Predict Tumor Behavior Research Articles

PATH-50. AI-POWERED AUTOMATED TISSUE SEGMENTATION IMPROVES OUTCOME STRATIFICATION IN GLIOBLASTOMA

Abstract Glioblastoma displays morphological heterogeneity on routine H&E whole slide images, with conflicting evidence on the reliability of morphological features in predicting tumor behavior and treatment response. However, current standards for assessing morphology and disease status rely on nonquantitative manual evaluation by pathologists, which are prone to inherent variation. We sought to (1) expand the tools available for quantitative assessment and (2) evaluate the utility of this approach in identifying valuable biomarkers. We trained a deep learning-based algorithm using DenseNet on HALO AI platform for automated segmentation of six tissue classes (heavy infiltration, mild infiltration, mesenchymal tissue, geographic necrosis, palisading necrosis, and hemorrhage) on 3232 labeled annotations from 100 whole slide images. Manual pathologists’ estimations from clinical records showed strong correlation with corresponding digital quantifications (p<0.001), and further pixel-wise validation on 828 separate annotations showed high overlap between predicted and ground truth segmentations (precision=0.88, recall= 0.85, F1-score=0.87). We then identified a longitudinal cohort of 115 newly diagnosed glioblastoma tissue paired with the recurrence post-treatment (RT/TMZ), including all 827 H&E whole slide images scanned at 40x. The quantification of longitudinally paired tissue showed a relative increase in geographic necrosis (+62%) and mild infiltration (+110%) and a relative decrease in palisading necrosis (-54%) and heavy infiltration (-35%) between the two timepoints. Patients with rapid clinical progression had more areas of large geographic necrosis (p=0.002), and mesenchymal tissue increase was associated with worse overall survival (p=0.016). Digitally quantified heavy infiltration as a predominant tissue on recurrence outperformed corresponding pathologist estimation of tumor as a predominant tissue on recurrence in stratifying overall-survival (p=0.005 vs p=0.640). Collectively, our AI-powered classifier enables an automated objective quantification of glioblastoma tissue, identifies markers of clinical response, and offers a potential adjunct to enhance routine pathologic reporting of glioblastoma.

NIMG-02. DEVELOPING A RADIOMIC HIERARCHICAL GAUSSIAN PROCESS BOOSTING MODEL TO PREDICT PRIMARY TUMOR ORIGIN FROM MULTICENTRIC LONGITUDINAL MRI DATA OF BRAIN METASTASES

Abstract Focal neurologic deficits due to brain metastases might be the initial presentation in patients with cancer. Common approaches to investigate the occult primary malignancy include a whole-body PET-CT, whole-body MRI, studying tumor markers, or histopathological examination. Most of these modalities are expensive, time-consuming, invasive, and delay treatment. The field of radiomics leverages quantitative features extracted from images to improve the decision-making process in clinical practices. Although not easily understandable, these features are proxies for the tumor’s shape, contour, texture, and intensity patterns. They can help understand tumor heterogeneity, predict tumor behavior, and assess treatment response. We propose a robust radiomic workflow using longitudinal MRI data from 914 high-resolution imaging studies from 12 different centers (Ocaña-Tienda et al. (2023), Ramakrishnan et al. (2023), Wang et al. (2023)) to predict the origin of brain metastases from brain MRI scans. After using ensemble feature selection methods, we trained three fixed-effects and one mixed-effects multiclass classification model to account for longitudinal data. Fixed-effects logistic regression and support vector kernel models performed the worst (AUC 0.74 and 0.75, respectively), while the random forest performed better (AUC 0.97). The mixed-effects hierarchical Gaussian process boosting (GPBoost) model performed the best with an accuracy of 85.8%, precision of 85.4%, sensitivity of 85.8%, specificity of 95.7%, and an AUC of 0.98. In one-versus-rest classification, the GPBoost model identified the primary tumor as melanoma with the highest accuracy (96.1%) and non-small cell lung cancer with the lowest accuracy (89.0%). Developing such models holds great promise in reducing patient and institutional costs, improving time to effective treatment, and enhancing overall survival rates through personalized therapy approaches. In the future, we hope that incorporating newer patient data and refining the model to improve external validity would enable more accurate and generalizable predictions, leading to better clinical outcomes across diverse populations.

