Bonding positional accuracy of attachments and marginal adaptation of in-house aligners - A quality improvement laboratory study.

OBJECTIVES: To evaluate the 3D accuracy of attachment positioning and the adaptation of aligners to attachments using in-house templates made with either polyethylene terephthalate glycol (PETG) or ethylene-vinyl acetate (EVA) and either pressure or vacuum thermoforming machines. MATERIALS AND METHODS: Overall, 140 test specimens were resin-printed. Templates for the attachment bonding were made with 1-mm EVA or 0.5-mm PETG laminates. Orthodontic aligners were manufactured with 0.75-mm PETG. The thermoplastification process was carried out using either vacuum or pressure machines. The positional differences between the virtual and bonded attachments were assessed in the X, Y and Z coordinates. The marginal adaptation between the aligners and the attachments was measured. RESULTS: Minor inaccuracies in the positioning of the attachments were observed in all combinations of thermoforming machines and plastic laminates used to fabricate the templates, mainly in the superior-inferior (Z) dimension. PETG performed better than EVA in the anterior region (p < .05). No association was found between thermoplastification machines and the accuracy of the positioning of the attachments (p > .05). While small misadaptations between the aligners and the attachments were observed, the EVA templates performed better than the PETG templates. CONCLUSIONS: The inaccuracy of the attachment positioning and the misadaptation of the aligners to the attachments were slight. The vacuum and pressure thermoplastification machines showed no difference in attachment positioning accuracy. The PETG template was better than the EVA template in the anterior region, but the EVA attachments presented a better adaptation to the aligners than the PETG attachments.

N-acetylgalactosaminyltransferase GALNT6 is a potential therapeutic target of clear cell renal cell carcinoma progression.

High expression of truncated O-glycans Tn antigen predicts adverse clinical outcome in patients with clear cell renal cell carcinoma (ccRCC). To understand the biosynthetic underpinnings of Tn antigen changes in ccRCC, we focused on N-acetylgalactosaminyltransferases (GALNTs, also known as GalNAcTs) known to be involved in Tn antigen synthesis. Data from GSE15641 profile and local cohort showed that GALNT6 was significantly upregulated in ccRCC tissues. The current study aimed to determine the role of GALNT6 in ccRCC, and whether GALNT6-mediated O-glycosylation aggravates malignant behaviors. Gain- and loss-of-function experiments showed that overexpression of GALNT6 accelerated ccRCC cell proliferation, migration, and invasion, as well as promoted ccRCC-derived xenograft tumor growth and lung metastasis. In line with this, silencing of GALNT6 yielded the opposite results. Mechanically, high expression of GALNT6 led to the accumulation of Tn antigen in ccRCC cells. By undertaking immunoprecipitation coupled with liquid chromatography/mass spectrometry, vicia villosa agglutinin blot, and site-directed mutagenesis assays, we found that O-glycosylation of prohibitin 2 (PHB2) at Ser161 was required for the GALNT6-induced ccRCC cell proliferation, migration, and invasion. Additionally, we identified lens epithelium-derived growth factor (LEDGF) as a key regulator of GALNT6 transcriptional induction in ccRCC growth and an upstream contributor to ccRCC aggressive behavior. Collectively, our findings indicate that GALNT6-mediated abnormal O-glycosylation promotes ccRCC progression, which provides a potential therapeutic target in ccRCC development.

CACNA1H restrains chemotherapy resistance in ovarian clear cell carcinoma cells by repressing autophagy.

