Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas.

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

Cholangiocarcinoma combined with biliary obstruction: an exosomal circRNA signature for diagnosis and early recurrence monitoring.

Cholangiocarcinoma (CCA) is a highly malignant biliary tract cancer with currently suboptimal diagnostic and prognostic approaches. We present a novel system to monitor CCA using exosomal circular RNA (circRNA) via serum and biliary liquid biopsies. A pilot cohort consisting of patients with CCA-induced biliary obstruction (CCA-BO, n = 5) and benign biliary obstruction (BBO, n = 5) was used to identify CCA-derived exosomal circRNAs through microarray analysis. This was followed by a discovery cohort (n = 20) to further reveal a CCA-specific circRNA complex (hsa-circ-0000367, hsa-circ-0021647, and hsa-circ-0000288) in both bile and serum exosomes. In vitro and in vivo studies revealed the three circRNAs as promoters of CCA invasiveness. Diagnostic and prognostic models were established and verified by two independent cohorts (training cohort, n = 184; validation cohort, n = 105). An interpreter-free diagnostic model disclosed the diagnostic power of biliary exosomal circRNA signature (Bile-DS, AUROC = 0.947, RR = 6.05) and serum exosomal circRNA signature (Serum-DS, AUROC = 0.861, RR = 4.04) compared with conventional CA19-9 (AUROC = 0.759, RR = 2.08). A prognostic model of CCA undergoing curative-intent surgery was established by calculating early recurrence score, verified with bile samples (Bile-ERS, C-index=0.783) and serum samples (Serum-ERS, C-index = 0.782). These models, combined with other prognostic factors revealed by COX-PH model, enabled the establishment of nomograms for recurrence monitoring of CCA. Our study demonstrates that the exosomal triple-circRNA panel identified in both bile and serum samples serves as a novel diagnostic and prognostic tool for the clinical management of CCA.

EP300 through upregulating the expression of vimentin to promote the progression of chordoma.

OBJECTIVE: There is a lack of effective drugs to treat the progression and recurrence of chordoma, which is widely resistant to treatment in chemotherapy. The authors investigated the functional and therapeutic relevance of the E1A-binding protein p300 (EP300) in chordoma. METHODS: The expression of EP300 and vimentin was examined in specimens from 9 patients with primary and recurrent chordoma with immunohistochemistry. The biological functions of EP300 were evaluated with Cell Counting Kit-8, clonogenic assays, and transwell assays. The effects of EP300 inhibitors (C646 and SGC-CBP30) on chordoma cell motility were assessed with these assays. The effect of the combination of EP300 inhibitors and cisplatin on chordoma cells was evaluated with clonogenic assays. Reverse transcription quantitative polymerase chain reaction and Western blot techniques were used to explore the potential mechanism of EP300 through upregulation of the expression of vimentin to promote the progression of chordoma. RESULTS: Immunohistochemistry analysis revealed a positive correlation between elevated EP300 expression levels and recurrence. The upregulation of EP300 stimulated the growth of and increased the migratory and invasive capabilities of chordoma cells, along with upregulating vimentin expression and consequently impacting their invasive properties. Conversely, EP300 inhibitors decreased cell proliferation and downregulated vimentin. Furthermore, the combination of EP300 inhibition and cisplatin exhibited an enhanced anticancer effect on chordoma cells, indicating that EP300 may influence chordoma sensitivity to chemotherapy. CONCLUSIONS: These findings indicate that EP300 functions as an oncogene in chordoma. Targeting EP300 offers a novel approach to the development and clinical treatment of chordoma.

Serial Postoperative Circulating Tumor DNA Assessment Has Strong Prognostic Value During Long-Term Follow-Up in Patients With Breast Cancer.

