Benign Counterparts Research Articles

Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues

Raman spectroscopy (RS) is a promising tool for cancer diagnosis. In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. Recently, it has been demonstrated that RS can perform an accurate classification of chondrosarcoma tissues. Chondrosarcoma is a cancer of bones, that can occur in the soft tissues near the bones. It is normally characterized by three different malignant degrees and a benign counterpart, knows as enchondroma. In line with these findings, in this paper, we exploited ML algorithms to distinguish, as well as possible, between the three grades of chondrosarcoma and to distinguish between chondrosarcoma and enchondroma. We obtained a high level of accuracy of classification by analyzing a dataset composed of a relatively small number of Raman spectra, collected in a previous study by one of the authors of this paper. Such spectra were acquired from micrometric tissue sections with a confocal Raman microscope. We tested the classification performances of a support vector machine (SVM) and a random forest classifier (RFC), as representatives of ML algorithms, and two versions of the multi-layer perceptron (MLPC) as representatives of deep learning (DL). These models, especially RFC and MLPC, showed excellent classification performances, with accuracy reaching 99.7%. This outcome makes the aforementioned models a promising route for future improvements of diagnostic devices focused on detecting cancerous bone tissues. Alongside the diagnostic purpose, the aforementioned approach allowed us to identify characteristic molecules, i.e., amino acids, nucleic acids, and bioapatites, relevant for obtaining the final diagnostic response, through the use of a tool named by us Raman Band Identification (RBI). The method to evaluate RBI is the most important contribution of this paper, because RBI could represent a relevant parameter for the identification of biochemical processes on the basis of the tumor progression and associated malignant degree. In turn, the spectral bands highlighted by RBI could provide precious indicators in an attempt to restrict the spectral acquisition to specific Raman bands. This last objective could help to reduce the amount of experimental data needed to obtain an accurate final grading outcome, with a consequent reduction in the computational cost.

Level of Necrosis in Feline Mammary Tumors: How to Quantify, Why and for What Purpose?

Necrosis is a common finding in human and animal neoplasms. The percentage of tumor necrosis is included in tumor grading schemes in veterinary oncology; however, evaluation methods are often overlooked. Different studies have assessed the prognostic value of tumor necrosis in feline mammary tumors with contradictory results, which could be related to methodologic variability. In this study, a comprehensive evaluation of tumor necrosis in feline mammary tumors (FMTs) was conducted, by applying a semi-quantitative and a quantitative methodology for assessing necrosis. The interobserver agreement, the relationship with clinicopathological characteristics and the prognostic value of necrosis were analyzed in 154 FMT cases. Although subjectivity in the assessment of necrosis existed, an almost perfect agreement (weighted quadratic k = 0.851) between two observers was obtained. Furthermore, there was a significant positive correlation between the semi-quantitative and quantitative methods. Necrosis was more common and more extensive in malignant tumors than in their benign counterparts. Despite the non-significant results in the survival analysis, extensive necrosis was significantly associated with aggressive clinicopathological features, such as higher histological grade, high mitotic count and lymphovascular invasion. Our results support the potential relevance of necrosis in FMT.

CSIG-08. AGGRESSIVE HIGH-GRADE NF2 MUTANT MENINGIOMAS DOWNREGULATE ONCOGENIC YAP SIGNALING VIA THE UPREGULATION OF VGLL4 AND FAT3/4