Development and Characterization of a Three-Dimensional Organotypic In Vitro Oral Cancer Model with Four Co-Cultured Cell Types, Including Patient-Derived Cancer-Associated Fibroblasts.

Background/Objectives: Cancer organoids have emerged as a valuable tool of three-dimensional (3D) cell cultures to investigate tumor heterogeneity and predict tumor behavior and treatment response. We developed a 3D organotypic culture model of oral squamous cell carcinoma (OSCC) to recapitulate the tumor-stromal interface by co-culturing four cell types, including patient-derived cancer-associated fibroblasts (PD-CAFs). Methods: A stainless-steel ring was used twice to create the horizontal positioning of the cancer stroma (adjoining normal oral mucosa connective tissue) and the OSCC layer (surrounding normal oral mucosa epithelial layer). Combined with a structured bi-layered model of the epithelial component and the underlying stroma, this protocol enabled us to construct four distinct portions mimicking the oral cancer tissue arising in the oral mucosa. Results: In this model, α-smooth muscle actin-positive PD-CAFs were localized in close proximity to the OSCC layer, suggesting a crosstalk between them. Furthermore, a linear laminin-γ2 expression was lacking at the interface between the OSCC layer and the underlying stromal layer, indicating the loss of the basement membrane-like structure. Conclusions: Since the specific 3D architecture and polarity mimicking oral cancer in vivo provides a more accurate milieu of the tumor microenvironment (TME), it could be crucial in elucidating oral cancer TME.

Evaluation of Applicability of Tumor Budding and Poorly Differentiated Clusters as Additional Prognostic Markers in Colorectal Cancers

Purpose Very few studies have assessed tumor budding (TB) and poorly differentiated cell clusters (PDCs) simultaneously in colorectal cancers (CRCs). The goal of this study was to establish a correlation between these two pertinent histological features and to reinforce the importance of their incorporation in routine histopathological reporting of CRC cases as a means to predict clinical outcome. Methods Resection specimens of colorectal carcinoma were included in the study. Patients who received presurgical therapy, or refused consent were excluded. PDC and TB were evaluated in routine hematoxylin and eosin-stained histopathological sections taken from the advancing edge of the tumor. TB and PDC were reported by selecting a “hotspot” chosen after review of all available slides with invasive tumor. It was then followed by their correlation with other known prognostic factors. Results Spearman's rho calculator for strength of association between TB and PDC as well as association of TB and PDC individually with known prognostic factors revealed statistical significance. Correlation of TB and PDC with histologic grade, primary tumor (pT), and regional lymph node (pN) stage was done based on one-way analysis of variance calculator, which yielded statistically significant results. Conclusion Evaluation of these two histological parameters in the same hotspot field at the tumor invasive front plays a fundamental role in the definition of cancer aggressiveness and prediction of tumor behavior.

Correlation of pN Stage and Hypoechogenicity with Tumour Encapsulation and Vascular Invasion in Thyroid Cancer (TC): A Comprehensive Analysis and Clinical Outcomes.