PURPOSE: Here, we report the sensitivity of a personalized, tumor-informed circulating tumor DNA (ctDNA) assay (Signatera) for detection of molecular relapse during long-term follow-up of patients with breast cancer. METHODS: A total of 156 patients with primary breast cancer were monitored clinically for up to 12 years after surgery and adjuvant chemotherapy. Semiannual blood samples were prospectively collected, and analyzed retrospectively to detect residual disease by ultradeep sequencing using ctDNA assays, developed from primary tumor whole-exome sequencing data. RESULTS: Personalized Signatera assays detected ctDNA ahead of clinical or radiologic relapse in 30 of the 34 patients who relapsed (patient-level sensitivity of 88.2%). Relapse was predicted with a lead interval of up to 38 months (median, 10.5 months; range, 0-38 months), and ctDNA positivity was associated with shorter relapse-free survival (P < .0001) and overall survival (P < .0001). All relapsing triple-negative patients (n = 7/23) had a ctDNA-positive test within a median of 8 months (range, 0-19 months), while the 16 nonrelapsed patients with triple-negative breast cancer remained ctDNA-negative during a median follow-up of 58 months (range, 8-99 months). The four patients who had negative tests before relapse all had hormone receptor-positive (HR+) disease and conversely, five of the 122 nonrelapsed patients (all HR+) had an occasional positive test. CONCLUSION: Serial postoperative ctDNA assessment has strong prognostic value, provides a potential window for earlier therapeutic intervention, and may enable more effective monitoring than current clinical tests such as cancer antigen 15-3. Our study provides evidence that those with serially negative ctDNA tests have superior clinical outcomes, providing reassurance to patients with breast cancer. For select cases with HR+ disease, decisions about treatment management might require serial monitoring despite the ctDNA-positive result.

Association between pathological characteristics and recurrence score by OncotypeDX in resected T1-3 and N0-1 breast cancer: a real-life experience of a North Hungarian regional center.

Introduction: The 21-gene analysis (OncotypeDX) is validated test for pT1-3, pN0-1 with hormone receptor (HR) positive and normal expression of human epidermal growth factor receptor-2 (HER2) breast cancer (BC) to determine the aggressiveness of the disease based on the calculation of Recurrence Score (RS). Methods: In this retrospective study the authors correlated pathological characteristics and Recurrence Score (RS) by traditional statistical methods and Observed Oriented Modeling (OOM) in a realistic cohort of BC patients. Results: OncotypeDX tests were performed in 94 tumour specimens of 90 BC patients. >83% of node-negative (pN0) and >72% of node-positive (pN1) cases could avoid chemotherapy. For pN0 cases, non-parametric correlation and tests demonstrated significant association in eight types of characteristics [progesterone receptor (PR) expression, Ki-67 value, Ki-67 group, PR group, grade, estrogen receptor (ER) expression, Nottingham Prognostic Index (NPI) and Clinical Risk]. For pN1 cases, parametric correlation and tests showed significant association in six characteristic types (number of positive nodes, ER and PR expression, PR group, Ki-67 group and NPI). Based on OOM for pN0 cases, significant associations were established in three characteristics (Ki-67 group, grade and NPI group). For pN1 cases OOM found significant associations in seven characteristics (PR group, PNI, LVI, Ki-67 group, grade, NPI group and number of positive nodes). Conclusion: First in oncology, OOM was applied, which found some other significant characteristics associated with RS than traditional statistical methods. There were few patients, where no clinical associations were found between characteristics and RS contrary to statistically significant differences. Therefore, the results of these statistical analyses can be neither applied for individual cases nor able to provide the bases for screening patients, i.e., whether they need for OncotypeDX testing or not. OncotypeDX still provides a personalised approach in BC.

Molecular and immunological characteristics of postoperative relapse in lymph node-positive esophageal squamous cell cancer.

