Mitochondrial Pyruvate Carrier 1 as a Novel Prognostic Biomarker in Non-Small Cell Lung Cancer.

BACKGROUND: Abnormal mitochondrial pyruvate carrier 1 (MPC1) expression plays a key role in tumor metabolic reprogramming and progression. Understanding its significance in non-small cell lung cancer (NSCLC) is crucial for identifying therapeutic targets. METHODS: TIMER 2.0 was utilized to assess the expression of MPC1 in both normal and cancer tissues in pan-cancer. Overall survival (OS) differences between high and low MPC1 expression were analyzed in NSCLC using the Cancer Genome Atlas (TCGA) datasets. We also examined the expression of MPC1 in NSCLC cell lines using western blotting and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). In addition, the tissue samples and clinical information of 80 patients with NSCLC from our hospital were collected. Immunohistochemistry (IHC) was used to assess MPC1 expression, and OS was evaluated using Kaplan-Meier curves and the log-rank test. Univariate and multivariate Cox regression analyses were conducted to evaluate the prognostic values of the clinical characteristics and MPC1expression. RESULTS: Analysis of public databases suggested that MPC1 was downregulated in NSCLC compared to that in normal lung tissue and predicted poor prognosis. In addition, the expression of MPC1 in NSCLC cell lines was lower than that in human bronchial epithelial (HBE) cells at both protein and mRNA levels. Further clinical analysis suggested that MPC1 expression was correlated with age, tumor T stage, and TNM stage. Kaplan-Meier analysis revealed that NSCLC patients with high MPC1 expression had a better prognosis, particularly in lung adenocarcinoma (LUAD), whereas no survival benefit was observed in lung squamous cell carcinoma (LUSC). Univariate and multivariate analyses suggested that MPC1 was an independent prognostic factor for patients with NSCLC. CONCLUSIONS: MPC1 is poorly expressed in NSCLC, particularly in LUAD, which predicts a poor prognosis and may serve as an independent prognostic factor. Further studies on MPC1 may reveal new targets for the treatment of NSCLC.

Paeoniae radix overcomes resistance to EGFR-TKIs via aurora B pathway suppression in lung adenocarcinoma.

Targeted therapies using epidermal growth factor receptor (EGFR) inhibitors have markedly improved survival rates and quality of life for patients with EGFR-mutant lung adenocarcinoma (LUAD). Despite these advancements, resistance to EGFR inhibitors remains a significant challenge, limiting the overall effectiveness of the treatment. This study explored the synergistic effects of combining Paeoniae Radix (PR) with first-generation EGFR-tyrosine kinase inhibitors (TKIs), erlotinib and gefitinib, to overcome this resistance. Transcriptomic analysis of EGFR-mutant LUAD cell lines revealed that PR treatment could potentially reverse the gene signatures associated with resistance to EGFR-TKIs, primarily through the suppression of the Aurora B pathway. Experimental validation demonstrated that combining PR with erlotinib and gefitinib enhanced drug responsiveness by inhibiting Aurora kinase activity and inducing apoptosis in LUAD cells. Additionally, gene expression changes confirmed these combined effects, with the suppression of the Aurora B pathway and upregulation of the apoptotic pathway, which was accompanied by increased expression of multiple pro-apoptotic genes. Our findings contribute to the development of natural product-based therapeutic strategies to mitigate drug resistance in LUAD.

The Value of Topological Radiomics Analysis in Predicting Malignant Risk of Pulmonary Ground-Glass Nodules: A Multi-Center Study.