In this retrospective study, the relationship between the pN stage of TC and the ultrasound hypoechogenicity of tumour encapsulation and vascular invasion was investigated. The data of a total of 678 TC patients were analysed. The goal of this study was to assess the significance of the pTNM score and preoperative ultrasound features in predicting cancer prognosis and guiding therapeutic decisions in patients with TC. The main research methods included a retrospective analysis of patient data, mainly the pTNM score and presence of tumour encapsulation and vascular invasion obtained from histopathological results and preoperative ultrasound imaging. Patients with well-differentiated TCs (papillary and follicular) were extracted from TC patients to better unify the results because of similar clinical strategies for these TCs. Significant associations were observed between advanced pN stage and the presence of encapsulation and vessel invasion. The majority of pN1a patients exhibited encapsulation (77.71%; p < 0.0001) and vascular invasion (75.30%; p < 0.0001), as did the majority of pN1b patients (100%; p < 0.0001 and 100%; p < 0.0001, respectively). Less than half of the patients with hypoeghogenic patterns presented with encapsulation (43.30%; p < 0.0001) and vascular invasion (43.52%; p < 0.0001), while the vast majority of patients without hypoechogenicity did not present with encapsulation (90.97%; p < 0.0001) or vascular invasion (90.97%; p < 0.0001). Hypoechogenicity was found to be indicative of aggressive tumour behaviour. The results of this study underscore the importance of accurate N staging in TC and suggests the potential use of ultrasound features in predicting tumour behaviour. Further research is needed to confirm these findings and explore additional prognostic markers to streamline TC management strategies and improve patient outcomes.

E-cadherin expression and gene expression profiles in corticotroph pituitary neuroendocrine tumor subtypes.

Corticotroph adenomas/pituitary neuroendocrine tumors (PitNETs) are associated with significant morbidity and mortality. Predictors of tumor behavior have not shown high prognostic accuracy. For somatotroph adenomas/PitNETs, E-cadherin expression correlates strongly with prognosis. E-cadherin expression has not been investigated in other PitNETs. A retrospective chart review of adults with corticotroph adenomas/PitNETs was conducted to assess correlation between E-cadherin expression and tumor characteristics. In addition, gene expression microarray was performed in subset of tumors (n = 16). Seventy-seven patients were identified; 71% were female, with median age of cohort 45.2 years. Seventy-five percent had macroadenomas, of which 22% were hormonally active. Ninety-five percent of microadenomas were hormonally active. Adrenocorticotropic hormone granulation pattern by IHC identified 63% as densely granulated (DG) and 34% as sparsely granulated (SG). All microadenomas were DG (p < .001); 50% of macroadenomas were DG associated with increased tumor invasion compared to SG. E-cadherin IHC was positive in 80%, diminished in 17%, and absent in 20% and did not correlate with corticotroph PitNETs subtype, size, or prognosis. In contrast to the distinct transcriptomes of corticotroph PitNETs and normal pituitaries, a comparison of clinically active and silent corticotroph PitNETs demonstrated similar molecular signatures indicating their common origin, but with unique differences related to their secretory status.

68Ga]DOTATOC PET-derived radiomics to predict genetic background of head and neck paragangliomas: a pilot investigation.

To investigate the [68Ga]DOTATOC PET radiomic profile of head and neck paragangliomas (HNPGLs) and identify radiomic characteristics useful as predictors of succinate dehydrogenase genes (SDHx) pathogenic variants. Sporadic and SDHx HNPGL patients, who underwent [68Ga]DOTATOC PET/CT, were retrospectively included. HNPGLs were analyzed using LIFEx software, and extracted features were harmonized to correct for batch effects and confronted testing for multiple comparison. Stepwise discriminant analysis was conducted to remove redundancy and identify best discriminating features. ROC analysis was used to define optimal cut-offs. Multivariate decision-tree analysis was performed using CHAID method. 34 patients harboring 60 HNPGLs (51 SDHx in 25 patients) were included. Three sporadic and nine SDHx HNPGLs were metastatic. At stepwise discriminant analysis, both GLSZM-Zone Size Non-Uniformity (ZSNU, reflecting tumor heterogeneity) and IB-TLSRE (total lesion somatostatin receptor expression) were independent predictors of genetic status, with 96.4% of lesions and 91.6% of patients correctly classified after cross validation (p < 0.001). Among non-metastatic patients, GLSZM-ZSNU and IB-TLSRE were significantly higher in sporadic than SDHx HNPGLs (p < 0.001). No differences were revealed in metastatic patients. Decision-tree analysis highlights multifocality and IB-TLSRE as useful variables, correctly identifying 6/9 sporadic and 24/25 SDHx patients. Model failed to classify one SDHA and three sporadic patients (2 metastatic). Radiomics features GLSZM-ZSNU and IB-TLSRE appear to reflect HNPGLs SDHx status and tumor behavior (metastatic vs. non-metastatic). If validated, especially IB-TLSRE might represent a simple and time-efficient radiomic index for SDHx variants early screening and prediction of tumor behavior in HNPGL cases.

