Tumor Grade Research Articles

SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis

The integration of morphological attributes extracted from histopathological images and genomic data holds significant importance in advancing tumor diagnosis, prognosis, and grading. Histopathological images are acquired through microscopic examination of tissue slices, providing valuable insights into cellular structures and pathological features. On the other hand, genomic data provides information about tumor gene expression and functionality. The fusion of these two distinct data types is crucial for gaining a more comprehensive understanding of tumor characteristics and progression. In the past, many studies relied on single-modal approaches for tumor diagnosis. However, these approaches had limitations as they were unable to fully harness the information from multiple data sources. To address these limitations, researchers have turned to multi-modal methods that concurrently leverage both histopathological images and genomic data. These methods better capture the multifaceted nature of tumors and enhance diagnostic accuracy. Nonetheless, existing multi-modal methods have, to some extent, oversimplified the extraction processes for both modalities and the fusion process. In this study, we presented a dual-branch neural network, namely SG-Fusion. Specifically, for the histopathological modality, we utilize the Swin-Transformer structure to capture both local and global features and incorporate contrastive learning to encourage the model to discern commonalities and differences in the representation space. For the genomic modality, we developed a graph convolutional network based on gene functional and expression level similarities. Additionally, our model integrates a cross-attention module to enhance information interaction and employs divergence-based regularization to enhance the model’s generalization performance. Validation conducted on glioma datasets from the Cancer Genome Atlas unequivocally demonstrates that our SG-Fusion model outperforms both single-modal methods and existing multi-modal approaches in both survival analysis and tumor grading.

Bioinformatics analysis of SH2D4A in glioblastoma multiforme to evaluate immune features and predict prognosis.

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain cancer in adults. This study aimed to obtain data on immune cell infiltration based on public datasets and to examine the prognostic significance of SH2 domain containing 4A (SH2D4A) for GBM. SH2D4A expression in GBM was analyzed using a Tumor Immunity Estimation Resource (TIMER) 2.0 dataset, and a gene expression profile interaction analysis (GEPIA), and the results were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The Chinese Glioma Genome Atlas (CGGA) dataset was used to assess the effect of SH2D4A on GBM patient survival. The SH2D4A co-expression network of the LinkedOmics dataset and GeneMANIA dataset was also investigated. Least absolute shrinkage and selection operator (LASSO) regression models and a nomogram were constructed to assess the prognosis of GBM patients. A Gene Set Enrichment Analysis (GSEA) was performed using The Cancer Genome Atlas (TCGA) dataset to find functional differences. The relationship between SH2D4A expression and tumor-infiltrating immune cells was analyzed using xCELL, the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, and the TIMER dataset. We discovered that SH2D4A expression was upregulated in GBM patients, and elevated SH2D4A expression was also substantially correlated with tumor grade. The survival curve analysis and multivariate Cox regression analysis showed that high SH2D4A expression was a significant independent predictor of poor overall survival (OS) in GBM patients. The immunoassay results suggested that altered SH2D4A expression may affect the immune infiltration of GBM tissues and thus the survival outcomes of GBM patients. In addition to being a possible prognostic marker and therapeutic target for GBM, SH2D4A may also accelerate the progression of GBM.

An Uncommon Culprit: Pancreatic Neuroendocrine Tumor in a Patient with Uncontrolled Diabetes