Abstract Meningiomas are the most common primary brain tumors in adults. Although generally benign, a subset is of higher grade, shows aggressive growth behavior and recurs even after multiple surgeries. Around half of all meningiomas harbor inactivating mutations in NF2. While benign low-grade NF2 mutant meningiomas exhibit few genetic events in addition to NF2 inactivation, aggressive high-grade NF2 mutant meningiomas frequently harbor a highly aberrant genome. We and others have previously shown that NF2 inactivation leads to YAP1 activation and that YAP1 acts as the pivotal oncogenic driver in benign NF2 mutant meningiomas. Using bulk and single-cell RNA-Seq data from a large cohort of human meningiomas, we show that aggressive NF2 mutant meningiomas harbor decreased levels YAP1 activity compared to their benign counterparts. Furthermore, decreased expression levels of YAP target genes are significantly associated with an increased risk of recurrence. We then identify the increased expression of the YAP1 competitor VGLL4 as well as the YAP1 upstream regulators FAT3/4 as a potential mechanism for the downregulation of YAP activity in aggressive NF2 mutant meningiomas. High expression of these genes is significantly associated with an increased risk of recurrence. In vitro, overexpression of VGLL4 resulted in the downregulation of YAP activity in benign NF2 mutant meningioma cells, confirming the direct link between VGLL4 expression and decreased levels of YAP activity observed in aggressive NF2 mutant meningiomas. Our results shed new insight on the biology of benign and aggressive NF2 mutant meningiomas and may have important implications for the efficacy of therapies targeting oncogenic YAP1 in NF2 mutant meningiomas.

AlzDiscovery: A computational tool to identify Alzheimer's disease-causing missense mutations using protein structure information.

Alzheimer's disease (AD) is one of the most common forms of dementia and neurodegenerative diseases, characterized by the formation of neuritic plaques and neurofibrillary tangles. Many different proteins participate in this complicated pathogenic mechanism, and missense mutations can alter the folding and functions of these proteins, significantly increasing the risk of AD. However, many methods to identify AD-causing variants did not consider the effect of mutations from the perspective of a protein three-dimensional environment. Here, we present a machine learning-based analysis to classify the AD-causing mutations from their benign counterparts in 21 AD-related proteins leveraging both sequence- and structure-based features. Using computational tools to estimate the effect of mutations on protein stability, we first observed a bias of the pathogenic mutations with significant destabilizing effects on family AD-related proteins. Combining this insight, we built a generic predictive model, and improved the performance by tuning the sample weights in the training process. Our final model achieved the performance on area under the receiver operating characteristic curve up to 0.95 in the blind test and 0.70 in an independent clinical validation, outperforming all the state-of-the-art methods. Feature interpretation indicated that the hydrophobic environment and polar interaction contacts were crucial to the decision on pathogenic phenotypes of missense mutations. Finally, we presented a user-friendly web server, AlzDiscovery, for researchers to browse the predicted phenotypes of all possible missense mutations on these 21 AD-related proteins. Our study will be a valuable resource for AD screening and the development of personalized treatment.

Growth dynamics of lung nodules: implications for classification in lung cancer screening

BackgroundLung nodules observed in cancer screening are believed to grow exponentially, and their associated volume doubling time (VDT) has been proposed for nodule classification. This retrospective study aimed to elucidate the growth dynamics of lung nodules and determine the best classification as either benign or malignant.MethodsData were analyzed from 180 participants (73.7% male) enrolled in the I-ELCAP screening program (140 primary lung cancer and 40 benign) with three or more annual CT examinations before resection. Attenuation, volume, mass and growth patterns (decelerated, linear, subexponential, exponential and accelerated) were assessed and compared as classification methods.ResultsMost lung cancers (83/140) and few benign nodules (11/40) exhibited an accelerated, faster than exponential, growth pattern. Half (50%) of the benign nodules versus 26.4% of the malignant ones displayed decelerated growth. Differences in growth patterns allowed nodule malignancy to be classified, the most effective individual variable being the increase in volume between two-year-interval scans (ROC-AUC = 0.871). The same metric on the first two follow-ups yielded an AUC value of 0.769. Further classification into solid, part-solid or non-solid, improved results (ROC-AUC of 0.813 in the first year and 0.897 in the second year).ConclusionsIn our dataset, most lung cancers exhibited accelerated growth in contrast to their benign counterparts. A measure of volumetric growth allowed discrimination between benign and malignant nodules. Its classification power increased when adding information on nodule compactness. The combination of these two meaningful and easily obtained variables could be used to assess malignancy of lung cancer nodules.

