Risk Of Metastasis Research Articles

"No-Touch" Left Approach for Recipient Hepatectomy: A Promising Strategy to Minimize Hepatocellular Carcinoma Recurrence in Liver Transplantation.

Managing hepatocellular carcinoma (HCC) presents significant clinical challenges, often necessitating orthotopic liver transplantation (OLT). To mitigate the risk of iatrogenic metastasis during OLT and reduce posttransplantation recurrence (PTR), we introduced the "no-touch" left (NTL) approach for recipient hepatectomy in OLT. In this retrospective cohort study, our aim was to compare the safety and PTR rates in patients undergoing OLT via either the NTL technique or the conventional approach for recipient hepatectomy. We included 106 patients who met the Hangzhou criteria and exhibited a high tumor burden in the right lobe, with 50 patients assigned to the NTL group and 56 to the conventional group. The primary endpoint was the 1-y PTR rate, whereas secondary endpoints encompassed the safety of the NTL approach, PTR rates at 2 and 5 y, and overall survival. Baseline demographics and clinical characteristics showed no significant differences between the groups. The NTL approach exhibited major surgical outcomes similar to those of the conventional approach. The cumulative PTR rates at 1, 2, and 5 y were 14.0% in the NTL group, compared with 24.5%, 35.8%, and 35.8% in the conventional group (P = 0.013). Cumulative overall survival rates at 1, 2, and 5 y were 94.0%, 91.9%, and 89.7% in the NTL group and 88.7%, 75.5%, and 72.5% in the conventional group (P = 0.03). This innovative surgical technique enhances safety and significantly reduces the risk of PTR, leading to improved long-term survival. Further prospective studies with larger cohorts and longer follow-up periods are needed to validate our findings and establish the NTL approach as a standard practice in OLT.

30years of prophylactic thyroidectomy for hereditary medullary thyroid cancer : Amilestone in translational medicine

Medullary thyroid cancer (MTC) is the most frequent manifestation of multiple endocrine neoplasia type 2 (MEN2) that determines the oncological outcome. Germline mutations in the rearranged during transfection (RET) protooncogene, atumor suppressor gene on chromosome 10q11.2, were identified 30 years ago as the genetic basis of MEN2 and published in 1993 and 1994. These seminal findings gave rise to the concept of prophylactic thyroidectomy for asymptomatic gene mutation carriers based on apositive RET gene test, which has become the standard of care ever since. Clinical genetic investigations showed genotype-phenotype correlations with respect to the individual gene mutation regarding the penetrance and onset of MTC and to alesser extent also with respect to the other components of MEN2, pheochromocytoma and primary hyperparathyroidism. From this a clinically relevant risk stratification could be derived. Initially, the optimal timing of prophylactic thyroidectomy was primarily based on the RET genotype alone, which was not sufficient for a precise age recommendation and subsequently required additional consideration of calcitonin serum levels for fine tuning. Calcitonin levels first show the risk of lymph node metastasis when they exceed the upper normal limit of the assay independent of carrier age and RET mutation. Routine calcitonin screening of patients with nodular thyroid disease, screening of families on identification of MEN2 index patients, and pre-emptive thyroidectomy in carriers of gene mutations with normal calcitonin levels have led to the fact that nowadays, 30years after the first description of the gene mutations causing the disease, the life-threatening hereditary MTC has become curable: ashining example for the success of translational transnational medical research for the benefit of patients.

Diagnostic Accuracy of Preoperative Radiologic Findings in Papillary Thyroid Microcarcinoma: Discrepancies with the Postoperative Pathologic Diagnosis and Implications for Clinical Outcomes.