Ovarian clear cell carcinoma (OCCC) is a subtype of ovarian cancer and is highly malignant with high chemoresistance. CACNA1H is pivotal in tumor development. However, the role of CACNA1H in the acquisition process of chemotherapeutic resistance in OCCC cells is rarely reported. Therefore, this study aimed to explore the role of CACNA1H in chemotherapy resistance of OCCC cells and its related mechanism. Based on bioinformatics analysis, we found that CACNA1H was downregulated in chemoresistant OCCC patients compared to chemosensitive OCCC patients. Comparing DDP-resistant and sensitive OCCC cell lines, the resistant strain showed lower CACNA1H mRNA expression. CACNA1H expression was associated with calcium signaling pathways in chemoresistant OCCC patients. CACNA1H mRNA expression was significantly downregulated in OCCC cells compared to normal ovarian epithelial cells. When CACNA1H was overexpressed, intracellular Ca2+ concentration and protein levels of p-CaMKII and p-Akt were significantly upregulated, while protein levels of LC3-II/LC3-I and Beclin1 were downregulated, indicating a repression of autophagy. The rescue experiment revealed that CACNA1H overexpression in drug-resistant OCCC cells reduced autophagy-induced DDP resistance via CaMKII/Akt signaling. Overall, CACNA1H increased intracellular Ca2+ concentration and activated CaMKII/Akt signaling pathway in OCCC, thereby repressing autophagy to maintain the sensitivity of OCCC cells to DDP.

Orthodontic aligner therapy outcomes in children with autism spectrum disorder.

BACKGROUND: Children with autism spectrum disorder (ASD) face unique challenges in oral care. Aligner therapy offers a promising alternative to conventional approaches for this patient group. AIM: To evaluate orthodontic aligner therapy outcomes in children with ASD using the Peer Assessment Rating (PAR) Index and the Index of Complexity, Outcome, and Need (ICON), and to investigate whether concomitant disorders affect ICON, PAR scores, and treatment duration. DESIGN: Two calibrated observers assessed digital dental casts and intraoral pictures of 37 children with ASD before (T0) and after (T1) their treatment. At T0, the participants' average age was 12.9 years (SD = 1.68); at T1, post-therapy, the average age was 14.9 years (SD = 1.51). All participants underwent orthodontic aligner therapy. Statistical methods employed in this study included descriptive analysis, Wilcoxon tests, and univariate linear regression. RESULTS: Posttreatment, median ICON scores decreased significantly from 74 to 14, and median PAR scores from 36 to 8 (p < .0001), demonstrating "excellent to substantial" improvement in 89.2% (n = 33) of the children. Comorbidities, present in 62% of patients, did not significantly affect treatment duration (22.6 ± 11.02 months). CONCLUSION: Children with ASD significantly benefit from orthodontic aligner therapy, emphasizing the need for tailored orthodontic care.

Radiomics nomogram based on CT radiomics features and clinical factors for prediction of Ki-67 expression and prognosis in clear cell renal cell carcinoma: a two-center study.

OBJECTIVES: To develop and validate a radiomics nomogram combining radiomics features and clinical factors for preoperative evaluation of Ki-67 expression status and prognostic prediction in clear cell renal cell carcinoma (ccRCC). METHODS: Two medical centers of 185 ccRCC patients were included, and each of them formed a training group (n = 130) and a validation group (n = 55). The independent predictor of Ki-67 expression status was identified by univariate and multivariate regression, and radiomics features were extracted from the preoperative CT images. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) were used to identify the radiomics features that were most relevant for high Ki-67 expression. Subsequently, clinical model, radiomics signature (RS), and radiomics nomogram were established. The performance for prediction of Ki-67 expression status was validated using area under curve (AUC), calibration curve, Delong test, decision curve analysis (DCA). Prognostic prediction was assessed by survival curve and concordance index (C-index). RESULTS: Tumour size was the only independent predictor of Ki-67 expression status. Five radiomics features were finally identified to construct the RS (AUC: training group, 0.821; validation group, 0.799). The radiomics nomogram achieved a higher AUC (training group, 0.841; validation group, 0.814) and clinical net benefit. Besides, the radiomics nomogram provided a highest C-index (training group, 0.841; validation group, 0.820) in predicting prognosis for ccRCC patients. CONCLUSIONS: The radiomics nomogram can accurately predict the Ki-67 expression status and exhibit a great capacity for prognostic prediction in patients with ccRCC and may provide value for tailoring personalized treatment strategies and facilitating comprehensive clinical monitoring for ccRCC patients.