BACKGROUND: The molecular and immunological characteristics of primary tumors and positive lymph nodes in esophageal squamous cell carcinoma (ESCC) are unknown and the relationship with recurrence is unclear, which this study attempted to explore. METHODS: A total of 30 ESCC patients with lymph node positive (IIB-IVA) were enrolled. Among them, primary tumor and lymph node specimens were collected from each patient, and subjected to 551-tumor-targeted DNA sequencing and 289-immuno-oncology RNA panel sequencing to identify the different molecular basis and immunological features, respectively. RESULTS: The primary tumors exhibited a higher mutation burden than lymph nodes (p < 0.001). One-year recurrent ESCC exhibited a higher Mucin16 (MUC16) mutation rate (p = 0.038), as well as univariate and multivariate analysis revealed that MUC16 mutation is independent genetic factor associated with reduced relapse-free survival (univariate, HR: 5.39, 95% CI: 1.67-17.4, p = 0.005; multivariate, HR: 7.36, 95% CI: 1.79-30.23, p = 0.006). Transcriptomic results showed non-relapse group had higher cytolytic activity (CYT) score (p = 0.025), and was enriched in the IFN-α pathway (p = 0.036), while those in the relapsed group were enriched in the TNF-α/NF-κB (p = 0.001) and PI3K/Akt pathway (p = 0.014). CONCLUSION: The difference in molecular characteristics between primary lesions and lymph nodes may be the cause of the inconsistent clinical outcomes. Mutations of MUC16 and poor immune infiltration are associated with rapid relapse of nodes-positive ESCC.

Disease Evolution Monitored by Serial Cerebrospinal Fluid Liquid Biopsies in Two Cases of Recurrent Medulloblastoma.

Medulloblastoma is the most common malignant brain tumor in childhood. Initial treatment generally includes surgery, irradiation, and chemotherapy. Approximately 20-30% of patients will experience a recurrence, which portends a very poor prognosis. The current standard of care for evaluation for relapse includes radiographic surveillance with magnetic resonance imaging at regular intervals. The presence of circulating tumor DNA in the cerebrospinal fluid has been demonstrated to be a predictor of a higher risk of progression in a research setting for patients with medulloblastoma treated on a prospective single institution clinical trial. We have previously published and clinically validated a liquid-biopsy-based genetic assay utilizing low-pass whole genome sequencing to detect copy number alterations in circulating tumor DNA. Here, we present two teenage patients with posterior fossa medulloblastoma with recurrent disease who have been monitored with serial liquid biopsies showing tumor evolution over time, demonstrating the clinical utility of these approaches.

The correlation study between TOP2A gene expression in circulating tumor cells and chemotherapeutic drug resistance of patients with breast cancer.

BACKGROUND: Patients with breast cancer (BC) at advanced stages have poor outcomes because of high rate of recurrence and metastasis. Biomarkers for predicting prognosis remain to be explored. This study aimed to evaluate the relationships between circulating tumor cells (CTCs) and outcomes of BC patients. PATIENTS AND METHODS: A total of 50 female were enrolled in this study. Their diagnoses were determined by clinical characteristics, image data, and clinical pathology. CTC subtypes and TOP2A gene expression on CTCs were detected by CanPatrol™ technology and triple color in situ RNA hybridization (RNA-ISH), which divided into epithelial CTCs (eCTCs), mesenchymal CTCs (MCTCs), and hybrid CTCs (HCTCs) based on their surface markers. Hormone receptor, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) expression, was measured by immunohistochemistry (IHC) method before treatment. The risk factors for predicting recurrence and metastasis were calculated by COX risk regression model. The progression-free survival (PFS) of patients was determined using Kaplan-Meier survival curve. RESULTS: The patients with a large tumor size (≥ 3 cm) and advanced tumor node metastasis (TNM) stages had high total CTCs (TCTCs) (P < 0.05). These patients also had high TOP2A expression level. COX risk regression analysis indicated that TOP2A expression levels in TCTCs, ER + , HER-2 + , and TNM stages were critical risk factors for recurrence and metastasis of patients (P < 0.05). The PFS of patients with ≥ 5 TCTCs, ≥ 3 HCTCs, and positive TOP2A expression in ≥ 3 TCTCs was significantly longer than that in patient with < 5 TCTCs, < 3 HCTCs, and TOP2A expression in < 3 TCTCs (P < 0.05). In contrast, the PFS of patients with positive hormone receptors (ER + , PR + , HER-2 +) also was dramatically lived longer than that in patients with negative hormone receptor expression. CONCLUSIONS: High TCTC, HCTCs, and positive TOP2A gene expression on CTCs were critical biomarkers for predicting outcomes of BC patients. Positive hormone receptor expression in BC patients has significant favor PFS.

Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights.

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Ensemble-based classification using microRNA expression identifies a breast cancer patient subgroup with an ultralow long-term risk of metastases.