Distinguishing follicular-type thyroid carcinomas from their benign counterparts, a study of 104 consecutively resected and needle-biopsied tumors

Distinguishing follicular-type thyroid carcinomas from their benign counterparts, a study of 104 consecutively resected and needle-biopsied tumors

Aggressive high-grade NF2 mutant meningiomas downregulate oncogenic YAP signaling via the upregulation of VGLL4 and FAT3/4.

Meningiomas are the most common primary central nervous system tumors in adults. Although generally benign, a subset is of higher grade and ultimately fatal. Around half of all meningiomas harbor inactivating mutations in NF2, leading to deregulation of oncogenic YAP1 activity. While benign NF2 mutant meningiomas exhibit few genetic events in addition to NF2 inactivation, aggressive high-grade NF2 mutant meningiomas frequently harbor a highly aberrant genome. It is unclear if NF2 mutant meningiomas of different grades are equally reliant on YAP activity. We analyzed bulk and single-cell RNA-Seq data from a large cohort of human meningiomas for the expression of YAP1 target genes and Hippo effectors as well as in vitro cell line experiments. Aggressive NF2 mutant meningiomas harbor decreased expression levels of YAP1 target genes and increased expression levels of the YAP1 antagonist VGLL4 and the upstream regulators FAT3/4 compared to their benign counterparts. Decreased expression of YAP1 target genes as well as high expression of VGLL4 and FAT3/4 is significantly associated with an increased risk of recurrence. In vitro, overexpression of VGLL4 resulted in the downregulation of YAP activity in benign NF2 mutant meningioma cells, confirming the direct link between VGLL4 expression and decreased levels of YAP activity observed in aggressive NF2 mutant meningiomas. Our results shed new insight into the biology of benign and aggressive NF2 mutant meningiomas and may have important implications for the efficacy of therapies targeting oncogenic YAP1 activity in NF2 mutant meningiomas.

New potential diagnostic markers for verrucous hyperplasia and verrucous carcinoma based on RNA-sequencing data

Verrucous carcinoma (VC) is a rare subtype of squamous cell carcinoma (SCC) characterized by its histological presentation as a low-grade tumor with no potential for metastasis, setting it apart from invasive SCC. However, distinguishing VC from its benign counterpart, verrucous hyperplasia (VH), is challenging due to their clinical and morphological similarities. Despite the importance of accurate diagnosis for determining treatment strategies, diagnosis of VH and VC relied only on lesion recurrence after resection. To address this challenge, we generated RNA profiling data from tissue samples of VH and VC patients to identify novel diagnostic markers. We analyzed differentially expressed (DE) mRNA and long non-coding RNA (lncRNA) in tissue samples from VH and VC patients. Additionally, ChIP-X Enrichment Analysis 3 (ChEA3) was conducted to identify the top five transcription factors potentially regulating the expression of DE mRNAs in VH and VC. Our analysis of mRNA and lncRNA expression profiles in VH and VC provides insights into the underlying molecular characteristics of these diseases and offers potential new diagnostic markers. The identification of specific DE genes and lncRNAs may enable clinicians to more accurately differentiate between VH and VC, leading to better treatment choices.

Computer-aided diagnosis of eyelid skin tumors using machine learning

ObjectiveTo develop an automated, new framework based on machine learning to diagnose malignant eyelid skin tumors. MethodsThis study used eyelid lesion images from Sheba Medical Center, a large tertiary center in Israel. Before model training, we pretrained our models on the International Skin Imaging Collaboration (ISIC) 2019 dataset consisting of 25,332 images. The proprietary eyelid data set was then used for fine-tuning. The data set contained multiple images per patient, aiming to classify malignant lesions in comparison to benign counterparts. ResultsThe analyzed data set consisted of images representing both benign and malignant eyelid lesions. For the benign category, a total of 373 images were sourced. By comparison, for the malignant category, 186 images were sourced. For the final model, at sensitivity of 93.8% (95% CI 80.0–100.0%), the model has a corresponding specificity of 73.7% (95% CI 60.0–87.1%). To further understand the decision-making process of our model, we employed heatmap visualization techniques, specifically gradient-weighted Class Activation Mapping. DiscussionThis study introduces a dependable model-aided diagnostic technology for assessing eyelid skin lesions. The model demonstrated accuracy comparable to human evaluation, effectively determining whether a lesion raises a high suspicion of malignancy or is benign. Such a model has the potential to alleviate the burden on the health care system, particularly benefiting rural areas, and enhancing the efficiency of clinicians and overall health care.