Pancreatic Neuro Endocrine Tumors (NETs) are rare neoplasms that originate from the endocrine tissues of the pancreas, accounting for only 1-2% of pancreatic tumors. Despite their low incidence, these tumors present with a wide range of symptoms and have the ability to secrete hormones, posing significant challenges for their diagnosis and treatment. There are two distinct types of pancreatic NETs: functioning and nonfunctioning. Functioning tumors are characterized by hormone-related clinical syndromes, while nonfunctioning tumors are often found incidentally. The pathogenesis of pancreatic NETs involves both sporadic and hereditary factors, including syndromes such as MEN1, VHL, and NF1. Typically, these tumors are diagnosed in individuals between the ages of 40 and 60, and their effective management requires a multidisciplinary approach. Diagnostic imaging techniques, such as CT and EUS, play a crucial role in accurate diagnosis, while PET scans aid in staging and treatment planning. Histological analysis is essential for determining the tumor grade and predicting prognosis. Treatment strategies are tailored to the tumor's characteristics and the patient's overall health. These may include the use of somatostatin analogs, such as Lanreotide and Octreotide, to control hormone secretion and inhibit tumor growth, as well as systemic therapies like everolimus, sunitinib, and PRRT for metastatic disease. This case report describes the clinical course of a 66-year-old male with a well-differentiated pancreatic NET who initially presented with persistent hyperglycemia. Further investigations revealed a sizable pancreatic mass and liver metastases. Diagnostic evaluation confirmed a grade 1 Neuro Endocrine Tumor, and the patient was started on treatment with Lanreotide. However, his management was complicated by the development of hepatic encephalopathy, which necessitated treatment with lactulose and rifaximin. This case highlights the importance of considering pancreatic NETs in cases of atypical diabetes presentations and emphasizes the need for a multidisciplinary team to provide optimal care. Given the complex nature of pancreatic NETs, a comprehensive diagnostic workup and personalized treatment approach are essential for improving patient outcomes.

Peritumoral radiomics increases the efficiency of classification of pure ground-glass lung nodules: a multicenter study

PurposeWe aimed to evaluate the efficiency of computed tomography (CT) radiomic features extracted from gross tumor volume (GTV) and peritumoral volumes (PTV) of 5, 10, and 15 mm to identify the tumor grades corresponding to the new histological grading system proposed in 2020 by the Pathology Committee of the International Association for the Study of Lung Cancer (IASLC).MethodsA total of 151 lung adenocarcinomas manifesting as pure ground-glass lung nodules (pGGNs) were included in this randomized multicenter retrospective study. Four radiomic models were constructed from GTV and GTV + 5/10/15-mm PTV, respectively, and compared. The diagnostic performance of the different models was evaluated using receiver operating characteristic curve analysisResultsThe pGGNs were classified into grade 1 (117), 2 (34), and 3 (0), according to the IASLC grading system. In all four radiomic models, pGGNs of grade 2 had significantly higher radiomic scores than those of grade 1 (P < 0.05). The AUC of the GTV and GTV + 5/10/15-mm PTV were 0.869, 0.910, 0.951, and 0.872 in the training cohort and 0.700, 0.715, 0.745, and 0.724 in the validation cohort, respectively.ConclusionsThe radiomic features we extracted from the GTV and PTV of pGGNs could effectively be used to differentiate grade-1 and grade-2 tumors. In particular, the radiomic features from the PTV increased the efficiency of the diagnostic model, with GTV + 10 mm PTV exhibiting the highest efficacy.

Immunohistochemical expression of GATA3, CK5/6 and CK20 in molecular subtypes of bladder carcinoma: correlation with clinicopathological features

BackgroundBladder urothelial carcinoma, is considered the 7th most common cancer in males. It is classified into luminal and basal subtypes depending on molecular markers, influencing prognosis and treatment. Identifying reliable biomarkers like GATA3, CK20, and CK5/6 through immunohistochemical methods can aid in early detection, risk stratification, and personalized treatment strategies. This study aims for evaluation prognostic role of these mentioned markers in correlation with clinicopathological parameters in urothelial carcinomas.MethodsTumor samples of forty cases were immunohistochemically stained for GATA3, CK5/6, and CK20. A cutoff of 20% positivity was used to determine subtype classifications, with staining patterns guiding the categorization into basal, luminal, double positive, or double negative groups.ResultsIn this study of 40 urothelial carcinoma patients tumors were classified into basal and luminal subtypes using GATA3, CK5/6 and CK20 markers. GATA3 expression showed no significant association with clinicopathological parameters; while, CK20 was associated with tumor size, and CK5/6 with T, N classification, and lymphovascular invasion. Significant differences in clinicopathological parameters were observed when subtypes were defined by CK5/6, GATA3 or CK20, particularly in tumor grade, T and N classification, and gender. Basal molecular subtypes was correlated with poor prognostic parameters.ConclusionsThis study documented that use of triple markers could define the luminal and basal subtypes of urothelial carcinoma. Basal tumors have shown to be associated with the aggressive behavior and future studies may allow the development of new therapies in the context of molecular subtypes.