STAC3 as a poor prognostic biomarker in renal clear cell carcinoma: relationship with immune infiltration.

Calcium ions (Ca2+) are crucial in tumorigenesis and progression, with their elevated levels indicating a negative prognosis in Kidney Renal Clear Cell Carcinoma (KIRC). The influence of genes regulating calcium ions on the survival outcomes of KIRC patients and their interaction with the tumor's immune microenvironment is yet to be fully understood. This study analyzed gene expression data from KIRC tumor and adjacent non-tumor tissues using the TCGA-KIRC dataset to pinpoint genes that are differentially expressed in KIRC. Intersection of these genes with those regulating calcium ions highlighted specific calcium ion-regulating genes that exhibit differential expression in KIRC. Subsequently, prognostic risk models were developed using univariate Cox and LASSO-Cox regression analyses to verify their diagnostic precision. Additionally, the study investigated the correlation between tumor immunity and KIRC patient outcomes, assessing the contribution of STAC3 genes to tumor immunity. Further exploration entailed SSGASE, single-cell analysis, pseudotime analysis and both in vivo and in vitro experiments to evaluate STAC3's role in tumor immunity and progression. Notably, STAC3 was significantly overexpressed in tumor specimens and positively correlated with the degree of malignancy of KIRC, affecting patients' prognosis. Elevated STAC3 expression correlated with enhanced immune infiltration in KIRC tumors. Furthermore, silencing STAC3 curtailed KIRC cell proliferation, migration, invasion, and stemness properties. Experimental models in mice confirmed that STAC3 knockdown led to a reduction in tumor growth. Elevated STAC3 expression is intricately linked with immune infiltration in KIRC tumors, as well as with the aggressive biological behaviors of tumor cells, including their proliferation, migration, and invasion. Targeting STAC3 presents a promising strategy to augment the efficacy of current therapeutic approaches and to better the survival outcomes of patients with KIRC.

Prediction of clear cell renal cell carcinoma ≤ 4cm: visual assessment of ultrasound characteristics versus ultrasonographic radiomics analysis.

Objective: To investigate the diagnostic efficacy of the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model based on ultrasonographic radiomics for the differentiation of small clear cell Renal Cell Carcinoma (ccRCC) and Renal Angiomyolipoma (RAML). Methods: The clinical, ultrasound, and contrast-enhanced CT(CECT) imaging data of 302 small renal tumors (maximum diameter ≤ 4cm) patients in Tianjin Medical University Cancer Institute and Hospital from June 2018 to June 2022 were retrospectively analyzed, with 182 patients of ccRCC and 120 patients of RAML. The ultrasound images of the largest diameter of renal tumors were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from ROI segmented images. The patients were randomly divided into training and internal validation cohorts in the ratio of 7:3. The Random Forest algorithm of the Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model. The efficacy of the prediction models was verified in an independent external validation cohort consisting of 69 patients, from 230 small renal tumor patients in two different institutions. The Delong test compared the predictive ability of three models and CECT. Calibration Curve and clinical Decision Curve Analysis were applied to evaluate the model and determine the net benefit to patients. Results: 491 ultrasonographic radiomics features were extracted from 302 small renal tumor patients, and 9 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. In the internal validation cohort, the area under the curve (AUC), sensitivity, specificity, and accuracy of the clinical ultrasound imaging model, ultrasonographic radiomics model, comprehensive model, and CECT were 0.75, 76.7%, 60.0%, 70.0%; 0.80, 85.6%, 61.7%, 76.0%; 0.88, 90.6%, 76.7%, 85.0% and 0.90, 92.6%, 88.9%, 91.1%, respectively. In the external validation cohort, AUC, sensitivity, specificity, and accuracy of the three models and CECT were 0.73, 67.5%, 69.1%, 68.3%; 0.89, 86.7%, 80.0%, 83.5%; 0.90, 85.0%, 85.5%, 85.2% and 0.91, 94.6%, 88.3%, 91.3%, respectively. The DeLong test showed no significant difference between the clinical ultrasound imaging model and the ultrasonographic radiomics model (Z=-1.287, P=0.198). The comprehensive model showed superior diagnostic performance than the ultrasonographic radiomics model (Z=4. 394, P<0.001) and the clinical ultrasound imaging model (Z=4. 732, P<0.001). Moreover, there was no significant difference in AUC between the comprehensive model and CECT (Z=-0.252, P=0.801). Both in the internal and external validation cohort, the Calibration Curve and Decision Curve Analysis showed a better performance of the comprehensive model. Conclusion: It is feasible to construct an ultrasonographic radiomics model for distinguishing small ccRCC and RAML based on ultrasound images, and the diagnostic performance of the comprehensive model is superior to the clinical ultrasound imaging model and ultrasonographic radiomics model, similar to that of CECT.