The diagnostic accuracy of preoperative radiologic findings in predicting the tumor characteristics and clinical outcomes of papillary thyroid microcarcinoma (PTMC) was evaluated across all risk groups. In total, 939 PTMC patients, comprising both low-risk and non-low-risk groups, who underwent surgery were enrolled. The preoperative tumor size and lymph node metastasis (LNM) were evaluated by ultrasonography within 6 months before surgery and compared with the postoperative pathologic findings. Discrepancies between the preoperative and postoperative tumor sizes were analyzed, and clinical outcomes were assessed. The agreement rate between radiological and pathological tumor size was approximately 60%. Significant discrepancies were noted, including an increase in tumor size in 24.3% of cases. Notably, in 10.8% of patients, the postoperative tumor size exceeded 1 cm, despite being initially classified as 0.5 to 1.0 cm based on preoperative imaging. A postoperative tumor size >1 cm was associated with aggressive pathologic factors such as multiplicity, microscopic extrathyroidal extension, and LNM, as well as a higher risk of distant metastasis. In 30.1% of patients, LNM was diagnosed after surgery despite not being suspected before the procedure. This group was characterized by smaller metastatic foci and lower risks of distant metastasis or recurrence than patients with LNM detected both before and after surgery. Among all risk groups of PTMCs, a subset showed an increase in tumor size, reaching 1 cm after surgery. These cases require special consideration due to their association with adverse clinical outcomes, including an elevated risk of distant metastasis.

A non-invasive preoperative prediction model for predicting axillary lymph node metastasis in breast cancer based on a machine learning approach: combining ultrasonographic parameters and breast gamma specific imaging features.

The most common route of breast cancer metastasis is through the mammary lymphatic network. An accurate assessment of the axillary lymph node (ALN) burden before surgery can avoid unnecessary axillary surgery, consequently preventing surgical complications. In this study, we aimed to develop a non-invasive prediction model incorporating breast specific gamma image (BSGI) features and ultrasonographic parameters to assess axillary lymph node status. Cohorts of breast cancer patients who underwent surgery between 2012 and 2021 were created (The training set included 1104 ultrasound images and 940 BSGI images from 235 patients, the test set included 568 ultrasound images and 296 BSGI images from 99 patients) for the development of the prediction model. six machine learning (ML) methods and recursive feature elimination were trained in the training set to create a strong prediction model. Based on the best-performing model, we created an online calculator that can make a linear predictor in patients easily accessible to clinicians. The receiver operating characteristic (ROC) and calibration curve are used to verify the model performance respectively and evaluate the clinical effectiveness of the model. Six ultrasonographic parameters (transverse diameter of tumour, longitudinal diameter of tumour, lymphatic echogenicity, transverse diameter of lymph nodes, longitudinal diameter of lymph nodes, lymphatic color Doppler flow imaging grade) and one BSGI features (axillary mass status) were selected based on the best-performing model. In the test set, the support vector machines' model showed the best predictive ability (AUC = 0.794, sensitivity = 0.641, specificity = 0.8, PPV = 0.676, NPV = 0.774 and accuracy = 0.737). An online calculator was established for clinicians to predict patients' risk of ALN metastasis ( https://wuqian.shinyapps.io/shinybsgi/ ). The result in ROC showed the model could benefit from incorporating BSGI feature. This study developed a non-invasive prediction model that incorporates variables using ML method and serves to clinically predict ALN metastasis and help in selection of the appropriate treatment option.

Impact of an Online Risk Calculator for Sentinel Node Positivity on Management of Patients with T1 and T2 Melanomas.