BACKGROUND: Current clinical markers overestimate the recurrence risk in many lymph node negative (LNN) breast cancer (BC) patients such that a majority of these low-risk patients unnecessarily receive systemic treatments. We tested if differential microRNA expression in primary tumors allows reliable identification of indolent LNN BC patients to provide an improved classification tool for overtreatment reduction in this patient group. METHODS: We collected freshly frozen primary tumors of 80 LNN BC patients with recurrence and 80 recurrence-free patients (mean follow-up: 20.9 years). The study comprises solely systemically untreated patients to exclude that administered treatments confound the metastasis status. Samples were pairwise matched for clinical-pathological characteristics to minimize dependence of current markers. Patients were classified into risk-subgroups according to the differential microRNA expression of their tumors via classification model building with cross-validation using seven classification methods and a voting scheme. The methodology was validated using available data of two independent cohorts (n = 123, n = 339). RESULTS: Of the 80 indolent patients (who would all likely receive systemic treatments today) our ultralow-risk classifier correctly identified 37 while keeping a sensitivity of 100% in the recurrence group. Multivariable logistic regression analysis confirmed independence of voting results from current clinical markers. Application of the method in two validation cohorts confirmed successful classification of ultralow-risk BC patients with significantly prolonged recurrence-free survival. CONCLUSION: Profiles of differential microRNAs expression can identify LNN BC patients who could spare systemic treatments demanded by currently applied classifications. However, further validation studies are required for clinical implementation of the applied methodology.

Fibroblast Growth Factor 23 is a Potential Prognostic Biomarker in Uterine Sarcoma.

BACKGROUND: Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality in women. In this study, we evaluated the expression of human fibroblast growth factor 23 (FGF23) in different US subtypes and the relationship between survival and clinicopathological characteristics. METHODS: We conducted a comparative analysis of FGF23 gene expression in different pathological types of US. Utilizing a cohort from The Cancer Genome Atlas of 57 patients, a 50-patient microarray dataset (GSE119043) from the Gene Expression Omnibus and a Suining cohort of 44 patients, we analyzed gene expression profiles and corresponding clinicopathological information. Immunohistochemistry was used to examine the expression level of FGF23 in four US subtypes. Survival analysis was used to assess the relationship between FGF23 expression and prognosis in US patients. RESULTS: Compared with uterine normal smooth muscle and uterine leiomyoma, FGF23 expression was significantly upregulated in US and was differentially expressed in four US subtypes. Uterine carcinosarcoma exhibited the highest expression of FGF23 among the subtypes. Survival analysis revealed no correlation between FGF23 expression and either overall survival or progression-free survival in US (P > 0.05). Similar results were obtained from the validation cohorts. Univariate and multivariate analyses showed no significant correlation between FGF23 expression and the US prognosis. Tumor stage, CA125, and tumor recurrence were independent prognostic factors for survival of US patients. CONCLUSION: FGF23 was highly expressed in US and was promising as a novel potential biomarker for the diagnosis and prognosis of US.

Boosting predictive models and augmenting patient data with relevant genomic and pathway information.

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus-integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer. To address the scarcity of genetic data, we employ imputation techniques, leveraging publicly available datasets such as The Cancer Genome Atlas (TCGA), integrating pathway scores into our patient cohort from the Cancer Long Survivor Artificial Intelligence Follow-up (CLARIFY) project. Through the integration of imputed pathway scores from the TCGA dataset with clinical data, our approach achieves notable strides in predicting relapse among a held-out test set of 200 patients. By training machine learning models on enriched knowledge graph data, inclusive of triples derived from pathway score imputation, we achieve a promising precision of 82% and specificity of 91%. These outcomes highlight the potential of our models as supplementary tools within tumour, node, and metastasis (TNM) classification systems, offering improved prognostic capabilities for lung cancer patients. In summary, our research underscores the significance of refining machine learning models for relapse prediction in early-stage non-small cell lung cancer. Our approach, centered on imputing pathway scores and integrating them with clinical data, not only enhances predictive performance but also demonstrates the promising role of machine learning in anticipating relapse and ultimately elevating patient outcomes.