Microbial Changes in the Periodontal Environment Due to Orthodontic Appliances: A Review.

Orthodontic appliances significantly influence the microbiological dynamics within the oral cavity, transforming symbiotic relationships into dysbiotic states that can lead to periodontal diseases. This review synthesizes current findings on how orthodontic treatments, particularly fixed and removable appliances, foster niches for bacterial accumulation and complicate oral hygiene maintenance. Advanced culture-independent methods were employed to identify shifts toward anaerobic and pathogenic bacteria, with fixed appliances showing a more pronounced impact compared to clear aligners. The study underscores the importance of meticulous oral hygiene practices and routine dental monitoring to manage these microbial shifts effectively. By highlighting the relationship between appliance type, surface characteristics, treatment duration, and microbial changes, this review aims to enhance dental professionals' understanding of periodontal risks associated with orthodontic appliances and strategies to mitigate these risks. The findings are intended to guide clinicians in optimizing orthodontic care to prevent plaque-associated diseases, ensuring better periodontal health outcomes for patients undergoing orthodontic treatment.

How accurate is predicted root movement achieved in four first-premolar extraction cases with Invisalign?

OBJECTIVES: This study aims to compare the achieved and predicted root movements in adults after four first-premolar extractions and Invisalign treatment. MATERIALS AND METHODS: Thirty-three consecutive adults (22 Class I, 9 Cusp-to-cusp Class II and 2 Cusp-to-cusp Class III) from a single clinical division who completed the first series of aligners after premolar extractions were included in this retrospective study. A pretreatment cone-beam computed tomography model was registered onto the pretreatment surface-scanned dental model (SSDM) to locate the pretreatment root apices of the whole dentition. These were copied and transferred to the predicted and achieved post-treatment SSDMs to acquire the locations of the predicted and achieved post-treatment root apices. The differences between predicted and achieved root movements (DPARMs) were tested using the paired t-test or Wilcoxon signed rank test. RESULTS: In the anteroposterior direction, posterior root movements of maxillary and mandibular anterior teeth were poorly achieved (3.24-5.74 mm DPARMs, p < .05). In the vertical direction, roots of maxillary anterior teeth achieved greater intrusion (0.70-0.93 mm DPARMs, p < .05), while those of mandibular incisors achieved less intrusion (0.57-0.65 mm DPARMs, p < .05) than predicted. In the mediolateral direction, lateral incisor roots did not move distally (-0.65 to -0.96 mm DPARMs, p < .05), while those of canines did not move buccally, compared with the prediction (-0.75 mm DPARMs, p < .05). CONCLUSIONS: In the four first-premolar extraction treatments with Invisalign, root movements were not achieved as predicted, particularly for anterior teeth in the anteroposterior direction.

Integrated genomic/epigenomic analysis stratifies subtypes of clear cell ovarian carcinoma, highlighting their cellular origin.