Predicting which patients with American Joint Committee on Cancer (AJCC) T1-T2 melanomas will have a positive sentinel lymph node (SLN) is challenging. Melanoma Institute Australia (MIA) developed an internationally validated SLN metastatic risk calculator. This study evaluated the nomogram's impact on T1-T2 melanoma patient management at MIA. SLN biopsy (SLNB) rates were compared for the pre- and post-nomogram periods of 1 July 2018-30 June 2019 and 1 August 2020-31 July 2021, respectively. Overall, 850 patients were identified (pre-nomogram, 383; post-nomogram, 467). SLNB was performed in 29.0% of patients in the pre-nomogram group and 34.5% in the post-nomogram group (p=0.091). The overall positivity rate was 16.2% in the pre-nomogram group and 14.9% in the post-nomogram group (p=0.223). SLNB was performed less frequently in T1a melanoma patients in the pre-nomogram group (1.1%, n=2/177) than in the post-nomogram group (8.6%, n=17/198) [p≤0.001]. This increase was particularly for melanomas with a risk score ≥ 5%, with an SLN positivity rate of 11.8% in the post-nomogram group (p=0.004) compared with zero. For T1b melanomas with a risk score of > 10%, the SLNB rate was 40.0% (8/20) pre-nomogram and 75.0% (12/16) post-nomogram (p=0.049). In this specialized center, the SLN risk calculator appears to influence practice for melanomas previously considered low risk for metastasis, with increased use of SLNB for T1a and higher-risk T1b melanomas. Further evaluation is required across broader practice settings. Melanoma management guidelines could be updated to incorporate the availability of nomograms to better select patients for SLNB than previous criteria.

Model of micro-metastases of breast cancer cells in ovarian tissue: Cryopreservation of ZR-75-1 and MDA-MB-231 cells with increased speed of warming increases malignancy

In medicine, ovarian tissue cryopreservation exists for fertility preservation of cancer patients. In fact, ovarian tissue frozen for subsequent thawing and re-transplantation can be contaminated with cancer cells. Therefore, investigations on the effect of cryopreservation on the post-thawed viability of such cells are relevant. Speed of warming is a key parameter of cell cryopreservation. However, the data about comparative viability of cancer cells cryopreserved with different parameters of warming are limited. The aim of our investigations was to assess the malignancy of cryopreserved cancer cells after conventional cooling followed by relatively slow and quick speed of warming. In vitro cultured breast cancer cells of lines ZR-75-1 and MD0MD-231 in form of compacted fragments (as a model of solid tumors) were frozen following a protocol usually used for freezing of ovarian tissue (6 % ethylene glycol+6 % glycerol+0.15 M sucrose, −0.3 °C/min). Cells were warmed by two routine regimes of warming: at 37 °C (“slow” warming) and 100 °C (“quick” warming). Biological properties of cells were investigated: viability, proliferation rate, 2D- and 3D-migration, transmembrane movement and invasion. Quick warming at 100 °C in comparison with slow warming at 37 °C exhibited significantly higher cell survival for MDA-MB-231 cells: 70.1 % vs. 63.2 % and for ZR-75-1 86.8 % vs. 82.9 %, respectively. The cell motility including 2D movement and 3D transmembrane migration were higher after quick thawing at 100 °C. Invasive abilities of cells after cryopreservation were higher than that of fresh (non-treated cells). Both thawing regimes showed a similar rate of cell proliferation. Cryopreservation procedures, and especially this one with quick thawing, increase malignancy of ZR-75-1 and MDA-MB-231 breast cancer cells and risk of metastasis.

A machine learning model for predicting the lymph node metastasis of early gastric cancer not meeting the endoscopic curability criteria.

We developed a machine learning (ML) model to predict the risk of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) who did not meet the existing Japanese endoscopic curability criteria and compared its performance with that of the most common clinical risk scoring system, the eCura system. We used data from 4,042 consecutive patients with EGC from 21 institutions who underwent endoscopic submucosal dissection (ESD) and/or surgery between 2010 and 2021. All resected EGCs were histologically confirmed not to satisfy the current Japanese endoscopic curability criteria. Of all patients, 3,506 constituted the training cohort to develop the neural network-based ML model, and 536 constituted the validation cohort. The performance of our ML model, as measured by the area under the receiver operating characteristic curve (AUC), was compared with that of the eCura system in the validation cohort. LNM rates were 14% (503/3,506) and 7% (39/536) in the training and validation cohorts, respectively. The ML model identified patients with LNM with an AUC of 0.83 (95% confidence interval, 0.76-0.89) in the validation cohort, while the eCura system identified patients with LNM with an AUC of 0.77 (95% confidence interval, 0.70-0.85) (P = 0.006, DeLong's test). Our ML model performed better than the eCura system for predicting LNM risk in patients with EGC who did not meet the existing Japanese endoscopic curability criteria. We developed a neural network-based machine learning model that predicts the risk of lymph node metastasis in patients with early gastric cancer who did not meet the endoscopic curability criteria.