A computational tumor growth model experience based on molecular dynamics point of view using deep cellular automata

Cancer, as identified by the World Health Organization, stands as the second leading cause of death globally. Its intricate nature makes it challenging to study solely based on biological knowledge, often leading to expensive research endeavors. While tremendous strides have been made in understanding cancer, gaps remain, especially in predicting tumor behavior across various stages. The integration of artificial intelligence in oncology research has accelerated our insights into tumor behavior, right from its genesis to metastasis. Nevertheless, there's a pressing need for a holistic understanding of the interactions between cancer cells, their microenvironment, and their subsequent interplay with the broader body environment. In this landscape, deep learning emerges as a potent tool with its multifaceted applications in diverse scientific challenges. Motivated by this, our study presents a novel approach to modeling cancer tumor growth from a molecular dynamics' perspective, harnessing the capabilities of deep-learning cellular automata. This not only facilitates a microscopic examination of tumor behavior and growth but also delves deeper into its overarching behavioral patterns. Our work primarily focused on evaluating the developed tumor growth model through the proposed network, followed by a rigorous compatibility check with traditional mathematical tumor growth models using R and Matlab software. The outcomes notably aligned with the Gompertz growth model, accentuating the robustness of our approach. Our validated model stands out by offering adaptability to diverse tumor growth datasets, positioning itself as a valuable tool for predictions and further research.

Smart DNA sensors‐based molecular identification for cancer subtyping

AbstractMolecular subtyping of cancer can greatly help to understand the development of disease and predict tumor behavior. Exploring detection methods for precise subtyping is appealing to prognosis and personalized therapy. During the past decades, DNA‐based biosensors have exhibited great potential in cancer diagnosis due to their structural programmability and functional diversity. Despite the encouraging progress that has been made, there remains an issue in improving the accuracy and sensitivity of cancer subtyping due to the complex process of disease, especially in preclinical or clinical applications. To accelerate the development of DNA sensors in the identification of cancer subtypes, in this review, we summarized their advances in molecular subtyping by analyzing the heterogeneity in categories and levels of biomarkers between cancer subtypes. The strategies toward genomic and proteomic heterogeneity in cells or on the cell surface, as well as the cancer excretions including extracellular vesicles (EVs) and microRNA (miRNAs) in serum, are summarized. Current challenges and the opportunities of DNA‐based sensors in this field are also discussed.

Gastric Carcinoma with low ROR alpha, low E- Cadherin and High LAPTM4B Immunohistochemical Profile; is associated with unfavorable prognosis in Egyptian patients

ABSTRACT In view of multiplicity of carcinogenic pathways of gastric carcinoma (GC), poor survival and chemotherapy resistance, more analysis of these pathways is required for prediction of prognosis and developing new therapeutic targets. Knocking down of RORα; induces tumor cell proliferation and epithelial–mesenchymal transition (EMT). LAPTM4B has been suggested to be associated with EMT which promote tumor invasion. This work aimed to investigate prognostic role of RORα, LAPTM4B, and E-Cadherin expression in GC. This retrospective immunohistochemical study assesses the expression of RORα, LAPTM4B, and E-Cadherin in 73 primary gastric carcinomas. Low RORα and high LAPTM4B expression in GC cases were associated with unfavorable prognostic factors such as positive lymph nodes, and high tumor budding. E-Cadherin heterogeneous staining was associated with poor prognostic criteria, such as diffuse type GC and high tumor budding. Low RORα, high LAPTM4B, and heterogeneous E-Cadherin were the most common immunohistochemical profile in GC cases. Low RORα expression showed poor prognostic impact on overall patient survival. In conclusion, RORα and LAPTM4B may have crucial role in GC aggressiveness. The predominance of low RORα, high LAPTM4B, and heterogeneous or negative E-Cadherin immunohistochemical profile in GC cases with unfavorable pathological parameters suggested that this profile may predict tumor behavior.