The cellular origin of clear cell ovarian carcinoma (CCOC), a major histological subtype of ovarian carcinoma remains elusive. Here, we explored the candidate cellular origin and identify molecular subtypes using integrated genomic/epigenomic analysis. We performed whole exome-sequencing, microarray, and DNA methylation array in 78 CCOC samples according to the original diagnosis. The findings revealed that ARID1A and/or PIK3CA mutations were mutually exclusive with DNA repair related genes, including TP53, BRCA1, and ATM. Clustering of CCOC and other ovarian carcinomas (n = 270) with normal tissues from the fallopian tube, ovarian surface epithelium, endometrial epithelium, and pelvic peritoneum mesothelium (PPM) in a methylation array showed that major CCOC subtypes (with ARID1A and/or PIK3CA mutations) were associated with the PPM-lile cluster (n = 64). This cluster was sub-divided into three clusters: (1) mismatch repair (MMR) deficient with tumor mutational burden-high (n = 2), (2) alteration of ARID1A (n = 51), and (3) ARID1A wild-type (n = 11). The remaining samples (n = 14) were subdivided into (4) ovarian surface epithelium-like (n = 11) and (5) fallopian tube-like (considered as high-grade serous histotype; n = 3). Among these, subtypes (1-3) and others (4 and 5) were found to be associated with immunoreactive signatures and epithelial-mesenchymal transition, respectively. These results contribute to the stratification of CCOC into biological subtypes.

The Radiogenomic Landscape of Clear Cell Renal Cell Carcinoma: Insights into Lipid Metabolism through Evaluation of ADFP Expression.

This study aims to explore the relationship between radiological imaging and genomic characteristics in clear cell renal cell carcinoma (ccRCC), focusing on the expression of adipose differentiation-related protein (ADFP) detected through computed tomography (CT). The goal is to establish a radiogenomic lipid profile and understand its association with tumor characteristics. Data from The Cancer Genome Atlas (TCGA) and the Cancer Imaging Archive (TCIA) were utilized to correlate imaging features with adipose differentiation-related protein (ADFP) expression in ccRCC. CT scans assessed various tumor features, including size, composition, margin, necrosis, and growth pattern, alongside measurements of tumoral Hounsfield units (HU) and abdominal adipose tissue compartments. Statistical analyses compared demographics, clinical-pathological features, adipose tissue quantification, and tumoral HU between groups. Among 197 patients, 22.8% exhibited ADFP expression significantly associated with hydronephrosis. Low-grade ccRCC patients expressing ADFP had higher quantities of visceral and subcutaneous adipose tissue and lower tumoral HU values compared to their high-grade counterparts. Similar trends were observed in low-grade ccRCC patients without ADFP expression. ADFP expression in ccRCC correlates with specific imaging features such as hydronephrosis and altered adipose tissue distribution. Low-grade ccRCC patients with ADFP expression display a distinct lipid metabolic profile, emphasizing the relationship between radiological features, genomic expression, and tumor metabolism. These findings suggest potential for personalized diagnostic and therapeutic strategies targeting tumor lipid metabolism.

Deciphering the Effects of the PYCR Family on Cell Function, Prognostic Value, Immune Infiltration in ccRCC and Pan-Cancer.

Pyrroline-5-carboxylate reductase (PYCR) is pivotal in converting pyrroline-5-carboxylate (P5C) to proline, the final step in proline synthesis. Three isoforms, PYCR1, PYCR2, and PYCR3, existed and played significant regulatory roles in tumor initiation and progression. In this study, we first assessed the molecular and immune characteristics of PYCRs by a pan-cancer analysis, especially focusing on their prognostic relevance. Then, a kidney renal clear cell carcinoma (KIRC)-specific prognostic model was established, incorporating pathomics features to enhance predictive capabilities. The biological functions and regulatory mechanisms of PYCR1 and PYCR2 were investigated by in vitro experiments in renal cancer cells. The PYCRs' expressions were elevated in diverse tumors, correlating with unfavorable clinical outcomes. PYCRs were enriched in cancer signaling pathways, significantly correlating with immune cell infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI). In KIRC, a prognostic model based on PYCR1 and PYCR2 was independently validated statistically. Leveraging features from H&E-stained images, a pathomics feature model reliably predicted patient prognosis. In vitro experiments demonstrated that PYCR1 and PYCR2 enhanced the proliferation and migration of renal carcinoma cells by activating the mTOR pathway, at least in part. This study underscores PYCRs' pivotal role in various tumors, positioning them as potential prognostic biomarkers and therapeutic targets, particularly in malignancies like KIRC. The findings emphasize the need for a broader exploration of PYCRs' implications in pan-cancer contexts.