Exosome-sheathed porous silica nanoparticle-mediated co-delivery of 3,3′-diindolylmethane and doxorubicin attenuates cancer stem cell-driven EMT in triple negative breast cancer

BackgroundTherapeutic management of locally advanced and metastatic triple negative breast cancer (TNBC) is often limited due to resistance to conventional chemotherapy. Metastasis is responsible for more than 90% of breast cancer-associated mortality; therefore, the clinical need to prevent or target metastasis is immense. The epithelial to mesenchymal transition (EMT) of cancer stem cells (CSCs) is a crucial determinant in metastasis. Doxorubicin (DOX) is the frequently used chemotherapeutic drug against TNBC that may increase the risk of metastasis in patients. After cancer treatment, CSCs with the EMT characteristic persist, which contributes to advanced malignancy and cancer recurrence. The latest developments in nanotechnology for medicinal applications have raised the possibility of using nanomedicines to target these CSCs. Hence, we present a novel approach of combinatorial treatment of DOX with dietary indole 3,3′-diindolylmethane (DIM) which is an intriguing field of research that may target CSC mediated EMT induction in TNBC. For efficient delivery of both the compounds to the tumor niche, advance method of drug delivery based on exosomes sheathed with mesoporous silica nanoparticles may provide an attractive strategy.ResultsDOX, according to our findings, was able to induce EMT in CSCs, making the breast cancer cells more aggressive and metastatic. In CSCs produced from spheres of MDAMB-231 and 4T1, overexpression of N-cadherin, Snail, Slug, and Vimentin as well as downregulation of E-cadherin by DOX treatment not only demonstrated EMT induction but also underscored the pressing need for a novel chemotherapeutic combination to counteract this detrimental effect of DOX. To reach this goal, DIM was combined with DOX and delivered to the CSCs concomitantly by loading them in mesoporous silica nanoparticles encapsulated in exosomes (e-DDMSNP). These exosomes improved the specificity, stability and better homing ability of DIM and DOX in the in vitro and in vivo CSC niche. Furthermore, after treating the CSC-enriched TNBC cell population with e-DDMSNP, a notable decrease in DOX mediated EMT induction was observed.ConclusionOur research seeks to propose a new notion for treating TNBC by introducing this unique exosomal nano-preparation against CSC induced EMT.Graphical

A structured iterative division approach for non-sparse regression models and applications in biological data analysis.

In this paper, we focus on the modeling problem of estimating data with non-sparse structures, specifically focusing on biological data that exhibit a high degree of relevant features. Various fields, such as biology and finance, face the challenge of non-sparse estimation. We address the problems using the proposed method, called structured iterative division. Structured iterative division effectively divides data into non-sparse and sparse structures and eliminates numerous irrelevant variables, significantly reducing the error while maintaining computational efficiency. Numerical and theoretical results demonstrate the competitive advantage of the proposed method on a wide range of problems, and the proposed method exhibits excellent statistical performance in numerical comparisons with several existing methods. We apply the proposed algorithm to two biology problems, gene microarray datasets, and chimeric protein datasets, to the prognostic risk of distant metastasis in breast cancer and Alzheimer's disease, respectively. Structured iterative division provides insights into gene identification and selection, and we also provide meaningful results in anticipating cancer risk and identifying key factors.