Relationship of HER2 with age, gender, location of the tumor, and tumor budding in colorectal adenocarcinoma at H. Adam Malik General Hospital, Medan, Indonesia

Link of Video Abstract: https://youtu.be/_B_bL8gi7hU Background: Colorectal carcinoma is one of the most common malignancies and is one of the leading causes of cancer-related death worldwide. The incidence of colorectal carcinoma in Indonesia is reported to be 12.8 per 100,000 adult population, accounting for 9.5% of all cancer-related deaths. Assessment of Human Epidermal Growth Factor Receptor 2 (HER2) expression is used to help predict tumor behavior and the effect of anti-HER2 receptor therapy. This study aims to analyze the relationship between HER2 immunohistochemical expression with age, gender, tumor location, and tumor budding in this malignancy. Methods: This study is a cross sectional analytic study of 45 samples diagnosed with colorectal carcinoma at H. Adam Malik General Hospital Medan. Tumor budding was assessed for tumor invasiveness based on the International Tumor Budding Consensus Conference (ITBCC) 2016 in a field area of ​​0.785 mm2 with a 20x objective lens using a three-level scoring system, which was categorized into low budding (0-4 buds), intermediate budding (5-9 buds), and high budding (≥10 buds). Staining was performed using immunohistochemistry of the monoclonal anti-human HER2 anti-human DBS manufacturer, which would appear positive on the tumor cell membrane at a dilution of 1:100. HER2 expression was assessed using the HERACLES criteria. The results are presented as a score of 0, 1+, 2+, 3+, then categorized into negative (score 0-2+) and positive (score 3+). Data were analyzed using SPSS version 25.0 for Windows. Results: There was no significant relationship between HER2 and clinicopathological parameters such as age (p=0.755), gender (p&gt;0.05) and tumor location (p&gt;0.05). However, there was a significant relationship between HER2 and tumor budding histopathological parameters with a value of p=0.011 in a positive direction (the greater the number of budding, the more positive HER2 expression, and vice versa). Conclusion: HER2 is not significantly related to age, gender and tumor location. However, it is significantly associated with tumor budding. HER2 plays a role in the proliferation and differentiation of colorectal carcinoma tumor cells.

Determination of expression level of AP1S1, CDK9, FIGF and HDAC11 genes in bladder tumors for aggressive phenotype characterization

Bladder cancer holds a steady 10th place among oncological diseases. Follow-up and timely diagnosis of recurrence and progression of bladder cancer are still based on regular but outdated cystoscopy followed by cytological examination. To reduce the number of cystoscopy procedures, new and reliable biomarkers for predicting tumor behavior must be developed. The aim of this study was to confirm our previous results that demonstrated overexpression of AP1S1, CDK9, FIGF and HDAC11 in muscle-invasive bladder cancer. The project management was performed using iterative flexible project work (Flexible Methodology for Innovative Projects in Scientific Organizations, FMIPSO). Gene expression analysis of the AP1S1, CDK9, FIGF and HDAC11 genes was evaluated in 39 newly collected non-invasive and muscle-invasive bladder tumors. Differential gene expression was calculated using the ΔΔCt method with GPDH as a housekeeping gene. The 4,0-fold change in gene expression was used as a cutoff to determine up- or down-regulation compared to the negative control. Our results demonstrate the involvement of the FIGF, CDK9 and HDAC11 in tumor progression and their potential use as candidate biomarkers to characterize invasive tumor phenotype and muscle progression, as well as potentially reduce the number of cystoscopies. We used FMIPSO to be able to achieve the results at the optimum level of efficiency and control of the project with all possible constraints in scientific organizations.