BACKGROUND: Early detection and accurate differentiation of malignant ground-glass nodules (GGNs) in lung CT scans are crucial for the effective treatment of lung adenocarcinoma. However, existing imaging diagnostic methods often struggle to distinguish between benign and malignant GGNs in the early stages. This study aims to predict the malignancy risk of GGNs observed in lung CT scans by applying two radiomics methods: topological data analysis and texture analysis. METHODS: A retrospective analysis was conducted on 3223 patients from two centers between January 2018 and June2023. The dataset was divided into training, testing, and validation sets to ensure robust model development and validation. We developed topological features applied to GGNs using radiomics analysis based on homology. This innovative approach emphasizes the integration of topological information, capturing complex geometric and spatial relationships within GGNs. By combining machine learning and deep learning algorithms, we established a predictive model that integrates clinical parameters, previous radiomics features, and topological radiomics features. RESULTS: Incorporating topological radiomics into our model significantly enhanced the ability to distinguish between benign and malignant GGNs. The topological radiomics model achieved areas under the curve (AUC) of 0.85 and 0.862 in two independent validation sets, outperforming previous radiomics models. Furthermore, this model demonstrated higher sensitivity compared to models based solely on clinical parameters, with sensitivities of 80.7% in validation set 1 and 82.3% in validation set 2. The most comprehensive model, which combined clinical parameters, previous radiomics features, and topological radiomics features, achieved the highest AUC value of 0.879 across all datasets. CONCLUSION: This study validates the potential of topological radiomics in improving the predictive performance for distinguishing between benign and malignant GGNs. By integrating topological features with previous radiomics and clinical parameters, our comprehensive model provides a more accurate and reliable basis for developing treatment strategies for patients with GGNs.

RNA-seq and bulk RNA-seq data analysis of cancer-related fibroblasts (CAF) in LUAD to construct a CAF-based risk signature.

Angiogenesis, metastasis, and resistance to therapy are all facilitated by cancer-associated fibroblasts (CAFs). A CAF-based risk signature can be used to predict patients' prognoses for Lung adenocarcinoma (LUAD) based on CAF characteristics. The Gene Expression Omnibus (GEO) database was used to gather signal-cell RNA sequencing (scRNA-seq) data for this investigation. The GEO and TCGA databases were used to gather bulk RNA-seq and microarray data for LUAD. The scRNA-seq data were analyzed using the Seurat R program based on the CAF markers. Our goal was to use differential expression analysis to discover differentially expressed genes (DEGs) across normal and tumor samples in the TCGA dataset. Pearson correlation analysis was utilized to discover prognostic genes related with CAF, followed by univariate Cox regression analysis. Using Lasso regression, a risk signature based on CAF-related prognostic genes was created. A nomogram model was created based on the clinical and pathological aspects. 5 CAF clusters were identified in LUAD, 4 of which were associated with prognosis. From 2811 DEGs, 1002 genes were found to be significantly correlated with CAF clusters, which led to the creation of a risk signature with 8 genes. These 8 genes were primarily connected with 41 pathways, such as antigen paocessing and presentation, apoptosis, and cell cycle. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for LUAD, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of LUAD. CAF-based risk signatures can be effective in predicting the prognosis of LUAD, and they may provide new strategies for cancer treatments by interpreting the response of LUAD to immunotherapy.

Deep learning-based characterization of pathological subtypes in lung invasive adenocarcinoma utilizing 18F-deoxyglucose positron emission tomography imaging.

OBJECTIVE: To evaluate the diagnostic efficacy of a deep learning (DL) model based on PET/CT images for distinguishing and predicting various pathological subtypes of invasive lung adenocarcinoma. METHODS: A total of 250 patients diagnosed with invasive lung cancer were included in this retrospective study. The pathological subtypes of the cancer were recorded. PET/CT images were analyzed, including measurements and recordings of the short and long diameters on the maximum cross-sectional plane of the CT image, the density of the lesion, and the associated imaging signs. The SUVmax, SUVmean, and the lesion's long and short diameters on the PET image were also measured. A manual diagnostic model was constructed to analyze its diagnostic performance across different pathological subtypes. The acquired images were first denoised, followed by data augmentation to expand the dataset. The U-Net network architecture was then employed for feature extraction and network segmentation. The classification network was based on the ResNet residual network to address the issue of gradient vanishing in deep networks. Batch normalization was applied to ensure the feature matrix followed a distribution with a mean of 0 and a variance of 1. The images were divided into training, validation, and test sets in a ratio of 6:2:2 to train the model. The deep learning model was then constructed to analyze its diagnostic performance across different pathological subtypes. RESULTS: Statistically significant differences (P < 0.05) were observed among the four different subtypes in PET/CT imaging performance. The AUC and diagnostic accuracy of the manual diagnostic model for different pathological subtypes were as follows: APA: 0.647, 0.664; SPA: 0.737, 0.772; PPA: 0.698, 0.780; LPA: 0.849, 0.904. Chi-square tests indicated significant statistical differences among these subtypes (P < 0.05). The AUC and diagnostic accuracy of the deep learning model for the different pathological subtypes were as follows: APA: 0.854, 0.864; SPA: 0.930, 0.936; PPA: 0.878, 0.888; LPA: 0.900, 0.920. Chi-square tests also indicated significant statistical differences among these subtypes (P < 0.05). The Delong test showed that the diagnostic performance of the deep learning model was superior to that of the manual diagnostic model (P < 0.05). CONCLUSIONS: The deep learning model based on PET/CT images exhibits high diagnostic efficacy in distinguishing and diagnosing various pathological subtypes of invasive lung adenocarcinoma, demonstrating the significant potential of deep learning techniques in accurately identifying and predicting disease subgroups.