Multi-omics prediction of lymph node metastasis status in breast cancer

Lymph node metastasis status stands as a pivotal prognostic indicator in forecasting the outlook for breast cancer patients. Consequently, precise evaluation of this status holds paramount importance in the staging, treatment, and prognosis of breast cancer. The utilization of radiomics, genomics, proteomics, transcriptomics, and histopathology methodologies has notably enhanced the precision of lymph node metastasis status prediction in breast cancer. This review provides an overview of recent advancements in omics-based lymph node metastasis prediction for breast cancer, elucidating the significance of various omics prediction models and integrated multi-omics models in this predictive endeavor. The overarching goal is to augment the accuracy of preoperative lymph node metastasis status prediction in breast cancer, thereby aiding clinicians in the selection of efficacious personalized treatment strategies, while concurrently averting undertreatment of patients with a heightened risk of metastasis.

Analysis of surgical margins and prognostic factors in dermatofibrosarcoma protuberans after wide local excision: Amulticenter study of 116 Japanese patients.

Cutaneous dermatofibrosarcoma protuberans (DFSP) is a fibrohistiocytic tumor characterized by a high risk of local recurrence but a low risk of metastasis. Wide local excision (WLE) has been an important treatment option, but its clinical outcomes and safety have not been thoroughly evaluated in previous reports. The aim of this study was to determine appropriate surgical margins (deep and lateral) and prognostic factors associated with recurrence-free survival (RFS) of DFSP. A database collected by two dermatology departments in Japan was retrospectively reviewed to identify 116 patients with DFSP who underwent complete resection with WLE between 1994 and 2021. Sixty-one men (53%) and 55 women (47%) were included in our cohort. The primary sites of DFSP were as follows: 11 head and neck (9%); seven face (7%); 12 upper extremities (10%); 20 lower extremities (17%); and 66 trunk (57%). There were 103 cases (89%) of primary DFSP and 13 cases (11%) of recurrent DFSP. Total 10-year RFS was 96.6%. There were significant differences in RFS by tumor size (median size: 3 cm), disease status (primary versus recurrent DFSP), and fibrosarcomatous change (positive versus negative) (all p < 0.05). Two patients (1.7%) with buccal or head lesions had positive deep margins. In all cases, the lateral margin was negative at the postoperative evaluation. Tumor size, disease status, and fibrosarcomatous change are important risk factors for recurrence. Both face and head-neck lesions were more likely to have positive deep margins than other anatomic areas in DFSP. Although this study was limited by its retrospective design, a narrow 2-cm lateral margin is especially considered for low-risk patients.

The 8th AJCC classification is inferior to a new neck stage based on intraparotid lymph node in parotid gland cancer

BackgroundLymph node (LN) status is an important prognostic factor for parotid gland cancer (PGC). This study aimed to analyze the impact of extranodal extension (ENE) of intraparotid LN and LN metastasis burden on survival in PGC.MethodsPatients with surgically treated PGC and at least one metastatic cervical LN were retrospectively enrolled. Primary outcome variables were distant metastasis-free survival (DMFS), disease-specific survival (DSS), and overall survival (OS). The impact of ENE and LN metastasis burden was assessed using the Cox model.ResultsA total of 292 patients were included. ENE in cervical or intraparotid LN was not associated with DMFS, DSS, or OS. Intraparotid LN metastasis had a significant impact on prognosis, and the presence of only one metastatic intraparotid LN offered an approximately 1.5-fold risk of distant metastasis. Prognostic models based on the number of positive LNs (1 vs. 2–3 vs. 4+) were superior to the AJCC N stage in terms of DMFS, DSS, and OS.ConclusionsENE of cervical or intraparotid LN has a limited effect on the prognosis of PGC, and the number of positive LNs is better than the AJCC N stage in LN status evaluation.

Keratin-Positive Giant Cell-Rich Tumor: A Review and Update.