Metastasising ameloblastoma or ameloblastic carcinoma? A case report with mutation analyses

BackgroundAmeloblastic carcinoma and metastasising ameloblastoma are rare epithelial odontogenic tumours with aggressive features. Distinguishing between these two lesions is often clinically difficult but necessary to predict tumour behaviour or to plan future therapy. Here, we provide a brief review of the literature available on these two types of lesions and present a new case report of a young man with an ameloblastoma displaying metastatic features. We also use this case to illustrate the similarities and differences between these two types of tumours and the difficulties of their differential diagnosis.Case presentationOur histopathological analyses uncovered a metastasising tumour with features of ameloblastic carcinoma, which developed from the ameloblastoma. We profiled the gene expression of Wnt pathway members in ameloblastoma sample of this patient, because multiple molecules of this pathway are involved in the establishing of cell polarity, cell migration or for epithelial–mesenchymal transition during tumour metastasis to evaluate features of tumor behaviour. Indeed, we found upregulation of several cell migration–related genes in our patient. Moreover, we uncovered somatic mutation BRAF p.V600E with known pathological role in cancerogenesis and germline heterozygous FANCA p.S858R mutation, whose interpretation in this context has not been discussed yet. ConclusionsIn conclusion, we have uncovered a unique case of ameloblastic carcinoma associated with an alteration of Wnt signalling and the presence of BRAF mutation. Development of harmful state of our patient might be also supported by the germline mutation in one FANCA allele, however this has to be confirmed by further analyses.

Combined Afirma Genomic Sequencing Classifier and TERT promoter mutation detection in molecular assessment of Bethesda III-VI thyroid nodules.

Molecular analysis of thyroid nodules can provide diagnostic and prognostic information as well as indicate opportunities for targeted therapy. Whole RNA exome analysis offers information that can be leveraged to predict tumor behavior.

Genomic analysis of spinal meningiomas: correlation with histopathological grade.

Spinal meningiomas are one of the most common primary intradural tumors of the adult spine. Spinal meningiomas typically have a benign course with low rates of recurrence. Recent advances in genomic profiling have provided valuable information on meningioma biology and natural history, but these studies have focused primarily on cranial meningiomas. Chromosomal copy number analysis of meningiomas has been shown to be a valuable molecular profiling technique for distinguishing benign from aggressive tumors. The Integrated Grade for Meningioma is a novel grading scheme that uses mitotic index and copy-number profile to identify aggressive tumors at high risk for recurrence. The integrated grade has been shown to be a better predictor of tumor behavior than WHO grade alone. The objective of this study was to evaluate the chromosomal copy-number profile of spinal meningiomas, and to correlate these findings with the assigned WHO grades. The authors evaluated 94 spinal meningiomas treated surgically at their institution between 2002 and 2022. The histopathological results including WHO grade, mitotic index, presence of atypical features, and MIB-1 index were recorded. Chromosomal copy number as determined by institutional whole-genome DNA copy-number profiling was available for 57 tumors. The WHO grades of the cohort consisted of 81 (86%) WHO grade 1 tumors and 13 (14%) WHO grade 2 tumors. In tumors for which copy-number profiling was available, 44 (77%) of 57 demonstrated loss of 22q/NF2. Notably absent were frequent high-risk copy number alterations including loss of 1p, 3p, 4p/q, 6p/q, 10p/q, 14q, 18p/q, 19p/q, and focal loss of CDKN2A on 9p. Of the 9 WHO grade 2 tumors for which copy-number profiling was available, 6 tumors were reclassified to a lower risk profile (integrated grade 1). This analysis suggests that spinal meningiomas exhibit overwhelmingly indolent biology, as supported by their benign integrated grade. These findings have implications in the surgical management of these patients in relation to the need for complete Simpson grade I resection, as well as the potential avoidance of adjuvant therapy following surgery in the setting of otherwise frequently benign pathology.