LINC01116-dependent upregulation of RNA polymerase I transcription drives oncogenic phenotypes in lung adenocarcinoma.

BACKGROUND: Hyperactive RNA Polymerase I (Pol I) transcription is canonical in cancer, associated with malignant proliferation, poor prognosis, epithelial-mesenchymal transition, and chemotherapy resistance. Despite its significance, the molecular mechanisms underlying Pol I hyperactivity remain unclear. This study aims to elucidate the role of long noncoding RNAs (lncRNAs) in regulating Pol I transcription in lung adenocarcinoma (LUAD). METHODS: Bioinformatics analyses were applied to identify lncRNAs interacting with Pol I transcriptional machinery. Fluorescence in situ hybridization was employed to examine the nucleolar localization of candidate lncRNA in LUAD cells. RNA immunoprecipitation assay validated the interaction between candidate lncRNA and Pol I components. Chromatin isolation by RNA purification and Chromatin Immunoprecipitation (ChIP) were utilized to confirm the interactions of candidate lncRNA with Pol I transcriptional machinery and the rDNA core promoter. Functional analyses, including lncRNA knock-in and knockdown, inhibition of Pol I transcription, quantitative PCR, cell proliferation, clonogenicity, apoptosis, cell cycle, wound-healing, and invasion assays, were performed to determine the effect of candidate lncRNA on Pol I transcription and associated malignant phenotypes in LUAD cells. ChIP assays and luminometry were used to investigate the transcriptional regulation of the candidate lncRNA. RESULTS: We demonstrate that oncogenic LINC01116 scaffolds essential Pol I transcription factors TAF1A and TAF1D, to the ribosomal DNA promoter, and upregulate Pol I transcription. Crucially, LINC01116-driven Pol I transcription activation is essential for its oncogenic activities. Inhibition of Pol I transcription abrogated LINC01116-induced oncogenic phenotypes, including increased proliferation, cell cycle progression, clonogenicity, reduced apoptosis, increased migration and invasion, and drug sensitivity. Conversely, LINC01116 knockdown reversed these effects. Additionally, we show that LINC01116 upregulation in LUAD is driven by the oncogene c-Myc, a known Pol I transcription activator, indicating a functional regulatory feedback loop within the c-Myc-LINC01116-Pol I transcription axis. CONCLUSION: Collectively, our findings reveal, for the first time, that LINC01116 enhances Pol I transcription by scaffolding essential transcription factors to the ribosomal DNA promoter, thereby driving oncogenic activities in LUAD. We propose the c-Myc-LINC01116-Pol I axis as a critical oncogenic pathway and a potential therapeutic target for modulating Pol I transcription in LUAD.

Solitary Giant Primary Gastric Plasmacytoma Mimicking Gastric Adenocarcinoma In Situ.