Keratin-positive giant cell-rich tumor (KPGCT) is an extremely rare and recently described mesenchymal neoplasm that occurs in both soft tissue and bone, frequently found in young women. It has locally recurrent potential if incompletely excised but low risk for metastasis. KPGCT is histologically similar to conventional giant cell tumors of soft tissue but shows the presence of keratin-positive mononuclear cells. Interestingly, KPGCT also shares some morphological features with xanthogranulomatous epithelial tumors. These two tumors have recently been shown to harbor an HMGA2-NCOR2 fusion, arguing in favor of a single entity. Surgery is the treatment of choice for localized KPGCT. Therapeutic options for advanced or metastatic disease are unknown. This review provides an overview of the current knowledge on the clinical presentation, pathogenesis, histopathology, and treatment of KPGCT. In addition, we will discuss the differential diagnosis of this emerging entity.

EZH2 G553C significantly increases the risk of brain metastasis from lung cancer due to salt bridge instability

BackgroundThe incidence and mortality of lung cancer is the highest in China and the world. Brain is the most common distant metastasis site of lung cancer. Its transfer mechanism and predictive biomarkers are still unclear. EZH2 participates in the catalysis of transcriptional inhibition complex, mediates chromatin compactness, leads to the silencing of its downstream target genes, participates in the silencing of multiple tumor suppressor genes, and is related to cell proliferation, apoptosis and cycle regulation. In physiology, EZH2 has high activity in stem cells or progenitor cells, inhibits genes related to cell cycle arrest and promotes self-renewal. To detect the expression and mutation of EZH2 gene in patients with brain metastasis of lung cancer, and provide further theoretical basis for exploring the pathogenesis of brain metastasis of lung cancer and finding reliable biomarkers to predict brain metastasis of lung cancer.MethodsThis study investigated susceptible genes for brain metastasis of lung cancer. The second-generation sequencing technology was applied to screen the differential genes of paired samples (brain metastasis tissues, lung cancer tissues and adjacent tissues) of lung cancer patients with brain metastasi.ResultsIt revealed that there was a significant difference in the G553C genotype of EZH2 between lung cancer brain metastasis tissues and lung cancer tissues (p = 0.045). The risk of lung cancer brain metastasis in G allele carriers was 2.124 times higher than that in C allele carriers. Immunohistochemistry showed that compared with lung cancer patients and lung cancer patients with brain metastasis, the expression level of EZH2 in lung cancer tissues of lung cancer patients was significantly higher than that in adjacent lung tissues (p < 0.0001), and higher than that in brain metastasis tissues (p = 0.0309). RNA in situ immunohybridization showed that EZH2 mRNA expression was gradually high in lung cancer adjacent tissues, lung cancer tissues and lung cancer brain metastasis tissues.ConclusionsEZH2 G553C polymorphism contributes to the prediction of brain metastasis of lung cancer, in which G allele carriers are more prone to brain metastasis.

Distinct characteristics of distant metastasis in early-onset gastric cancer patients compared to late-onset patients: An observational study.

Presently, there is limited understanding of the features of distant metastasis in early-onset gastric cancer (GC). To explore these disparities, a retrospective study utilizing the Surveillance, Epidemiology, and End Results (SEER) database was undertaken. The SEER database was utilized to extract patient data, and multivariate logistic regression analysis was employed to identify the risk factors associated with distant metastasis and liver metastasis. Propensity score matching (PSM) was used to compare the occurrence of liver metastasis among patients based on their age at diagnosis. The study included 2684 early-onset GC patients and 33,289 late-onset GC patients. Preliminary data analysis indicated that early-onset GC patients exhibited more aggressive characteristics such as poor cell differentiation, advanced T stage, and a higher incidence of distant metastasis, excluding liver metastasis. Multivariate logistic regression analysis identified younger age as an independent risk factor for distant metastasis, along with T stage, lymph node metastasis (LNM), and tumor size (>3 cm). Another regression analysis revealed that younger age, diffuse type, and female gender were protective factors against liver metastasis. Through PSM, 3276 early-onset GC patients were matched with an equal number of late-onset GC patients, revealing that patients with early-onset GC had fewer instances of liver metastasis but a higher prevalence of distant metastasis. Our findings suggest that early-onset serves as a protective factor against liver metastasis in GC, while it poses a risk for distant metastasis, likely influenced by the increased prevalence of diffuse-type GC in early-onset patients.