Contrast-Enhanced Imaging in the Management of Intrahepatic Cholangiocarcinoma: State of Art and Future Perspectives.

Intrahepatic cholangiocarcinoma (iCCA) represents the second most common liver cancer after hepatocellular carcinoma, accounting for 15% of primary liver neoplasms. Its incidence and mortality rate have been rising during the last years, and total new cases are expected to increase up to 10-fold during the next two or three decades. Considering iCCA's poor prognosis and rapid spread, early diagnosis is still a crucial issue and can be very challenging due to the heterogeneity of tumor presentation at imaging exams and the need to assess a correct differential diagnosis with other liver lesions. Abdominal contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) plays an irreplaceable role in the evaluation of liver masses. iCCA's most typical imaging patterns are well-described, but atypical features are not uncommon at both CT and MRI; on the other hand, contrast-enhanced ultrasound (CEUS) has shown a great diagnostic value, with the interesting advantage of lower costs and no renal toxicity, but there is still no agreement regarding the most accurate contrastographic patterns for iCCA detection. Besides diagnostic accuracy, all these imaging techniques play a pivotal role in the choice of the therapeutic approach and eligibility for surgery, and there is an increasing interest in the specific imaging features which can predict tumor behavior or histologic subtypes. Further prognostic information may also be provided by the extraction of quantitative data through radiomic analysis, creating prognostic multi-parametric models, including clinical and serological parameters. In this review, we aim to summarize the role of contrast-enhanced imaging in the diagnosis and management of iCCA, from the actual issues in the differential diagnosis of liver masses to the newest prognostic implications.

Tumor budding as a potential prognostic marker in determining the behavior of primary liver cancers.

Hepatocellular (HCC) and intrahepatic cholangiocarcinoma (ICC), the most common primary tumors of the liver, are among the most important causes of cancer deaths worldwide. Because patients with primary liver tumors are frequently diagnosed at an advanced stage and have high mortality, many efforts have been made to identify new markers to determine their behavior and treatment, similar to those in other solid organ tumors. Recently, morphological assessment of tumor budding (TB) has been revealed as a promising prognostic finding to predict tumor behavior and survival across several different tumor types. Currently, the TB score in colorectal cancer has been revealed as an important parameter in pathology report protocols to determine the course of the disease. Regarding the liver, despite enormous data showing that many mechanisms involved in TB are associated with tumor behavior in both HCC and ICC, studies focusing on the role of TB in predicting the behavior and prognosis of these tumors have started to be investigated very recently. The purpose of this review is to present data about TB in primary tumors of the liver, pointing out the potential role of this parameter in determining the course of the disease, and emphasize the need to increase the number of further studies focusing on the evaluation of this parameter with an overview of the mechanisms involved in TB.

Correlation between Microvessel Density Based on CD31 Immunohistochemical Expression and Clinicopathology of Invasive Breast Carcinoma