MYOEPITHELIAL CARCINOMA OF SOFT TISSUES OF THE RIGHT AXILLARY REGION WITH METASTASIS TO THE CECUM: A CLINICAL CASE

Relevance: Myoepithelial carcinoma is a morphologically diverse tumor that arises either de novo or due to the malignant transformation of its benign counterpart, myoepithelium. These are relatively lesser-known lesions rarely found in the head and neck area. Myoepithelial carcinoma (MC) is a rare malignancy primarily found in the salivary gland. MK can be confused with many other tumors outside the salivary glands, as a wide range of cytomorphological and immunohistochemical features characterizes them. Soft tissue MCs are extremely rare, although a salivary gland MC is relatively common and well-known with similar morphology. The histogenesis of soft tissue MC is still unknown. The tumor may have myoepithelial differentiation but is not derived from myoepithelial cells. Due to the rarity of soft tissue MCs, the number of studies and data on this tumor’s clinical and pathological characteristics are limited. In addition, the limited number of diagnostic criteria and prognostic parameters makes diagnosing and treating soft tissue MC difficult. The article describes a rare case of MC, formed from the soft tissues of the axillary region, with metastasis to the cecum. The purpose was to describe the imaging and clinicopathological features of axillary myoepithelial carcinoma of soft tissues with metastasis to the cecum and to form an understanding of this disease. Methods: A rare case of soft tissue CM of the axillary region with metastasis to the cecum is described. A 57-year-old woman complained of lymphadenopathy in the right axillary region in October 2020. Results: According to ultrasound examination, the lymph node is up to 3.0x3.5 cm in the right axillary region. Based on histopathological and immunohistochemical (IHC) data, on 02/03/2022, the final diagnosis was made: MK of the soft tissues of the right axillary region. According to positron emission tomography/computed tomography (PET/CT), after 4 months, a local focus of active accumulation was detected in the projection of the cecum, with an adjacent enlarged regional lymph node of the paracolic group. On January 18, 2023, surgical treatment was performed in the following volume: “Right-sided hemicolectomy.” Histological examination confirmed MC. According to the multidisciplinary team’s (MDG) decision, the patient received 3 courses of targeted therapy. Conclusion: This case report raises awareness and improves MC diagnostics and treatment.

Improving data participation for the development of artificial intelligence in dermatology

Artificial intelligence (AI) has the potential to significantly impact many aspects of dermatology. The visual nature of dermatology lends itself to innovations in this space. The robustness of AI algorithms depends on the quality, quantity, and variety of data on which it is trained and tested. Image collections can suffer from inconsistencies in image quality, underrepresentation of various anatomic sites and skin tones, and lack of benign counterparts leading to underperformance of algorithms in contexts other than one in which it is developed. Access to care, trust, rights, control, and transparency all play roles in the willingness of patients and health care providers and systems to collect, provide, and share data. Opportunities to improve data participation for the development of AI include the establishment of data hubs and public algorithms, federated learning strategies, development of renumeration ecosystems for patients and systems, and development of criteria and mechanisms for transparency.

