephrin signaling pathway in PC has not been fully elucidated. We first explored a pan-cancer overview of Eph/ephrin signaling pathway genes (EPGs). Then we grouped the PC patients into 3 subgroups based on EPG expression levels. Significantly different prognoses and tumor immune microenvironments between different subtypes further validate Eph/ephrin's important role in the pathophysiology of PC. Additionally, we estimated the IC50 values for several commonly used molecularly targeted drugs used to treat PC in the three clusters, which could help patients receive a more personalized treatment plan. Following a progressive screening of optimal genes, we established a prognostic signature and validated it in internal and external test sets. The receiver operating characteristic (ROC) curves of our model exhibited great predictive performance. Meanwhile, we further validated the results through qRT-PCR and immunohistochemistry. Overall, this research provides fresh clues on the prognosis and therapy of PC as well as the theoretical groundwork for future Eph/ephrin signaling pathway research.

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OBJECTIVE: To assess the risk stratification of clinicopathologically and molecularly classified endometrial cancer based on estrogen receptor (ER) and L1 cell adhesion molecule (L1CAM) expression. METHODS: This was a retrospective study of patients who underwent primary treatment at a single tertiary center. Carcinomas were classified into 5 clinicopathological risk groups, as per European guidelines. Immunohistochemistry and polymerase-ϵ sequencing were conducted for molecular classification and determination of ER and L1CAM expression. RESULTS: Data from 1044 patients were analyzed. The median follow-up was 67.5 months. In univariable analyses, ER expression correlated with improved disease-specific survival (DSS) in the "no specific molecular profile" (NSMP) (P < 0.001) and mismatch repair deficient (MMRd) (P = 0.002) subgroups. Negative L1CAM expression was associated with enhanced DSS in the NSMP subgroup alone (P < 0.001). ER (hazard ratio [HR] 0.18), but not L1CAM, exhibited prognostic significance within NSMP when controlling for parameters available at the time of diagnosis (tumor histotype, grade, age). ER and L1CAM were not independently associated with DSS within NSMP when controlling for parameters available after surgery (clinicopathological risk groups, age, adjuvant therapy). However, in high-risk-advanced-metastatic cases, both ER (HR 0.26) and L1CAM (HR 3.9) independently correlated with DSS. Similarly, within MMRd, ER was associated with improved DSS in high-risk-advanced-metastatic carcinomas (HR 0.42). CONCLUSION: The prognostic significance of ER and L1CAM varies across clinicopathological risk groups and molecular subgroups of endometrial cancer. Notably, risk assessment for high-risk-advanced-metastatic NSMP and MMRd subtype carcinomas can be refined by ER status.

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OBJECTIVE: Efforts have been made to better risk stratify patients given the rise in incidence of endometrial cancer (EC). The 2023 FIGO staging now incorporates histologic subtype and molecular classification into determination of EC stage. We sought to elucidate if the new staging system demonstrated prognostic differences compared to the 2009 staging system. METHODS: A retrospective chart review was performed on women treated for EC at our institution from September 2013 to May 2023 and combined with the publicly available TCGA Nature 2013 dataset. Detailed clinical information was captured. Patients were restaged according to the 2023 guidelines. Survival estimates were obtained using Kaplan-Meier method, and the log-rank test was used to compare survival curves for progression-free survival (PFS). RESULTS: 919 patients were included in our analysis. The datasets were comparable regarding histologic grade, stage, and age at diagnosis. 175 (31.5%) of patients in the institution dataset and 115 (31.6%) patients in the TCGA dataset experienced a stage change. Most patients whose stage changed were upstaged (275/290; 94.8%). 3-year PFS estimates for stage IA patients with no stage change versus those upstaged were 92.3% (95% CI: 87.2, 95.4) v. 72.0% (95% CI: 68.4, 84.9), p = 0.002. No significant differences in survival difference were seen in other stage subsets. CONCLUSION: Modest survival differences exist in patients with EC originally staged as IA who underwent upstaging. No significant survival difference is observed in patients who are restaged to stage II or III subsets. Improved risk stratification is needed in assessing prognosis and adjuvant therapy for patients with endometrial cancer.