Background&#x0D; Breast carcinoma is the most common malignancy in women worldwide. Tumor size, metastases, lymph node involvement (KGB), stage and histopathological grade are significant prognostic factors in invasive breast carcinoma. Microvessel density (MVD) assessment is used to measure angiogenesis which helps predict tumor behavior and the effect of antiangiogenic therapy. MVD is a quantitative calculation of intratumoral capillary blood vessels which reflects the results of the process of angiogenesis. The aim of this study was to analyze the relationship between MVD based on CD31 immunohistochemical expression and the clinicopathology of invasive breast carcinoma.&#x0D; &#x0D; Method&#x0D; Cross sectional analytic study with 42 samples diagnosed with invasive breast carcinoma at H. Adam Malik General Hospital Medan. MVD is the number of small blood vessels in terms of size and diameter (arterioles and venules) with a round lumen that is positively stained with CD31 at 10 large visual fields, categorized as low if &lt;45 blood vessels/10 LPB and high if ≥45 blood vessels/10 LPB. The relationship between MVD and several clinicopathological parameters was analyzed using the Chi-Square, Fisher's Exact and Mann-Whitney tests.&#x0D; &#x0D; Results&#x0D; There was a significant relationship between tumor size (p=0.029), metastasis (p=0.014), stage (p=0.002), histopathological grade (p=0.0043), LVI (p=0.002), TILs (p=0.007). Large tumor size, metastases, high histopathological stage and grade, positive LVI and high TILs were significantly associated with MVD. However, there was no significant relationship between KGB involvement (p=0.570) and MVD.&#x0D; &#x0D; Conclusion&#x0D; MVD is significantly related to tumor size, metastases, stage, histopathological grade, LVI and TILs, and not significantly related to lymph node involvement. MVD plays a role in the angiogenesis of invasive breast carcinoma clinicopathology.

Evaluation of Prognostic Significance of the Expression of p53, Cyclin D1, EGFR in Advanced Oral Squamous Cell Carcinoma after Chemoradiation—A Systematic Review

The majority of all head and neck tumours are squamous cell carcinomas (SCC). Recent advancements have assisted in producing a body of evidence for the genetic origins of these tumours. Identifying prognostic biomarkers in oral SCC would be of great importance in predicting tumour behaviour and in treatment planning. Many studies have proved that chemotherapy given with radiotherapy leads to better treatment outcomes and overall survival. Biomarkers like p53, cyclin D1, and EGFR, that regulate the cell cycle, have a pivotal role in tumour development and progression. This systematic review aims at analysing the prognostic significance of the expression of p53, cyclin D1, and EGFR in advanced oral SCC after chemoradiation therapy (CRT). A systematic search using predetermined keywords and inclusion/exclusion criteria was conducted in Medline/PubMed, Google Scholar, and other databases to identify relevant articles answering the research question “Does the expressions of p53, cyclin D1, and EGFR have a prognostic significance in recurrent oral SCC treated with chemoradiation?” Literature screening revealed eight articles that were considered for this study. The overexpression of p53, cyclin D1, EGFR was associated with the recurrence of the tumour, and pathologic response can be considered as a prognostic marker. However, the recurrence pattern not only depends on the biomarkers but also on the clinicopathologic factors that play a pivotal role in survival rates among oral cancer patients. The standard management of advanced head and neck SCC has been controversial. It has been concluded that concomitant therapy can result in better treatment outcomes. Clinicians need to scrutinize and evaluate p 53, cyclin D1 and EGFR as a diagnostic parameter for post tumour chemoradiation therapy. Personalised therapy strategies can be created for individual patients using biologically guided tumour characterization, which will enhance quality of life. Thus, the application of more sophisticated technology must be implemented for a better analysis of the tumour.

Loss of the Novel Mitochondrial Membrane Protein FAM210B Is Associated with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is an aggressive and challenging disease to treat. Due to the lack of effective early diagnosis and therapy for the illness, it is crucial to identify novel biomarkers that can predict tumor behavior in HCC. In such cases, family with sequence similarity 210 member B (FAM210B) is abundant in various human tissues, but its regulatory mechanisms and role in various tissues remain unclear. In this study, we analyzed the expression pattern of FAM210B in HCC using public gene expression databases and clinical tissue samples. Our results confirmed that FAM210B was dysregulated in both HCC cell lines and HCC paraffin section samples. FAM210B depletion significantly increased the capacity of cells to grow, migrate, and invade in vitro, while overexpression of FAM210B suppressed tumor growth in a xenograft tumor model. Furthermore, we identified FAM210B's involvement in MAPK signaling and p-AKT signaling pathways, both of which are known oncogenic signaling pathways. In summary, our study provides a rational basis for the further investigation of FAM210B as a valuable biological marker for diagnosing and predicting the prognosis of HCC patients.