The Role of Amide Proton Transfer (APT)-Weighted Imaging in Glioma: Assessment of Tumor Grading, Molecular Profile and Survival in Different Tumor Components.

Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and WHO grade, molecular profile and survival status. Sixty-one patients with adult-type diffuse gliomas were retrospectively analyzed. APT values were semi-automatically extracted from tumor solid and, whenever present, necrotic components. APT values were compared between groups stratified by WHO grade, IDH-mutation, MGMT promoter methylation and 1- and 2-year survival status using Wilcoxon rank-sum test, adjusting for multiple comparisons. Overall survival (OS) was analyzed in the subgroup of 48 patients with grade 4 tumors using Cox proportional-hazards models. Random-effects models were used to assess inter-subject heterogeneity of the mean APT values in each tumor component. APT values of the solid component significantly differed between patients with grades 2-3 and 4 tumors (mean 1.58 ± 0.50 vs. 2.04 ± 0.56, p = 0.028) and correlated with OS after 1 year (1.81 ± 0.58 in survivors vs. 2.17 ± 0.51 in deceased patients, p = 0.030). APT values did not differ by IDH-mutation, MGMT methylation, and 2-year survival status. Within grade 4 glioma patients, higher APT kurtosis of the solid component was a negative prognostic factor (hazard ratio = 1.60, p = 0.040). Mean APT values of the necrosis showed high inter-subject variability, although most necrotic tumors were grade 4 and IDH wildtype. In conclusion, APTw imaging in the solid component provided metrics associated with glioma grade and survival status but showed weak correlation with IDH-mutation and MGMT promoter methylation status, in contrast to previous works. Further research is needed to understand APT signal variability within the necrotic component of high-grade gliomas.

Risk factors for and prognostic impact of lateral pelvic lymph node metastasis in patients with rectal neuroendocrine tumors: a single-center retrospective analysis of 214 cases with radical resection.

Lateral pelvic lymph node (LPLN) metastasis of rectal neuroendocrine tumors (NETs) is rare, with unknown oncological features. We investigated the oncological impact of LPLN metastasis in patients with rectal NETs. This study included 214 patients with rectal NETs who underwent curative surgery. We evaluated their clinicopathological characteristics and short- and long-term outcomes. LPLN dissection was performed in 15 patients with LPLN swelling ≥ 7mm (preoperative imaging); 12 patients had LPLN metastases, 6 of whom had LPLN metastases without mesorectal lymph node metastases (skip metastasis). The short-term outcomes were similar between the groups with and without LPLN dissection. The median follow-up period was 59.4months, and patients with LPLN metastasis showed significantly shorter disease-free and overall survival rates than those without metastasis. Among 199 patients who did not undergo LPLN dissection, only 1 had LPLN recurrence. In a univariate analysis, tumor depth, tumor grade, and LPLN metastasis were associated with the overall survival. In the multivariate analysis, only LPLN metastasis was an independent predictor of the overall survival. LPLN metastasis is a poor prognostic factor for patients with rectal NETs. LPLN enlargement can be considered an indication for dissection, owing to its high rate of metastasis and associated poor prognosis.

Spatial Distribution of Meningiomas: A Magnetic Resonance Image Atlas.