A solitary extraosseous plasmacytoma is a rare type of plasma cell neoplasm. Its occurrence in the stomach is particularly unusual and can easily be mistaken for more common types of tumors. We describe a case involving a solitary extraosseous plasmacytoma in a patient who experienced weight loss as the sole symptom. Initially, the condition was misdiagnosed as gastric adenocarcinoma based on endoscopic biopsy results, leading to a gastrectomy after neoadjuvant chemotherapy. Subsequent examination of the pathological specimen revealed the presence of plasma cell neoplasia alongside a gastric adenocarcinoma in situ.

The Importance of Abdominal Pain in the Elderly: An Unlikely Diagnosis of 17 cm Colo-Colonic Intussusception.

We report an interesting case of a 17 cm colo-colonic intussusception involving the transverse colon, caecum, and distal small bowel in a previously healthy 79-year-old man. The patient presented to the emergency department with a two-day history of mild, left to right iliac fossa abdominal pain, with no other concerning symptoms. He had a CT of the abdomen and pelvis with contrast for suspected subacute bowel obstruction secondary to recurrent bowel cancer. This was reported as colo-colonic intussusception. Following a surgical review, he was transferred from the local district general hospital for an exploratory laparotomy and underwent a right hemicolectomy with primary ileocolonic anastomosis the same evening. The patient was discharged seven days later following an unremarkable post-operative recovery. Final histology confirmed a mucinous adenocarcinoma of the caecum with postoperative cancer staging as T2N0M0. Following discussion at the colorectal multidisciplinary meeting, no adjuvant therapy was advised, and he was placed on the standard colorectal cancer surveillance program for the next five years.

Prognostic Significance of Tumor and Inflammatory Markers in Disease-Free and Overall Survival Duration in Colonic Adenocarcinoma Patients.

Introduction Colorectal carcinoma (CRC) continues to be a major global health concern, contributing substantially to cancer incidence and mortality. Colonic adenocarcinoma, a common subtype of CRC, is influenced by various prognostic factors, including tumor stage, histopathological characteristics, and tumor markers. Despite their routine use in clinical settings, the prognostic value of traditional tumor markers, such as carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA 19-9), and others, is still under debate. In this study, we aim to analyze the tumor markers' prognostic significance in our CRC patients in terms of disease-free survival and overall survival. Methods A retrospective study was conducted on 71 patients who underwent surgery for colonic adenocarcinoma between January 1, 2018, and January 1, 2024. Data on patient demographics, recurrence rates, survival times, and tumor marker levels (CEA, CA 19-9, CA 125, AFP, and CRP to albumin ratio (CAR)), disease-free survival duration (DFS), and overall survival durations (OS) were collected and analyzed. Statistical analyses included Pearson and Spearman correlation coefficients, the Mann-Whitney U test, ROC curve analysis, and Kaplan-Meier survival analysis. Results The study found that elevated CAR and CA 125 levels were significantly associated with higher mortality and recurrence rates, whereas elevated CEA levels were strongly predictive of recurrence. Receiver operating characteristic (ROC) analysis identified optimal cutoff values for these markers, with CEA ≥ 47.145, CA 125 ≥ 15.85, and CAR ≥ 6.796 demonstrating high specificity and predictive value for recurrence. Kaplan-Meier analysis revealed that patients with CEA < 47.145 had a significantly longer DFS (67.7 months) compared to those with CEA ≥ 47.145 (24 months, p < 0.001). Similarly, patients with CA 125 < 15.85 and CAR < 6.796 showed longer DFS compared to those with higher values. Overall survival analysis also highlighted that patients with CA 125 < 21.71 and CAR < 4.09 had better survival outcomes, with significant differences of 26 and 10 months, respectively (p < 0.001 and p = 0.001). Conclusion Tumor markers, such as CEA, CA 125, and CAR, hold significant prognostic value in colonic adenocarcinoma, with higher levels correlating with poorer outcomes. These findings underscore the importance of integrating tumor markers into clinical decision-making to optimize treatment strategies and improve patient survival. Future research should focus on standardizing the use of these markers and exploring novel biomarkers for enhanced prognostication.

Pembrolizumab in Combination with Folfirinox for Treatment of Advanced Pancreatic Adenocarcinoma With MSI-H.