Prediction of Lymph Node Metastasis in T1 Colorectal Cancer Using Artificial Intelligence with Hematoxylin and Eosin-Stained Whole-Slide-Images of Endoscopic and Surgical Resection Specimens.

According to the current guidelines, additional surgery is performed for endoscopically resected specimens of early colorectal cancer (CRC) with a high risk of lymph node metastasis (LNM). However, the rate of LNM is 2.1-25.0% in cases treated endoscopically followed by surgery, indicating a high rate of unnecessary surgeries. Therefore, this study aimed to develop an artificial intelligence (AI) model using H&E-stained whole slide images (WSIs) without handcrafted features employing surgically and endoscopically resected specimens to predict LNM in T1 CRC. To validate with an independent cohort, we developed a model with four versions comprising various combinations of training and test sets using H&E-stained WSIs from endoscopically (400 patients) and surgically resected specimens (881 patients): Version 1, Train and Test: surgical specimens; Version 2, Train and Test: endoscopic and surgically resected specimens; Version 3, Train: endoscopic and surgical specimens and Test: surgical specimens; Version 4, Train: endoscopic and surgical specimens and Test: endoscopic specimens. The area under the curve (AUC) of the receiver operating characteristic curve was used to determine the accuracy of the AI model for predicting LNM with a 5-fold cross-validation in the training set. Our AI model with H&E-stained WSIs and without annotations showed good performance power with the validation of an independent cohort in a single center. The AUC of our model was 0.758-0.830 in the training set and 0.781-0.824 in the test set, higher than that of previous AI studies with only WSI. Moreover, the AI model with Version 4, which showed the highest sensitivity (92.9%), reduced unnecessary additional surgery by 14.2% more than using the current guidelines (68.3% vs. 82.5%). This revealed the feasibility of using an AI model with only H&E-stained WSIs to predict LNM in T1 CRC.

Approaches and considerations in the endoscopic treatment of T1 colorectal cancer.

The detection of early colorectal cancer (CRC) is increasing through the implementation of screening programs. This increased detection enhances the likelihood of minimally invasive surgery and significantly lowers the risk of recurrence, thereby improving patient survival and reducing mortality rates. T1 CRC, the earliest stage, is treated endoscopically in cases with a low risk of lymph node metastasis (LNM). The advantages of endoscopic treatment compared with surgery include minimal invasiveness and limited tissue disruption, which reduce morbidity and mortality, preserve bowel function to avoid colectomy, accelerate recovery, and improve cost-effectiveness. However, T1 CRC has a risk of LNM. Thus, selection of the appropriate treatment between endoscopic treatment and surgery, while avoiding overtreatment, is challenging considering the potential for complete resection, LNM, and recurrence risk.

Advances in Imaging Techniques for Retinoblastoma with Subretinal Seeding

Retinoblastoma is a rare and highly malignant intraocular tumor primarily affecting young children. Subretinal seeding, specifically Type D, indicates an advanced stage of retinoblastoma with a high risk of metastasis and a poor prognosis. We present a case of a 4-year-old girl who presented with leukocoria, vision loss, and painless redness in her left eye. Examination of the posterior segment revealed a total retinal detachment and abnormal, tortuous retinal vessels in the left eye. No visible mass, vitreous seeding, or hemorrhage was observed. B-mode ultrasound confirmed a detached retina. Due to the poor visual prognosis and strong clinical suspicion of malignancy, enucleation was performed. Further histopathological analysis confirmed the diagnosis of diffuse infiltrative retinoblastoma.

Morphologic patterns observed in prostate biopsy cases with discrepant grade group and molecular risk classification.