The size and anatomic location of meningiomas have been shown to correlate with distinct clinical manifestations, histopathological subtypes, and surgical risk. However, meningioma anatomic origin sites can be obscured in large tumors and those crossing compartments. We therefore sought to apply unbiased lesion mapping to localize intracranial meningioma distributions and their association with biology and grade. MRI scans, World Health Organization (WHO) grade, and a molecularly Integrated Grade (IG) derived from cytogenetics were analyzed from adult patients with intracranial meningiomas. Semi-automated tumor segmentation was performed on T1-weighted contrast-enhanced MRI. We used the voxel-based lesion mapping technique to generate a meningioma atlas, mapping spatial frequency and correlating with tumor grades. Of 881 patients with meningioma (median age: 57 years, 68.8% female), 589 were WHO grade 1 (66.8%), 265 WHO grade 2 (30.1%), and 27 WHO grade 3 (3.1%) with a median tumor volume of 14.6 cm3. After molecular reclassification, 585 were IG-1 (66.4%), 160 IG-2 (18.2%), and 136 IG-3 (15.4%). Benign tumors were concentrated in and around the midline anterior skull base while malignant meningiomas were enriched in the falcine/parasagittal region and the sphenoid wing, similar to the distribution when stratified by chromosome 1p loss. Meningiomas exhibited sharper spatial clustering when stratified by the molecular IG than by WHO grade. WHO grade 2 meningiomas divided equally across IG 1-3, with corresponding partition of spatial distribution in the midline anterior skull base (in WHO grade 2, IG-1) and falcine/parasagittal and sphenoid regions (WHO grade 2, IG-3). Meningioma volumes significantly varied across age, sex, and WHO/IG grades. We demonstrate the utility of voxel-based lesion mapping for intracranial tumors, characterizing distinct meningioma distribution patterns across histopathological and molecularly defined grades. Molecular grading associated with sharper tumor spatial clusters, supporting a phenotype-genotype association in meningiomas.

Diagnostic utility of apparent diffusion coefficient in preoperative assessment of endometrial cancer: are we ready for the 2023 FIGO staging?

BackgroundAlthough endometrial cancer (EC) is staged surgically, magnetic resonance imaging (MRI) plays a critical role in assessing and selecting the most appropriate treatment planning. We aimed to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging (DWI) in preoperative assessment of EC.MethodsProspective analysis was done for sixty-eight patients with pathology-proven endometrial cancer who underwent MRI and DWI. Apparent diffusion coefficient (ADC) values were measured by two independent radiologists and compared with the postoperative pathological results.ResultsThere was excellent inter-observer reliability in measuring ADCmean values. There were statistically significant lower ADCmean values in patients with deep myometrial invasion (MI), cervical stromal invasion (CSI), type II EC, and lympho-vascular space involvement (LVSI) (AUC = 0.717, 0.816, 0.999, and 0.735 respectively) with optimal cut-off values of ≤ 0.84, ≤ 0.84, ≤ 0.78 and ≤ 0.82 mm2/s respectively. Also, there was a statistically significant negative correlation between ADC values and the updated 2023 FIGO stage and tumor grade (strong association), and the 2009 FIGO stage (medium association).ConclusionsThe preoperative ADCmean values of EC were significantly correlated with main prognostic factors including depth of MI, CSI, EC type, grade, nodal involvement, and LVSI.

Radiotherapy dosing in intracranial ependymoma using the national cancer database.

To determine the dose-dependent effect of adjuvant radiotherapy on survival for pediatric intracranial ependymomas and explore patient and disease characteristics that experience survival benefit from higher doses. Data was accessed from the National Cancer Database. Inclusion criteria was comprised of a diagnosis of non-metastatic intracranial ependymoma, World Health Organization (WHO) grade 2 or 3, surgical resection, adjuvant radiotherapy between 4500-6300cGy, and non-missing survivorship data. Crude and adjusted Cox proportional hazard ratios (HRs) were calculated to estimate the associations of patient, tumor, and treatment characteristics with overall survival (OS). Kaplan-Meier (KM) estimations were used to visualize survival curves for dosing for the general cohort and by subgroups (age, resection extent, and grade). Of the 1154 patients who met inclusion criteria, 405 received ≤ 5400cGy and 749 received > 5400cGy. We found no difference in OS crude (0.95, 95% CI 0.72-1.06) or adjusted (0.88, 95% CI 0.46-1.69) HR for those receiving ≤ 5400cGy. KM curves showed no difference in OS for dosing for the general cohort based on age, surgical extent, and grade. However, there was better OS in those with WHO grade 2 tumors compared to grade 3 regardless of dose received. There was no difference in OS between patients who received ≤ 5400cGy compared to > 5400cGy. We found improved OS in those with grade 2 tumors compared to grade 3, however there was no difference in OS based on dose received by tumor grade, age, or resection extent. Limitations in data available prevent exploring other outcomes or toxicity.

Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging-A Systematic Review.