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OBJECTIVE: We aimed to evaluate the performance of endometrial cancer (EC) molecular classification in predicting extrauterine disease after primary surgery alone and in combination with other clinical data available in preoperative setting. METHODS: Retrospective single-center observational study including patients with endometrial adenocarcinoma treated with primary surgery between December 1994 and May 2022. Molecular profiling was performed using immunohistochemistry of p53, MLH1, PMS2, MSH2 and MSH6; and KASP genotyping of the 6 most common mutations of POLE gene. Clinical, pathological and imaging information was reviewed. Logistic regression, regression trees and random forest classification techniques (CART) were performed. RESULTS: We enrolled 658 patients, 47 with POLEmut (7.1%), 234 with MMRd (35.6%), 95 with p53abn (14.4%) and 282 with NSMP (42.8%) tumors. Advanced stage after primary surgery (III-IV FIGO 2009) was diagnosed in 11.7% of patients, p53abn tumors showed increased extrauterine spread (34.1%) and nodal involvement (30.1%) (p < .001). In multivariate analysis, only p53abn subgroup (aOR = 16.0, CI95% = 1.5-165.1) and radiological suspicion of extrauterine disease (aOR = 24.2, CI95% = 12.2-48.2) independently predicted the finding of extrauterine disease after primary surgery. In patients with preoperative uterine-confined disease, deep myometrial and cervical involvement in radiological assessment and p53abn molecular subtype were the best variables to identify patients at-risk of occult extrauterine disease after the staging surgery. CONCLUSION: EC molecular classification is more accurate than histotype or grade in preoperative biopsy to predict advanced disease, and together with imaging tests are the most reliable preoperative information. This work provides an initial framework for using molecular information preoperatively to tailor surgical treatment.

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Pancreatic neuroendocrine tumors (PanNETs), the second most common type of primary pancreatic tumors, display notable heterogeneity in invasiveness. Current knowledge regarding genomic alterations, including DAXX/ATRX, MEN1 mutations, and copy number variations (CNVs), provides some insights into tumor invasiveness. However, the underlying reasons for the significant variation in invasiveness between insulinoma and other types of PanNETs remain unclear. To construct a comprehensive model for the stratification of prognosis, we employed analysis of both the well-established Rip1-Tag2 (RT2) mouse model of PanNETs and human PanNETs with various functional types. Firstly, by applying single-cell and bulk RNA sequencing in PanNETs from different ages and strains of RT2 mice and human PanNETs, we introduced a 2-dimensional (2D) classification system. Based on the 2-D classification system, human PanNETs were mainly classified as benign insulinomas or non-insulinomas subclusters. Non-insulinomas subtypes mainly included gastrinomas, glucagonomas, VIPomas, and NF-PanNETs, which all exhibited potential invasiveness. In addition, we discovered an enrichment of specific CNV patterns and mutations in corresponding human PanNET subclusters. Then we denoted somatic DAXX/ATRX as the 'second hit' and confounding factors for invasiveness. Finally, by combining the 2D system, DAXX/ATRX mutation status, and tumor diameter, a group of indolent PanNETs with minimal recurrence risk was identified. In conclusion, our current work constructed a comprehensive model to elucidate the heterogeneity of invasiveness in PanNETs and improve prognostic stratification.

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OBJECTIVE: The International Federation of Gynecology and Obstetrics (FIGO) 2023 staging system for endometrial cancer (EC) was released with incorporating histology, lympho-vascular space invasion, and molecular classification together. Our objective is to further explore the clinical utility and prognostic significance of the 2023 FIGO staging system in China. METHODS: A retrospective analysis was conducted for patients who received standard surgeries and underwent genetic testing using multigene next-generation sequencing (NGS) panels between December 2018 and December 2023 at Fudan University Shanghai Cancer Center, Shanghai, China. The genomic and clinical data of all patients were analyzed, and stages were determined by both the 2009 and 2023 FIGO staging systems. Kaplan-Meier estimators and Cox proportional hazards models were used for survival analysis. RESULTS: A total of 547 patients were enrolled in the study. After the restaged by the FIGO 2023 staging system, stage shifts occurred in 147/547 (26.9%) patients. In patients with early stages in FIGO 2009 (stage I-II), 63 cases were rearranged to IAmPOLEmut and 53 cases to IICmp53abn due to the molecular classification of POLEmut and p53abn. Altogether 345 cases were in stage I, 107 cases in stage II, 69 cases in stage III, and 26 cases in stage IV according to the FIGO 2023 staging criteria. For stage I diseases, the 3-year PFS rate was 92.7% and 95.3% in 2009 and 2023 FIGO staging systems, respectively. The 3-year PFS of stage II in 2023 FIGO was lower than that of FIGO 2009 (3-year PFS: 85.0% versus 90.9%), especially in substage IIC and IICmp53abn. Three cases (12%) of stage IIIA in FIGO 2009 were shifted to stage IA3 FIGO 2023, with 3-year PFS rates of 90.9% versus 100%, respectively. In NGS analysis, the most prevalent gene alterations were observed in PTEN and PIK3CA. CONCLUSION: The FIGO 2023 staging system was proved to be a good predictor of survival for EC patients with enhanced precision compared to FIGO 2009. Predominant stage shifts were observed in early-stage diseases. Distinct gene alterations of different subtypes may help to explore more accurate target therapies.

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