Molecular-based risk classifier tests are increasingly being utilized by urologists and radiation oncologists to guide clinical decision making. The Decipher prostate biopsy test is a 22-gene RNA biomarker assay designed to predict likelihood of high-grade disease at radical prostatectomy and risk of metastasis and mortality. The test provides a risk category of low, intermediate, or high. We investigated histologic features of biopsies in which the Grade Group (GG) and Decipher risk category (molecular risk) were discrepant. Our institutional urologic outcomes database was searched for men who underwent prostate biopsies with subsequent Decipher testing from 2016 to 2020. We defined discrepant GG and molecular risk as either GG1-2 with high Decipher risk category or GG ≥ 3 with low Decipher risk category. The biopsy slide on which Decipher testing was performed was re-reviewed for GG and various histologic features, including % Gleason pattern 4, types of Gleason pattern 4 and 5, other "high risk" features (e.g., complex papillary, ductal carcinoma, intraductal carcinoma [IDC]), and other unusual and often "difficult to grade" patterns (e.g., atrophic carcinoma, mucin rupture, pseudohyperplastic carcinoma, collagenous fibroplasia, foamy gland carcinoma, carcinoma with basal cell marker expression, carcinoma with prominent vacuoles, and stromal reaction). Follow-up data was also obtained from the electronic medical record. Of 178 men who underwent prostate biopsies and had Decipher testing performed, 41 (23%) had discrepant GG and molecular risk. Slides were available for review for 33/41 (80%). Of these 33 patients, 23 (70%) had GG1-2 (GG1 n = 5, GG2 n = 18) with high Decipher risk, and 10 (30%) had GG ≥ 3 with low Decipher risk. Of the 5 GG1 cases, one case was considered GG2 on re-review; no other high risk features were identified but each case showed at least one of the following "difficult to grade" patterns: 3 atrophic carcinoma, 1 collagenous fibroplasia, 1 carcinoma with mucin rupture, and 1 carcinoma with basal cell marker expression. Of the 18 GG2 high Decipher risk cases, 2 showed GG3 on re-review, 5 showed large cribriform and/or other high risk features, and 10 showed a "difficult to grade" pattern. Of the 10 GG ≥ 3 low Decipher risk cases, 5 had known high risk features including 2 with large cribriform, 1 with IDC, and 1 with Gleason pattern 5. In GG1-2 high Decipher risk cases, difficult to grade patterns were frequently seen in the absence of other known high risk morphologic features; whether these constitute true high risk cases requires further study. In the GG ≥ 3 low Decipher risk cases, aggressive histologic patterns such as large cribriform and IDC were observed in half (50%) of cases; therefore, the molecular classifier may not capture all high risk histologic patterns.

A Population-Based Long-Term Follow-Up of Soft Tissue Angiosarcomas: Characteristics, Treatment Outcomes, and Prognostic Factors

Angiosarcoma is a rare aggressive and understudied soft tissue sarcoma with pending evidence-based treatment guidelines due to varying study cohorts and inconsistent outcome measures. Surgery with wide resection is currently considered to be the cornerstone in management. In a population-based cohort identified from Danish National Health Registers between 2000 and 2017, this study aimed to define prognostic factors in patients with newly diagnosed soft tissue angiosarcoma. Kaplan–Meier survival analysis demonstrated 5-year overall survival of 28%. Competing risk analysis demonstrated cumulative incidence of local recurrence of 30% and metastasis of 43%. Multivariable Cox models among 154 included patients demonstrated age above 60 years and metastasis to be independently associated with worse overall survival. Cutaneous tumors, surgery, and negative resection margin were independently associated with improved overall survival. Adjuvant oncological treatment did not improve overall survival, risk of metastasis, or recurrence. Negative margin was not associated with lower risk of recurrence and metastasis. We conclude that, despite demonstrated improved survival after surgery with wide resection, overall survival remains poor.