Construction of an autophagy-related genes risk model as predicting prognosis: BAG1 suppresses growth of clear cell renal cell carcinoma.

BACKGROUND: The incidence of clear cell renal cell carcinoma (ccRCC) is increasing annually. While the cure rate and prognosis of early ccRCC are promising, the 5-year survival rate of patients with metastatic ccRCC is below 12%. Autophagy disfunction is closely related to infection, cancer, neurodegeneration and aging. Nevertheless, there has been limited exploration of the association between autophagy and ccRCC through bioinformatics analysis. METHODS: A novel risk model of autophagy-related genes (ARGs) was constructed to predict the prognosis of patients with ccRCC and guide the individualized treatment to some extent. Relevant data samples were obtained from the TCGA database, and ccRCC-related ARGs were identified by Pearson correlation analysis, leading to the establishment of a risk model covering 10 ccRCC-related ARGs. Many indicators were used to assess the accuracy of the risk model. RESULTS: Receiver operating characteristic (ROC) curve analysis showed that the risk model had high accuracy, indicating that the risk model could predict the prognosis of ccRCC patients. Moreover, the findings revealed significant differences about immune and metabolic features in low- and high-risk groups. The study also found that BAG1 within the risk model was closely related to the prognosis of ccRCC and an independent risk factor. In vitro and in vivo experiments validated for the first time that BAG1 could suppress the proliferation, migration, and invasion of ccRCC. CONCLUSION: The construction of ARGs risk model, can well predict the prognosis of ccRCC patients, and provide guidance for individual therapy to patients. It was also found that BAG1 has significant prognostic value for ccRCC patients and acts as a tumor suppressor gene in ccRCC. These findings have crucial implications for the prognosis and treatment of ccRCC patients.

Structure of Ground Vegetation and Natural Regeneration of Tree Species in 12- to 15-Year-Old Bilberry Pine Forest-Clear-cut Complex of Middle Taiga Subzone.

Abstract-Logging in mature stands where part of the forest is harvested in one or several cuts and part is retained (clearcutting and alternate strip cutting) results in the formation of an ecotone complex (EC), which includes a forest (F) zone, a forest edge (FE) as a transition from the forest to the clear-cut under the canopy, a clear-cut edge (CE) as a transition from the forest to the clear-cut outside of the canopy, and the clear-cut proper (C). The composition and structure of ground vegetation and natural regeneration of woody species (Pinus sylvestris L., Picea abies (L.) H. Karst., Betula sp., Populus tremula L., Sorbus aucuparia L., and Juniperus communis L.) were studied in a bilberry pine forest-clear-cut ecotone complex 12-15 years after stand removal. Specific structural features of ground vegetation and undergrowth (including tree regeneration) were observed in each of the four zones of the ecotone complex formed after logging of the mature forest. A typical forest habitat (zone F) showed a minimum number of young regeneration of Pinus sylvestris, Picea abies, Betula sp., Populus tremula, and Sorbus aucuparia and the highest abundance of the lingonberry V. vitis-idaea L. and bilberry Vaccinium myrtillus L. with a maximum height and a maximum yield of bilberry plants. The amount of tree regeneration in the FE zone was much the same as in the F zone. The projective cover, maximum shoot height, and yield of bilberry and the maximum shoot height of lingonberry in the FE zone were significantly lower than in the F zone. The transitional zone on the clear-cut side (CE) and the clear-cut proper (C) strikingly differed from the forest (F and FE) zones of the ecotone complex by a greater number of deciduous and pine regeneration and a low abundance of dwarf shrubs. The clear-cut proper (C) differed from the CE zone by a higher abundance of grasses and forbs and an established tree regeneration layer composed of pine, birch, and aspen.