In spinal oncology, integrating deep learning with computed tomography (CT) imaging has shown promise in enhancing diagnostic accuracy, treatment planning, and patient outcomes. This systematic review synthesizes evidence on artificial intelligence (AI) applications in CT imaging for spinal tumors. A PRISMA-guided search identified 33 studies: 12 (36.4%) focused on detecting spinal malignancies, 11 (33.3%) on classification, 6 (18.2%) on prognostication, 3 (9.1%) on treatment planning, and 1 (3.0%) on both detection and classification. Of the classification studies, 7 (21.2%) used machine learning to distinguish between benign and malignant lesions, 3 (9.1%) evaluated tumor stage or grade, and 2 (6.1%) employed radiomics for biomarker classification. Prognostic studies included three (9.1%) that predicted complications such as pathological fractures and three (9.1%) that predicted treatment outcomes. AI's potential for improving workflow efficiency, aiding decision-making, and reducing complications is discussed, along with its limitations in generalizability, interpretability, and clinical integration. Future directions for AI in spinal oncology are also explored. In conclusion, while AI technologies in CT imaging are promising, further research is necessary to validate their clinical effectiveness and optimize their integration into routine practice.

Myxoid Liposarcomas of the Thigh: Pre-Operative Presentation, Clinical Outcomes, and Functional Results of Surgical Treatment.

Myxoid liposarcomas are malignant soft-tissue sarcomas whose treatment represents a challenge, even for the most experienced surgeon. In this study, we report on our experience with the treatment of myxoid liposarcomas of the thigh. Our retrospective analysis included myxoid liposarcomas of the thigh treated with surgical resection between 2016 and 2022. Resection margins, complications, local recurrences, and metastases were recorded. The oncological outcome of each case was evaluated at their latest follow-up. Adjuvant therapies were administered according to the ESMO guidelines. Functionality was assessed with the MSTS score before surgery and at the patients' latest follow-up. Thirty cases (ten high-grade and 20 low-grade) were included. The mean diameter was 11.8 cm. Twenty-four cases had wide margins (80%) and six (20%) were marginal. Five cases (60% marginal) had local recurrences (17%). Marginal resection was associated with a higher risk of local recurrence (p = 0.041). Three cases with high-grade tumors (10%) developed metastases. At the patients' latest follow-up, their mean MSTS score had risen from 22.9 to 27.3. While tumor grade influences the risk of metastases, the quality of resection margins can determine the local recurrence rate. An adequate surgery can lead to good post-operative functional outcomes.

Longitudinal Changes in Ki-67 Indices in Small-Intestinal Neuroendocrine Tumours and Their Impact on Survival

Introduction: The purpose of this study was to evaluate longitudinal changes in Ki-67 indices of SI-NETs and assess the impact of these in overall survival (OS). Methods: We screened 551 patients with SI-NETs diagnosed from 1993, through 2021, identified using the SI-NET databases from five European referral centres. Only patients with well-differentiated tumours and available baseline tumour samples and follow-up re-biopsies were included. For tumour grading, apart from 2017 WHO classification system, we applied a recently proposed SI-NET site-specific modified histopathological grading system with Ki-67 cut-offs of 5 and 10%. Uni- and multivariable regression analyses were used to determine whether there was a difference between OS in SI-NET patients stratified by increment of Ki-67 indices over time and/or progression to a higher grade. Results: We included 45 patients. Median Ki-67 index at SI-NET diagnosis was 2% (range: 0.5–15%). Thirty-three patients had Ki-67 indices <5% (70.2%), 6 had Ki-67: 5–10% (12.8%), and 8 had Ki-67 ≥10% (17%). Mean time to re-biopsy was 48.8 months (SD: ±162.5). At re-biopsy, the median change in Ki-67 index (absolute value; follow-up minus time of diagnosis) was 1% (range: −10 to +38%). An increase in Ki-67 occurred in 20 patients (42.6%); in 14 patients, the change in Ki-67 resulted in progression to higher tumour grade following the modified grading system. Patients with an increment in Ki-67 ≥1% had a median OS of 32.9 months versus 80.5 months in patients without (HR = 5.6, 95% CI: 1.42–22.02; p = 0.014). When applying the novel modified histopathological grading system for SI-NETs, patients with grade progression had a median OS of 32.9 months versus 53.7 months in those without (HR = 4.61, 95% CI: 1.22–13.54; p = 0.022). At multivariable analysis, grade progression was confirmed as an independent predictor for death (HR = 7.2, 95% CI: 1.58–32.82; p = 0.011). Conclusions: Metachronous increment in Ki-67 indices and related grade progression over time following a site-specific modified histopathological grading system with Ki-67 cut-offs of 5 and 10% is observed in approximately 1/3 of SI-NETs subjected to re-biopsy and it is associated with worse survival outcomes.