Pancreatic cancer is one of the four most common causes of cancer-related death in the United States. Our patient had metastatic pancreatic cancer with a high tumour burden. He was trialled on an unconventional treatment of combination immunotherapy and chemotherapy. It resulted in decreased cancer burden and decreased FDG activity on a PET scan. Further studies are needed for standard pancreatic cancer treatment. LEARNING POINTS: Very few patients survive pancreatic cancer, especially metastatic disease. Our patient is doing very well after a few years.There is little evidence for concurrent use of chemotherapy and immunotherapy. Our patient received it and has had no new lesions, and there has been an improvement on imaging.

Revealing the Unanticipated: An Uncommon Case of Colorectal Adenocarcinoma Transitioning to Choriocarcinoma - A Case Report and Literature Review.

Choriocarcinomas are uncommon tumors, with non-gestational types occurring in both males and females. Primary choriocarcinoma of the colon is extremely rare. It presents significant diagnostic and therapeutic challenges due to its aggressive nature and poor prognosis, with no cure available, and a mean survival of 8 months. This case report describes a 48-year-old woman who presented with abdominal pain and an ovarian mass, initially suspected to be ovarian cancer. Further workup showed a primary tumor in the colon, with extension to the ovary and liver metastasis. The pathology findings confirmed the presence of colorectal adenocarcinoma with choriocarcinomatous differentiation, as indicated by immunohistochemistry. The patient initially responded to the cisplatin/etoposide regimen; however, she relapsed shortly after. The patient received additional treatments with pembrolizumab, paclitaxel, and olaparib, which resulted in partial remission. Despite challenges during treatment, such as suspected uveitis related to immune-checkpoint inhibitors and potential interference of antibodies with beta-human chorionic gonadotropin (ß-hCG) testing, the patient maintained a good performance status for over 1.5 years after being diagnosed. The case emphasizes the difficulties in treating choriocarcinomas, primarily because of their aggressiveness and the absence of standardized therapy. Our goal with this case is to draw multidisciplinary attention to this rare condition. Further studies are necessary to comprehend its clinical characteristics, prognosis factors, molecular markers, and treatment approaches. Such studies may be crucial in establishing targeted and personalized therapy. LEARNING POINTS: Primary choriocarcinoma of the colon is rare and often misdiagnosed due to its atypical presentation, complicating timely and accurate diagnosis.The aggressive nature of this tumor and lack of standardized therapy necessitates a multidisciplinary approach and personalized treatment plans, especially following relapse.Molecular profiling guided the use of immunotherapy, which showed potential but also presented challenges, highlighting the need for further research in treating this rare malignancy.

Case report: Intrapleural plus systemic Tislelizumab injection combined chemotherapy in RET gene fusion-positive lung adenocarcinoma presenting refractory malignant pleural effusion.

RET fusions were discovered in non-small cell lung cancer (NSCLC), and the efficacy of RET-targeted treatment in these patients has been previously established. However, patients with required resistance to RET-TKIs have limited treatment options. Herein, we describe a case of critical and advanced lung adenocarcinoma harboring RET fusion. Despite a significant response to Prasetinib previously, the patient developed refractory malignant pleural effusion after 24 months of treatment. He was treated simultaneously with intrapleural plus systemic Tislelizumab injection combined chemotherapy, thereby achieving an excellent clinical benefit maintaining control of pleural effusion for over 6 months. Hence, we would like to discuss intrapleural immunotherapy as an additional treatment method in refractory malignant pleural effusion while demonstrating good treatment tolerance.

Pityriasis Rubra Pilaris and underlying malignancy.