The role of piRNAs in predicting and prognosing in cancer: a focus on piRNA-823 (a systematic review and meta-analysis).

INTRODUCTION: This article examines the potential of using liquid biopsy with piRNAs to study cancer survival outcomes. While previous studies have explored the relationship between piRNA expression and cancer patient outcomes, a comprehensive investigation is still lacking. To address this gap, we conducted a systematic review and meta-analysis of existing literature. METHODS: We searched major online databases up to February 2024 to identify articles reporting on the role of piRNA in cancer patient survival outcomes. Our meta-analysis used a random-effects model to pool hazard ratios with 95% confidence intervals (CI) and assess the prognostic value of deregulated piRNA-823. For survival analysis, the Kaplan-Meier method and COX analysis were used. RESULTS: Out of 6104 articles screened, 20 met our inclusion criteria. Our analysis revealed that dysregulated piRNA expression is associated with cancer patient survival outcomes. Specifically, our meta-analysis found that overexpression of piR-823 is significantly linked with poorer overall survival in patients with colorectal cancer and renal cell cancer (HR: 3.82, 95% CI = [1.81, 8.04], I2 = 70%). CONCLUSION: Our findings suggest that various piRNAs may play a role in cancer survival outcomes and that piRNA-823 in particular holds promise as a prognostic biomarker for multiple human cancers. IMPLICATIONS FOR CANCER SURVIVORS: Our systematic review and meta-analysis of piRNA-823 has important implications for cancer survivors. Our findings suggest that piRNA-823 can be used as a prognostic biomarker for predicting cancer recurrence and survival rates. This information can help clinicians develop personalized treatment plans for cancer survivors, which can improve their quality of life and reduce the risk of recurrence.

GRIK1 promotes glioblastoma malignancy and is a novel prognostic factor of poor prognosis.

Primary tumors of the central nervous system (CNS) are classified into over 100 different histological types. The most common type of glioma is derived from astrocytes, and the most invasive glioblastoma (WHO IV) accounts for over 57% of these tumors. Glioblastoma (GBM) is the most common and fatal tumor of the CNS, with strong growth and invasion capabilities, which makes complete surgical resection almost impossible. Despite various treatment methods such as surgery, radiotherapy, and chemotherapy, glioma is still an incurable disease, and the median survival time of patients with GBM is shorter than 15 months. Thus, molecular mechanisms of GBM characteristic invasive growth need to be clarified to improve the poor prognosis. Glutamate ionotropic receptor kainate type subunit 1 (GRIK1) is essential for brain function and is involved in many mental and neurological diseases. However, GRIK1's pathogenic roles and mechanisms in GBM are still unknown. Single-nuclear RNA sequencing of primary and recurrent GBM samples revealed that GRIK1 expression was noticeably higher in the recurrent samples. Moreover, immunohistochemical staining of an array of GBM samples showed that high levels of GRIK1 correlated with poor prognosis of GBM, consistent with The Cancer Genome Atlas database. Knockdown of GRIK1 retarded GBM cells growth, migration, and invasion. Taken together, these findings show that GRIK1 is a unique and important component in the development of GBM and may be considered as a biomarker for the diagnosis and therapy in individuals with GBM.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing.

BACKGROUND: As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted. METHODS: We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining. RESULTS: Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55). CONCLUSIONS: TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

The KRAS, ATR and CHEK1 expression levels in endometrial cancer are the risk factors predicting recurrence.

Endometrial cancer is the most prevalent gynecologic malignancy with a high risk of recurrence. Local recurrence occurs in 7-20% of patients with treated stage I cancer within 3 years after primary treatment. In this study, we found significantly elevated mRNA expression levels of the oncoprotein KRAS, along with two replicative stress markers, ATR and CHEK1, in samples of endometrial carcinomas of endometrium (ECE) from patients with relapse. In contrast, mRNA expression levels of the studied genes were low and uniform in samples from patients without relapse. Elevated levels of KRAS protein and the phosphorylated form of ATR/CHEK1 were distinguishing features of recurrent ECE. A strong positive correlation was found between elevated mRNA and protein levels of the studied molecules. Elevated KRAS protein levels are characteristic of poorly differentiated (G3) endometrial carcinomas with deep myometrial invasion in patients without recurrence. In contrast, in patients with recurrence, higher protein levels of KRAS, pATR and pCHEK1 were observed in samples of G1-2 endometrial carcinomas, with statistically significant differences confirmed for pATR. High pCHEK1 protein levels are associated with deep tumor invasion in the myometrium among patients with recurrence. ROC analysis confirmed that evaluating the specificity and sensitivity of KRAS, pATR and pCHEK1 predicts recurrence development in patients with ECE. Our findings indicate that markers of replicative stress may play a significant role in ECE pathogenesis. Determining their levels in tumor samples after primary treatment could help define patients at high risk of recurrence and guide consequent courses of treatment.