Tissue inhibitor of metalloproteinase-3 expression affects clinicopathological features and prognosis of aflatoxin B1-related hepatocellular carcinoma.

The dysregulation of tissue inhibitor of metalloproteinase-3 (TIMP3) was positively correlated with the progression of hepatocellular carcinoma (HCC). However, it is not clear whether TIMP3 expression is associated with the clinicopathological features and prognosis of aflatoxin B1 (AFB1)-related HCC (AHCC). To assess the effects of TIMP3 expression on the clinicopathological features and prognosis of AHCC. A retrospective study, including 182 patients with AHCC, was conducted to explore the link between TIMP3 expression in cancerous tissues and the clinicopathological characteristics and prognosis of AHCC. TIMP3 expression was detected by immunohistochemistry and its effects on the clinicopathological features and prognosis of AHCC were evaluated by Kaplan-Meier survival analysis and Cox regression survival analysis. Odds ratio, hazard ratio (HR), median overall survival time (MST), median tumor recurrence-free survival time (MRT), and corresponding 95% confidential interval (CI) was calculated to evaluate the potential of TIMP3 expression in predicting AHCC prognosis. Kaplan-Meier survival analysis showed that compared with high TIMP3 expression, low TIMP3 expression in tumor tissues significantly decreased the MST (36.00 mo vs 18.00 mo) and MRT (32.00 mo vs 16 mo) of patients with AHCC. Multivariate Cox regression survival analysis further proved that decreased expression of TIMP3 increased the risk of death (HR = 2.85, 95%CI: 2.04-4.00) and tumor recurrence (HR = 2.26, 95%CI: 1.57-3.26). Furthermore, decreased expression of TIMP3 protein in tissues with AHCC was significantly correlated with tumor clinicopathological features, such as tumor size, tumor grade and stage, tumor microvessel density, and tumor blood invasion. Additionally, TIMP3 protein expression was also negatively associated with amount of AFB1-DNA adducts in tumor tissues. These findings indicate that the dysregulation of TIMP3 expression is related to AHCC biological behaviors and affects tumor outcome, suggesting that TIMP3 may act as a prognostic biomarker for AHCC.

Colorectal Leiomyosarcoma: Demographics Patterns, Treatment Characteristics, and Survival Analysis in the U.S. Population.

Colorectal leiomyosarcoma (CR-LMS) is a rare neoplasm arising from smooth muscle cells. It accounts for less than 0.1% of all colorectal malignancies. In this population-based study, we aim to understand the demographics, treatment characteristics, and pathologic factors associated with survival in CR-LMS. Data from the SEER Program (2000-2018) were analyzed using SEER*Stat and SPSS. Statistical methods included descriptive analysis, Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards regression to assess the impact of various factors on disease-specific and overall survival. A total of 191 cases of CR-LMS were identified. Most patients were 60-69years of age (median: 64years) and Caucasian (78%). There was nearly the same distribution in sex (M:F ratio; 1:1.2). The overall 5-year observed survival was 50.3% (95% C.I., 46.3-54.2). The 5-year disease-specific survival (DSS) was 66.1% (95% C.I., 62.0-70.1). The 5-year overall survival after resection was 60.8% (95% C.I., 56.3-65.3). Multivariable analysis identified grades III and IV (p = 0.028) as negative predictors of overall survival. Regional spread and distant stage are negative predictors of overall survival (p < 0.01). Our data reveals that colorectal leiomyosarcoma (CR-LMS) often presents in patients around 64years old with advanced stages and poor differentiation. Key adverse prognostic factors include older age, high tumor grade, large tumor size, and distant metastases, with surgical resection showing the best survival outcomes. To improve outcomes, further research and consolidation of data are essential for developing targeted therapies and comprehensive guidelines.