A 59-year-old man presented with a five-month history of widespread, salmon-colored, scaly plaques. Skin examination revealed salmon-colored plaques with "islands of sparing" on the trunk and waxy keratoderma on the palms and soles. Histopathology of the lesion showed alternating orthokeratosis and parakeratosis in vertical and horizontal directions, consistent with a diagnosis of pityriasis rubra pilaris (PRP). The patient was unresponsive to methotrexate and Secukinumab. Further evaluation through a computerized tomography scan revealed a presence of air-filled multicystic changes in the upper left lung, accompanied by diffuse pulmonary bullae. Elevated serum tumor markers, including CEA, NSE, and SCC, indicated an underlying acinar-predominant adenocarcinoma, suggesting a paraneoplastic PRP. He was subsequently referred to the oncology department for further management. This report underscores the importance of identifying an underlying malignancy in recalcitrant PRP cases.

An unusual pAIR: Anti-PKM2 antibody and occult pancreatic adenocarcinoma.

Purpose: To describe the clinical, laboratory and multimodal imaging findings in paraneoplastic autoimmune retinopathy (p-AIR) associated with anti-pyruvate kinase M2 antibody (anti-PKM2) and occult pancreatic adenocarcinoma. Observations: A 70 year old male with blurred vision, nyctalopia and concurrent difficulty with glucose control had retinal vascular attenuation and diffuse punctate pigment clumping in both eyes. Multimodal imaging demonstrated corresponding stippled hypofluorescence on fluorescein angiography, stippled hyperautofluorescence and a hyperautoflourescent macular ring with fundus autofluorescence, and focal hyperreflectivity at the level of the RPE-Bruch's membrane complex with diffuse loss of outer retinal layers on ocular coherence tomography. In addition, diffuse ganglion cell loss and severe visual field constriction were present. Genetic testing for retinitis pigmentosa was normal. Screening for anti-retinal antibodies was positive for only anti-PKM2. Systemic evaluation revealed previously undiagnosed adenocarcinoma of the pancreas. Conclusions and importance: Anti-PKM2 in the setting of autoimmune retinopathy may be associated with occult pancreatic cancer. The diagnosis of pAIR should be considered and systemic investigation for occult malignancy initiated even in the absence of more commonly associated anti-retinal antibodies.

Machine learning based intratumor heterogeneity signature for predicting prognosis and immunotherapy benefit in stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a prevalent malignancy that is highly aggressive and heterogeneous. Intratumor heterogeneity (ITH) showed strong link to tumor progression and metastasis. High ITH may promote tumor evolution. An ITH-related signature (IRS) was created using as integrative technique including 10 machine learning methods based on TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets. The relevance of IRS in predicting the advantages of immunotherapy was assessed using a number of prediction scores and three immunotherapy datasets (GSE78220, IMvigor210 and GSE91061). Vitro experiments were performed to verify the biological functions of AKR1B1. The RSF + Enet (alpha = 0.1) projected model was proposed as the ideal IRS because it had the highest average C-index. The IRS demonstrated a strong performance in serving as an independent risk factor for the clinical outcome of STAD patients. It performed exceptionally well in predicting the overall survival rate of STAD patients, as seen by the TCGA cohort's AUC of 1-, 3-, and 5-year ROC curves, which were 0.689, 0.683, and 0.669, respectively. A low IRS score demonstrated a superior response to immunotherapy, as seen by a lower TIDE score, lower immune escape score, greater TMB score, higher PD1&CTLA4 immunophenoscore, higher response rate, and improved prognosis. Common chemotherapeutic and targeted treatment regimens had lower IC50 values in the group with higher IRS scores. Vitro experiment showed that AKR1B1 was upregulated in STAD and knockdown of AKR1B1 obviously suppressed tumor cell proliferation and migration. The present investigation produced the best IRS for STAD, which may be applied to prognostication, risk stratification, and therapy planning for STAD patients.