BapFL: You can Backdoor Personalized Federated Learning

In federated learning (FL), malicious clients could manipulate the predictions of the trained model through backdoor attacks, posing a significant threat to the security of FL systems. Existing research primarily focuses on backdoor attacks and defenses within the generic federated learning scenario, where all clients collaborate to train a single global model. A recent study conducted by Qin et al. [ 24 ] marks the initial exploration of backdoor attacks within the personalized federated learning (pFL) scenario, where each client constructs a personalized model based on its local data. Notably, the study demonstrates that pFL methods with parameter decoupling can significantly enhance robustness against backdoor attacks. However, in this article, we whistleblow that pFL methods with parameter decoupling are still vulnerable to backdoor attacks. The resistance of pFL methods with parameter decoupling is attributed to the heterogeneous classifiers between malicious clients and benign counterparts. We analyze two direct causes of the heterogeneous classifiers: (1) data heterogeneity inherently exists among clients and (2) poisoning by malicious clients further exacerbates the data heterogeneity. To address these issues, we propose a two-pronged attack method, BapFL, which comprises two simple yet effective strategies: (1) poisoning only the feature encoder while keeping the classifier fixed and (2) diversifying the classifier through noise introduction to simulate that of the benign clients. Extensive experiments on three benchmark datasets under varying conditions demonstrate the effectiveness of our proposed attack. Additionally, we evaluate the effectiveness of six widely used defense methods and find that BapFL still poses a significant threat even in the presence of the best defense, Multi-Krum. We hope to inspire further research on attack and defense strategies in pFL scenarios. The code is available at: https://github.com/BapFL/code

Aggressive high-grade NF2 mutant meningiomas downregulate oncogenic YAP signaling via the upregulation of VGLL4 and FAT3/4.

Meningiomas are the most common primary brain tumors in adults. Although generally benign, a subset of meningiomas is of higher grade, shows aggressive growth behavior and recurs even after multiple surgeries. Around half of all meningiomas harbor inactivating mutations in NF2. While benign low-grade NF2 mutant meningiomas exhibit few genetic events in addition to NF2 inactivation, aggressive high-grade NF2 mutant meningiomas frequently harbor a highly aberrant genome. We and others have previously shown that NF2 inactivation leads to YAP1 activation and that YAP1 acts as the pivotal oncogenic driver in benign NF2 mutant meningiomas. Using bulk and single-cell RNA-Seq data from a large cohort of human meningiomas, we show that aggressive NF2 mutant meningiomas harbor decreased levels YAP1 activity compared to their benign counterparts. Decreased expression levels of YAP target genes are significantly associated with an increased risk of recurrence. We then identify the increased expression of the YAP1 competitor VGLL4 as well as the YAP1 upstream regulators FAT3/4 as a potential mechanism for the downregulation of YAP activity in aggressive NF2 mutant meningiomas. High expression of these genes is significantly associated with an increased risk of recurrence. In vitro, overexpression of VGLL4 resulted in the downregulation of YAP activity in benign NF2 mutant meningioma cells, confirming the direct link between VGLL4 expression and decreased levels of YAP activity observed in aggressive NF2 mutant meningiomas. Our results shed new insight on the biology of benign and aggressive NF2 mutant meningiomas and may have important implications for the efficacy of therapies targeting oncogenic YAP1 activity in NF2 mutant meningiomas.

Advancements in hepatocellular carcinoma management: the role of 18F-FDG PET-CT in diagnosing portal vein tumor thrombosis.

Portal vein thrombosis, a relatively frequent complication associated with hepatocellular carcinoma (HCC) and liver cirrhosis, is recognized as a significant global health concern. This is mainly due to these conditions' high prevalence and potentially severe outcomes. The aim of our study was to conduct a comprehensive literature review to evaluate the efficacy, accuracy, and clinical implications of 18F-FDG PET-CT in diagnosing and managing portal vein tumor thrombosis (PVTT) in patients with HCC. HCC, which accounts for 80% of liver malignancies, ranks as the fourth most prevalent cancer globally and is a significant contributor to cancer-related mortality. The majority of HCC patients are diagnosed at an advanced stage, leading to a deterioration in patient outcomes. Involvement of the portal vein is also a significant negative factor. This review analyzes the application of 18F-FDG PET-CT in the detection and management of PVTT in patients with HCC, with an emphasis on the importance of the maximum standardized uptake value as an essential diagnostic and prognostic marker. 18F-FDG PET-CT is invaluable for detecting recurrence and guiding management strategies, particularly in patients with high-grade HCC, and plays a pivotal role in differentiating malignant portal vein thrombi from their benign counterparts.