Development of Ligands and Degraders Targeting MAGE-A3.

Type I melanoma antigen (MAGE) family members are detected in numerous tumor types, and expression is correlated with poor prognosis, high tumor grade, and increased metastasis. Type I MAGE proteins are typically restricted to reproductive tissues, but expression can recur during tumorigenesis. Several biochemical functions have been elucidated for them, and notably, MAGEs regulate proteostasis by serving as substrate recognition modules for E3 ligase complexes. The repertoire of E3 ligase complexes that can be hijacked for targeted protein degradation continues to expand, and MAGE-E3 complexes are an especially attractive platform given their cancer-selective expression. Additionally, type I MAGE-derived peptides are presented on cancer cell surfaces, so targeted MAGE degradation may increase antigen presentation and improve immunotherapy outcomes. Motivated by these applications, we developed novel, small-molecule ligands for MAGE-A3, a type I MAGE that is widely expressed in tumors and associates with TRIM28, a RING E3 ligase. Chemical matter was identified through DNA-encoded library (DEL) screening, and hit compounds were validated for in vitro binding to MAGE-A3. We obtained a cocrystal structure with a DEL analog and hypothesize that the small molecule binds at a dimer interface. We utilized this ligand to develop PROTAC molecules that induce MAGE-A3 degradation through VHL recruitment and inhibit the proliferation of MAGE-A3 positive cell lines. These ligands and degraders may serve as valuable probes for investigating MAGE-A3 biology and as foundations for the ongoing development of tumor-specific PROTACs.

Lemur tail kinase 3 serves as a predictor of patient outcomes and a target for the treatment of ovarian cancer

Lemur tail kinase 3 (LMTK3) belongs to a family of tyrosine kinases that are known to correlate with tumor grade and patient survival in some cancers. Here, we validated LMTK3 as a specific target and a prognostic biomarker in ovarian cancer (OC). In samples from 204 stage I-II OC patients, immunohistochemical studies revealed a higher cytoplasmic-to-nuclear staining intensity of LMTK3, which correlated with worse overall survival (p<0.001). Efficacy studies utilizing novel LMTK3 binding peptides (LMTK3BPs) showed that all chemosensitive and chemoresistant OC cells were killed without affecting normal cells (p<0.005), with synergistic effects shown following cisplatin and docetaxel treatment. In an orthotopic xenograft mouse model of OC, we saw a 35% tumor reduction in response to intravenous injections of 2mg/kg LMTK3BP given three times a week for 3weeks. Furthermore, invivo safety studies showed no signs of toxicity after LMTK3BP treatment, even at doses as high as 40mg/kg. This study highlights LMTK3 as a predictor of patient clinical outcomes. More importantly, novel LMTK3BPs represent potential safe treatment options, either alone or in combination with therapies, for OC.

Tumor grade and progesterone receptor status in predicting benefit of chemotherapy in high genomic risk breast cancer

ABSTRACT Background Not all eligible breast cancer (BC) patients could afford the expensive test of 21-gene recurrence score (RS) assay. This study aimed to identify clinicopathological factors associated with high-risk RS and examine whether these factors correlate with the benefit of chemotherapy. Research design and methods Patients diagnosed with early-stage BC, node-negative, and estrogen receptor-positive disease were identified from the Surveillance, Epidemiology, and End Results Oncotype DX database. Result We included 74,605 patients. Those with higher grade (p < 0.001) and progesterone receptor-negative (PR Neg) (p < 0.001) had the highest odds of a high-risk RS. Among them, 3.2%, 10.1%, 39.1%, 18.6%, 41.6%, and 80.1% had high-risk RS tumors in PR-positive (PR Pos)/well-differentiated (G1), PR Pos/moderately differentiated (G2), PR Pos/poorly and/or undifferentiated (G3), PR Neg/G1, PR Neg/G2, and PR Neg/G3 groups, respectively. Receipt of chemotherapy was associated with improved breast cancer-specific survival (p = 0.010) and overall survival (p < 0.001) in high-risk RS cohort. However, there were no survival benefits from chemotherapy in patients with PR Neg/G3 disease and other groups after stratification by grade and PR status (all p ≥ 0.05). Conclusion Our study aids in refining patient selection for the RS testing, which is crucial given its economic implications. However, 21-gene RS remains pivotal for treatment decision-making.