In-silico identification of therapeutic targets in pancreatic ductal adenocarcinoma using WGCNA and Trader.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy, accounting for over 90% of pancreatic cancers, and is characterized by limited treatment options and poor survival rates. Systems biology provides in-depth insights into the molecular mechanisms of PDAC. In this context, novel algorithms and comprehensive strategies are essential for advancing the identification of critical network nodes and therapeutic targets within disease-related protein-protein interaction networks. This study employed a comprehensive computational strategy using the metaheuristic algorithm Trader to enhance the identification of potential therapeutic targets. Analysis of the expression data from the PDAC dataset (GSE132956) involved co-expression analysis and clustering of differentially expressed genes to identify key disease-associated modules. The STRING database was used to construct a network of differentially expressed genes, and the Trader algorithm pinpointed the top 30 DEGs whose removal caused the most significant network disconnections. Enriched gene ontology terms included "Signaling by Rho GTPases," "Signaling by receptor tyrosine kinases," and "immune system." Additionally, nine hub genes-FYN, MAPK3, CDK2, SNRPG, GNAQ, PAK1, LPCAT4, MAP1LC3B, and FBN1-were identified as central to PDAC pathogenesis. This integrated approach, combining co-expression analysis with protein-protein interaction network analysis using a metaheuristic algorithm, provides valuable insights into PDAC mechanisms and highlights several hub genes as potential therapeutic targets.

Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma.

BACKGROUND: Lung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established. METHODS: TCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses. RESULTS: In LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC = 0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle. CONCLUSION: Elevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD.

Celiac Disease Masking Duodenal Adenocarcinoma: A Case Report and Literature Review.

Small bowel adenocarcinoma (SBA) is an uncommon gastrointestinal malignancy, with the duodenum being the most commonly affected site. This report describes a 33-year-old woman who initially presented with abdominal pain and vomiting. Initial imaging revealed abnormalities of the proximal jejunum. Endoscopic evaluation initially revealed celiac disease (CD); however, with disease progression, the patient developed bowel obstruction that led to surgical intervention with an open duodenal biopsy. The open duodenal biopsy confirmed the presence of duodenal adenocarcinoma (DA). This case demonstrates the diagnostic complexity of DA in the presence of concurrent CD due to overlapping presentations. Physicians must maintain a high suspicion of DA in the setting of progressive and difficult-to-treat CD, as early diagnosis and management of DA can significantly improve patient outcomes.

Association of Membranous Basal Cell Adenoma and Basal Cell Adenocarcinoma With Brooke-Spiegler Syndrome.

Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) are uncommon basaloid biphasic salivary gland tumors composed of basal and ductal cells. BCAC is differentiated from BCA by the presence of invasion in BCAC. In this paper, an 82-year-old woman presented with a palpable 3 cm immobile mass in her right parotid gland. A computed tomography (CT) scan showed two separate right parotid masses. She underwent a right parotidectomy, and the pathology showed multiple membranous BCAs and BCAC, which were highly suspicious for Brooke-Spiegler syndrome (BSS). This paper discusses BCA, BCAC, and their relationship with BSS.

Computed tomography radiomics models of tumor differentiation in canine small intestinal tumors.

Radiomics models have been widely exploited in oncology for the investigation of tumor classification, as well as for predicting tumor response to treatment and genomic sequence; however, their performance in veterinary gastrointestinal tumors remains unexplored. Here, we sought to investigate and compare the performance of radiomics models in various settings for differentiating among canine small intestinal adenocarcinoma, lymphoma, and spindle cell sarcoma. Forty-two small intestinal tumors were contoured using four different segmentation methods: pre- or post-contrast, each with or without the inclusion of intraluminal gas. The mesenteric lymph nodes of pre- and post-contrast images were also contoured. The bin settings included bin count and bin width of 16, 32, 64, 128, and 256. Multinomial logistic regression, random forest, and support vector machine models were used to construct radiomics models. Using features from both primary tumors and lymph nodes showed significantly better performance than modeling using only the radiomics features of primary tumors, which indicated that the inclusion of mesenteric lymph nodes aids model performance. The support vector machine model exhibited significantly superior performance compared with the multinomial logistic regression and random forest models. Combining radiologic findings with radiomics features improved performance compared to using only radiomics features, highlighting the importance of radiologic findings in model building. A support vector machine model consisting of radiologic findings, primary tumors, and lymph node radiomics features with bin count 16 in post-contrast images with the exclusion of intraluminal gas showed the best performance among the various models tested. In conclusion, this study suggests that mesenteric lymph node segmentation and radiological findings should be integrated to build a potent radiomics model capable of differentiating among small intestinal tumors.