Radiomics analysis for distinctive identification of COVID-19 pulmonary nodules from other benign and malignant counterparts

This observational study investigated the potential of radiomics as a non-invasive adjunct to CT in distinguishing COVID-19 lung nodules from other benign and malignant lung nodules. Lesion segmentation, feature extraction, and machine learning algorithms, including decision tree, support vector machine, random forest, feed-forward neural network, and discriminant analysis, were employed in the radiomics workflow. Key features such as Idmn, skewness, and long-run low grey level emphasis were identified as crucial in differentiation. The model demonstrated an accuracy of 83% in distinguishing COVID-19 from other benign nodules and 88% from malignant nodules. This study concludes that radiomics, through machine learning, serves as a valuable tool for non-invasive discrimination between COVID-19 and other benign and malignant lung nodules. The findings suggest the potential complementary role of radiomics in patients with COVID-19 pneumonia exhibiting lung nodules and suspicion of concurrent lung pathologies. The clinical relevance lies in the utilization of radiomics analysis for feature extraction and classification, contributing to the enhanced differentiation of lung nodules, particularly in the context of COVID-19.

Metastatic Granular Cell Tumor: A Rare Entity.

Granular cell tumor, which is thought to recapitulate a Schwann cell phenotype, is a very rare neoplasm that belongs to soft tissue tumors. It can be classified as benign, atypical or malignant, based on specific histological criteria, with the majority of cases exhibiting an indolent behavior. Its biology and clinical course are poorly understood and its optimal management is yet to be defined, given the rarity of cases. Here we describe an atypical granular cell tumor in the upper middle back skin that evolved after a thirty-year indolent period. Despite complete surgical removal, the patient experienced a recurrence, both local and in the lungs, following an aggressive clinical course. Data on management of metastatic disease are extremely scarce, comprised exclusively of case reports. Therefore, we administered to the patient systemic therapy according to soft tissue sarcoma guidelines, which led to disease progression, with fatal outcome. In conclusion, recurrent and/or metastatic granular cell tumor is a rare disease that can be life-threatening, for which response to different therapies is unknown. The biologic behavior of atypical and malignant granular cell tumor is quite different from its benign counterpart, evoking soft tissue sarcomas, and its diagnosis should alert clinicians. The role of adjuvant chemotherapy and radiation therapy in this setting should be explored, to limit disease recurrence.

Implant-supported prosthetic rehabilitation after Ameloblastomas treatment: a systematic review

BackgroundAmeloblastoma (AM), the benign counterpart of ameloblastic carcinoma, is a benign odontogenic tumor of epithelial origin, naturally aggressive, with unlimited growth potential and a high tendency to relapse if not adequately removed. Patients with AM treated surgically can benefit from dental implant therapy, promoting oral rehabilitation and improving their quality of life. The present study aimed to determine the survival rate of dental implants placed after surgical treatment of patients affected by AM. In addition, there were two secondary objectives: 1) To evaluate which dental implant loading protocols are most frequently used and 2) To determine the type of prosthetic restoration most commonly used in these patients.MethodsThe Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were followed during the study. Searches were performed in three databases (PubMed/MEDLINE, Scopus, and Google Scholar) until November 2023. Additionally, the electronic search was enriched by an iterative hand search of journals related to oral pathology and medicine, maxillofacial surgery, and oral prosthodontics and implantology. Only reports and case series in English from January 2003 to date were included. The Joanna Briggs Institute tool (JBI-Case Reports/Case Series) was used for the study quality assessment.ResultsThe total number of patients and implants studied were 64 and 271, respectively, all with surgically treated AM. The patient’s ages ranged from 8 to 79 years, with a mean (SD) age of 37.3 ± 16.4. Fifty-three percent were male and 47% were female. The range of follow-up duration was 1 to 22 years. An implant survival/success rate of 98.1% was reported. In addition, most of them were conventionally loaded (38.3%). Hybrid implant-supported fixed dentures were the most commonly used by prosthodontists (53%).ConclusionsOral rehabilitation with dental implants inserted in free flaps for orofacial reconstruction in surgically treated patients with AM can be considered a safe and successful treatment modality.