Prognostic Model and Immune Response of Clear Cell Renal Cell Carcinoma Based on Co-Expression Genes Signature.

BACKGROUND: The identification of reliable prognostic markers is crucial for optimizing patient management and improving clinical outcomes in clear cell renal cell carcinoma (ccRCC). METHODS: We used the GSE89563 dataset from the GEO database and the Kidney Clear Cell Carcinoma (KIRC) dataset from the TCGA database to develop a prognostic model based on weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization (NMF) to predict disease progression and prognosis in ccRCC. RESULT: We utilized WGCNA to identify risk genes and applied NMF to stratify high-risk populations in ccRCC. We characterized the immune gene features of these high-risk groups and ultimately developed a risk prediction model for ccRCC patients using a Lasso regression approach. The risk score was calculated as follows: Risk score = SUM (-0.136394797 ANK3 + 0.004238138 BIVM_ERCC5 - 0.046248451 C4orf19 - 0.036013206 F2RL3 - 0.125531316 GNG7 - 0.012698109 METTL7A + 0.078462369 MSTO1 - 0.050450656 PINK1 - 0.059446590 SLC16A12 - 0.039883686 SLC2A9 + 0.083310722 TLCD1 - 0.059801739 WDR72 + 0.071430088 ZNF117). CONCLUSION: We develop a prognostic model for clear cell renal cell carcinoma and analyzed immune response in subgroups and confirmed protein-level expression concordance.

Decoding PTEN regulation in clear cell renal cell carcinoma: Pathway for biomarker discovery and therapeutic insights.

Renal cell carcinoma is the most common adult renal solid tumor and the deadliest urological cancer, with clear cell renal cell carcinoma (ccRCC) being the predominant subtype. The PI3K/AKT signaling pathway assumes a central role in ccRCC tumorigenesis, wherein its abnormal activation confers a highly aggressive phenotype, leading to swift resistance against current therapies and distant metastasis. Thus, treatment resistance and disease progression remain a persistent clinical challenge in managing ccRCC effectively. PTEN, an antagonist of the PI3K/AKT signaling axis, emerges as a crucial factor in tumor progression, often experiencing loss or inactivation in ccRCC, thereby contributing to elevated mortality rates in patients. Therefore, understanding the molecular mechanisms underlying PTEN suppression in ccRCC tumors holds promise for the discovery of biomarkers and therapeutic targets, ultimately enhancing patient monitoring and treatment outcomes. The present review aims to summarize these mechanisms, emphasizing their potential prognostic, predictive, and therapeutic value in managing ccRCC.

Revealing the characteristics of SETD2-mutated clear cell renal cell carcinoma through tumor heterogeneity analysis.