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential correlations between samples and provide model interpretability. Herein, we propose a novel interpretable multi-omics data integration method (DeepKEGG) for cancer recurrence prediction and biomarker discovery. In DeepKEGG, a biological hierarchical module is designed for local connections of neuron nodes and model interpretability based on the biological relationship between genes/miRNAs and pathways. In addition, a pathway self-attention module is constructed to explore the correlation between different samples and generate the potential pathway feature representation for enhancing the prediction performance of the model. Lastly, an attribution-based feature importance calculation method is utilized to discover biomarkers related to cancer recurrence and provide a biological interpretation of the model. Experimental results demonstrate that DeepKEGG outperforms other state-of-the-art methods in 5-fold cross validation. Furthermore, case studies also indicate that DeepKEGG serves as an effective tool for biomarker discovery. The code is available at https://github.com/lanbiolab/DeepKEGG.

Therapeutic vulnerabilities in triple negative breast cancer: Stem-like traits explored within molecular classification.

Triple Negative Breast Cancer (TNBC) is the most aggressive type of breast cancer (BC). Despite advances in the clinical management of TNBC, recurrence-related mortality remains a challenge. The stem-like phenotype of TNBC plays a significant role in the persistence of minimal disease residue after therapy. Individuals exhibiting stem-like characteristics are particularly prone to inducing malignant relapse accompanied by strong resistance. Therefore, stem-like traits have been broadly proposed as therapeutic vulnerabilities to treat TNBC and reduce recurrence. However, heterogeneity within TNBC often generally restricts the stability of the therapeutic efficacy. To understand the heterogeneity and manage TNBC more precisely, multiple TNBC subtyping categories have been reported, providing the basis for profile-according therapeutic regimens. To provide more insight into targeting stem-like traits to ablate TNBC and reduce recurrence in the context of heterogeneity, this paper reviewed the molecular subtyping of TNBC, identified the consensus subtypes with distinct stem-like phenotypes, characterized the stemness hierarchy of TNBC, outlined the biological models for stem-like TNBC subtypes, summarized the therapeutic vulnerabilities in stem-like traits of the subtypes, and proposed potential therapeutic regimens targeting stem-like characteristics to improve TNBC prognosis.

Sensitive circulating tumor DNA-based residual disease detection in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is one of the leading causes of cancer-related death in women worldwide, and is characterized by a high rate of recurrence after surgery and chemotherapy. We sought to implement a circulating tumor DNA (ctDNA)-based blood test for more accurate post-operative surveillance of this disease. We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 EOC patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment. Assay specificity was verified using cross-patient analysis of 1,195 control samples. ctDNA was detected in 51 of 55 (93%) samples at diagnosis, and 18 of 18 (100%) samples at progression. Positive ctDNA in the last on-treatment sample was associated with rapid progression (median 1.02 versus 3.38 yr, HR = 5.63, P < 0.001) and reduced overall survival (median 2.31 versus NR yr, HR = 8.22, P < 0.001) in patients with high-grade serous cancer. In the case of 12 patients, ctDNA assays detected progression earlier than standard surveillance, with a median lead time of 5.9 mo. To approach the physical limits of ctDNA detection, five patients were analyzed using ultra-sensitive assays interrogating 479-1,856 tumor mutations, capable of tracking ctDNA fractions down to 0.0004%. Our results demonstrate that ctDNA assays achieve high sensitivity and specificity in detecting post-operative residual disease in EOC.