SilentTrig: An imperceptible backdoor attack against speaker identification with hidden triggers

Speaker identification based on deep learning is known to be susceptible to backdoor attacks. However, the current research on audio backdoor attacks is limited, and these attacks often use obvious noises as triggers, which can raise suspicion among users. In this paper, we introduce SilentTrig, a novel and imperceptible backdoor attack method targeted at speaker identification. Our approach involves utilizing an optimized steganographic network to embed triggers into benign audio samples and implementing a two-stage adversarial optimization process. This ensures that the poisoned samples are acoustically indistinguishable from their benign counterparts, resulting in a substantially improved attack imperceptibility. We evaluate SilentTrig on two datasets and four state-of-the-art models. The results demonstrate a high Attack Success Rate (ASR) of up to 99.2%, a Just Noticeable Difference (JND) of only 0.3, and resistance to typical defense methods such as Neural Cleanse and Fine-Pruning.

Malignant proliferating trichilemmal tumor in male: A rare case entity with diagnostic dilemma

Abstract Trichilemmal tumor is a rare hair follicle tumor that is, thought to occur from a malignant transformation of a benign trichilemmoma. The tumor develops from the outer root sheath of the hair follicle. The patient underwent a wide local excision with 1 cm clear margin. The defect was covered by split thick skin graft harvested from ipsilateral thigh after consulting the plastic surgery department. Trichilemmal cyst can be misdiagnosed as other cutaneous lesions. Like in our case, initial FNAC was suggestive of a epidermoid cyst but post excision Histopathological examination gave us the real picture of a trichilemmal tumor. Recurrent tumors are very rare and can get misdiagnosed as squamous cell carcinoma. Malignant proliferating trichilemmal tumors are rare cutaneous tumors that are very rare in males. These tumors can be misdiagnosed as squamous cell carcinoma and require external stimuli for malignant conversion from benign counterparts. Wide local excision is sufficient for treatment.

Telengiectatic osteosarcoma of mandible with special emphasis on immunohistochemical and molecular characteristics: A case report with review of literature

AbstractBackgroundTelangiectatic osteosarcoma (TOS) is an uncommon pathology accounting for about 0.4%–12% of all osteosarcomas with predilection for younger adults. It is most frequently seen in the metaphysis of long bones, appearing as painful osteolytic mass that histopathologically characterized by dilated, blood‐filled vascular spaces lined by malignant osteoblasts along with osteoid formation. It has exchangeable clinical, radiological and pathological features with benign lesions like aneurysmal bone cyst and giant cell tumour of bone as well. Thus, delineating this malignancy from its benign counterparts is a crucial part in the therapeutic management.AimTo report a case of telengiectatic osteosarcoma of jaw in a 17 year old female patient with special highlights on molecular diagnostics and therapeutic modules.Materials and MethodsA panel of immunohistochemical markers comprising of SATB2, CDK4, MDM2, panCK, CD31, desmin, NKX2.2 and TLE1 were employed in combination with fluorescent in‐situ hybridization to detect the prevalence of rearrangement in CDK4 and MDM2 genes.ResultsOn immunohistochemistry, the neoplastic cells were strongly positive for SATB2 and negative for CDK4, MDM2, panCK, CD31, desmin, NKX2.2 and TLE1. Fluorescent in‐situ hybridization of CDK4 and MDM2 genes was also negative.ConclusionConsidering its rarity in jaws combined with clinicopathological overlap with other benign pathologies, diagnosis of this entity is crucial in treatment planning and prognostic significance. Moreover, only five cases of TOS have been reported so far in the craniofacial region. Here, we have reported the sixth case of its kind with detailed clarification pertaining to its immunohistochemical and molecular aspects.