Background: Renal cell carcinoma (RCC) is the most prevalent type of malignant kidney tumor in adults, with clear cell renal cell carcinoma (ccRCC) comprising about 75% of all cases. The SETD2 gene, which is involved in the modification of histone proteins, is often found to have alterations in ccRCC. Yet, our understanding of how these SETD2 mutations affect ccRCC characteristics and behavior within the tumor microenvironment is still not fully understood. Methods: We conducted a detailed analysis of single-cell RNA sequencing (scRNA-seq) data from ccRCC. First, the data was preprocessed using the Python package, "scanpy." High variability genes were pinpointed through Pearson's correlation coefficient. Dimensionality reduction and clustering identification were performed using Principal Component Analysis (PCA) and the Leiden algorithm. Malignant cell identification was conducted with the "InferCNV" R package, while cell trajectories and intercellular communication were depicted using the Python packages "VIA" and "cellphoneDB." We then employed the R package "Deseq2" to determine differentially expressed genes (DEGs) between groups. Using high-dimensional weighted gene correlation network analysis (hdWGCNA), co-expression modules were identified. We intersected these modules with DEGs to establish prognostic models through univariate Cox and the least absolute shrinkage and selection operator (LASSO) method. Results: We identified 69 and 53 distinctive cell clusters, respectively. These were classified further into 12 unique cell types. This analysis highlighted the presence of an abnormal tumor sub-cluster (MT + group), identified by high mitochondrial-encoded protein gene expression and an indication of unfavorable prognosis. Investigation of cellular interactions spotlighted significant interactions between the MT + group and endothelial cells, macrophaes. In addition, we developed a prognostic model based on six characteristic genes. Notably, risk scores derived from these genes correlated significantly with various clinical features. Finally, a nomogram model was established to facilitate more accurate outcome prediction, incorporating four independent risk factors. Conclusion: Our findings provide insight into the crucial transcriptomic characteristics of ccRCC associated with SETD2 mutation. We discovered that this mutation-induced subcluster could stimulate M2 polarization in macrophages, suggesting a heightened propensity for metastasis. Moreover, our prognostic model demonstrated effectiveness in forecasting overall survival for ccRCC patients, thus presenting a valuable clinical tool.

An unusual occurrence of multiple primary malignant neoplasms: a case report and narrative review.

Introduction: Multiple primary malignant neoplasms (MPMNs) are cancers presenting distinct pathological types that originate from different tissues or organs. They are categorized as either synchronous or metachronous. Nowadays, the incidence of MPMN is increasing. Patients and methods: We present a case of a 71-year-old male patient with a medical history of hepatitis B and a family history of breast and endometrial cancers. The patient reported a nasal tip skin lesion with recurrent bleeding, and the history disclosed lower urinary tract symptoms. Further investigations revealed the coexistence of four primary cancers: basosquamous carcinoma of the nasal lesion, prostatic adenocarcinoma, hepatocellular carcinoma, and clear cell renal cell carcinoma. Results: A multidisciplinary team cooperated to decide the proper diagnostic and therapeutic modules. Conclusion: To the best of our knowledge, the synchronization of these four primary cancers has never been reported in the literature. Even so, multiple primary malignant neoplasms, in general, are no longer a rare entity and need proper explanations, a precise representation of definition and incidence, further work-up approaches, and treatment guidelines as well.

Loss of clear cell characteristics in aggressive clear cell odontogenic carcinoma: a case report.

BACKGROUND: Clear cell odontogenic carcinoma (CCOC) is an odontogenic carcinoma characterized by sheets and islands of vacuolated and clear cells. The diagnosis of atypical CCOC can pose a challenge when tumor cells deviate from their characteristic clear morphology, even with the aid of genetic profiling for CCOC identification. CASE PRESENTATION: In this manuscript, we detailed the inaugural instance of a recurrently recurring clear cell odontogenic carcinoma (CCOC) with pronounced squamous differentiation in a 64-year-old male. The primary tumor in this individual initially displayed a biphasic clear cell phenotype. However, subsequent to the third recurrence, the clear tumor cells were entirely supplanted by epidermoid cells characterized by eosinophilic cytoplasm, vesicular chromatin, and prominent nucleoli. Notable aggressive attributes such as necrosis, conspicuous cytological malignancy, perineural dissemination, and vascular invasion were noted. Additionally, the tumor progressed to manifest lung metastases. The tumor cells exhibited positive immunoreactivity for AE1/AE3, KRT19, Pan-CK, EMA, P40, P63, CK34ßE12, and P53, while they tested negative for CK35ßH11, KRT7, S-100, and neuroendocrine markers. The Ki-67 proliferation index was calculated at an average of 15%. Furthermore, FISH analysis unveiled the presence of the EWSR1::ATF1 gene fusion. CONCLUSIONS: This case illustrated a rare and aggressive case of CCOC characterized by significant squamous differentiation upon recurrence of the tumor.