The immunological landscape and silico analysis of key paraptosis regulator LPAR1 in gastric cancer patients

This study aims to identify key regulators of paraptosis in gastric cancer (GC) and explore their potential in guiding therapeutic strategies, especially in stomach adenocarcinoma (STAD). Genes associated with paraptosis were identified from the references and subjected to Cox regression analysis in the TCGA-STAD cohort. Using machine learning models, LPAR1 consistently ranked highest in feature importance. Multiple sequencing data showed that LPAR1 was significantly overexpressed in cancer-associated fibroblasts (CAFs). LPAR1 expression was significantly higher in normal tissues, and ROC analysis demonstrated its discriminative ability. Copy number alterations and microsatellite instability were significantly associated with LPAR1 expression. High LPAR1 expression correlated with advanced tumor grades and specific cancer immune subtypes, and multivariate analysis confirmed LPAR1 as an independent predictor of poor prognosis. LPAR1 expression was associated with different immune response metrics, including immune effector activation and upregulated chemokine secretion. High LPAR1 expression also correlated with increased sensitivity to compounds, such as BET bromodomain inhibitors I-BET151 and RITA, suggesting LPAR1 as a biomarker for predicting drug activity. FOXP2 showed a strong positive correlation with LPAR1 transcriptional regulation, while increased methylation of LPAR1 promoter regions was negatively correlated with gene expression. Knockdown of LPAR1 affected cell growth in most tumor cell lines, and in vitro experiments demonstrated that LPAR1 influenced extracellular matrix (ECM) contraction and cell viability in the paraptosis of CAFs. These findings suggest that LPAR1 is a critical regulator of paraptosis in GC and a potential biomarker for drug sensitivity and immunotherapy response. This underscores the role of CAFs in mediating tumorigenic effects and suggests that targeting LPAR1 could be a promising strategy for precision medicine in GC.

Up-regulated DSG2 promotes tumor growth and reduces immune infiltration in cervical cancer

BackgroundDesmoglein-2 (DSG2) has been reported to play pivotal roles in various diseases. However, its roles in cervical cancer (CC) remain insufficiently elucidated. Here, we aimed to comprehensively explore the functional mechanisms of DSG2 in CC using bioinformatics and experimental methods. MethodsSeveral online databases, including Gene Expression Profiling Interactive Analysis (GEPIA), ONCOMINE, LinkedOmics, MetaScape, Human protein atlas (HPA), OMICS and single-cell RNA sequencing (scRNA-seq) data were used to explore the expression, prognosis, gene mutations, and potential signaling pathway of DSG2 in CC. Quantitative real-time PCR (qRT-PCR) and western blotting were used to measure DSG2 expression in collected samples. Experimental assays were conducted to verify the effects of dysregulated DSG2 on cervical cell lines in vitro. ResultsBioinformatic analyses revealed that DSG2 was significantly up-regulated in CC compared to normal cervical tissues at both mRNA and protein levels. Elevated DSG2 levels were also associated with poor prognosis and clinical parameters (e.g., cancer stages, tumor grade, nodal metastasis status, etc.). DSG2 expression was predominantly observed in epithelial cells, increasing with disease progression on a single-cell resolution. Additionally, up-regulation of DSG2 significantly enhanced tumor purity by reducing the infiltration of immune cells (e.g., B cells, T cells, NK cells, etc.). Over-expression of DSG2 was further validated in collected CC samples at both mRNA and protein levels. Knockdown of DSG2 markedly reduced the proliferation and invasion of CC cell lines in vitro. ConclusionsIn summary, elevated levels of DSG2 were significantly associated with poor prognosis and diminished immune infiltration in CC. Thus, DSG2 may serve as a potential therapeutic and diagnostic biomarker for CC.