Cancer is widely regarded as a leading cause of death in humans, with colon adenocarcinoma (COAD) ranking among the most prevalent types. Cuproptosis is a novel form of cell death mediated by protein lipoylation. Cuproptosis-related genes (CRGs) participate in tumourigenesis and development. Their role in pan-cancer and COAD require further investigation. This study comprehensively evaluated the relationship among CRGs, pan-cancer, and COAD. Our research revealed the differential expression of CRGs and the cuproptosis potential index (CPI) between normal and tumour tissues, and further explored the correlation of CRGs or CPI with prognosis, immune infiltration, tumor mutant burden(TMB), microsatellite instability (MSI), and drug sensitivity in pan-cancer. Gene set enrichment analysis (GSEA) revealed that oxidative phosphorylation and fatty acid metabolism pathways were significantly enriched in the high CPI group of most tumours. FDX1 and CDKN2A were chosen for further exploration, and we found an independent association between FDX1 and CDKN2A and prognosis, immune infiltration, TMB, and MSI in pan-cancer. Furthermore, a prognostic risk model based on the association between CRGs and COAD was built, and the correlations between the risk score and prognosis, immune-related characteristics, and drug sensitivity were analysed. COAD was then divided into three subtypes using cluster analysis, and the differences among the subtypes in prognosis, CPI, immune-related characteristics, and drug sensitivity were determined. Due to the level of LIPT1 was notably positive related with the risk score, the cytological identification was carried out to identify the association of LIPT1 with proliferation and migration of colon cancer cells. In summary, CRGs can be used as potential prognostic biomarkers to predict immune infiltration levels in patients with pan-cancer. In addition, the risk model could more accurately predict the prognosis and immune infiltration levels of COAD and better guide the direction of clinical medication. Thus, FDX1, CDKN2A, and LIPT1 may serve as prospective new targets for cancer therapy.

OBJECTIVE: To observe the therapeutic effects and underlying mechanism of baicalin against colon cancer.
METHODS: The effects of baicalin on the proliferation and growth of colon cancer cells MC38 and CT26. WT were observed and predicted potential molecular targets of baicalin for colon cancer therapy were studied by network pharmacology. Furthermore, molecular docking and drug affinity responsive target stability (DARTS) analysis were performed to confirm the interaction between potential targets and baicalin. Finally, the mechanisms predicted by in silico analyses were experimentally verified in-vitro and in-vivo.
RESULTS: Baicalin significantly inhibited proliferation, invasion, migration, and induced apoptosis in MC38 and CT26 cells (all P<0.01). Additionally, baicalin caused cell cycle arrest at the S phase, while the G0/G1 phase was detected in the tiny portion of the cells. Subsequent network pharmacology analysis identified 6 therapeutic targets associated with baicalin, which potentially affect various pathways including 39 biological processes and 99 signaling pathways. In addition, molecular docking and DARTS predicted the potential binding of baicalin with cyclin dependent kinase inhibitor 2A (CDKN2A), protein kinase B (AKT), caspase 3, and mitogen-activated protein kinase (MAPK). In vitro, the expressions of CDKN2A, MAPK, and p-AKT were suppressed by baicalin in MC38 and CT26 cells. In vivo, baicalin significantly reduced the tumor size and weight (all P<0.01) in the colon cancer mouse model via inactivating p-AKT, CDKN2A, cyclin dependent kinase 4, cyclin dependent kinase 2, interleukin-1, tumor necrosis factor α, and activating caspase 3 and mouse double minute 2 homolog signaling (all P<0.05).
CONCLUSIONS: Baicalin suppressed the CDKN2A protein level to prevent colon cancer and could be used as a therapeutic target for colon cancer.

Cuproptosis is a type of cell death characterized by excessive copper-lipid reactions in the tricarboxylic acid cycle, resulting in protein toxicity stress and cell death. Although known as a cuproptosis inhibitor through CRISPR-Cas9 screening, the role of cyclin-dependent kinase inhibitor 2A (CDKN2A) in cuproptosis resistance and its connection to tumor development remains unclear.
In this study, we combined single-cell sequencing, spatial transcriptomics, pathological image analysis, TCGA multi-omics analysis and in vitro experimental validation to comprehensively investigate CDKN2A distribution, expression, epigenetic modification, regulation and genomic features in colorectal cancer cells. We further explored the associations between CDKN2A and cellular pathway, immune infiltration and spatial signal communication.
Our findings showed an increasing trend in cuproptosis in the trajectory of tumor progression, accompanied by an upward trend of CDKN2A. CDKN2A underwent transcriptional activation by MEF2D and via the SNHG7/miR-133b axis, upregulating glycolysis, copper metabolism and copper ion efflux. CDKN2A likely drives epithelial-mesenchymal transition (EMT) and progression by activating Wnt signaling. CDKN2A is associated with high genomic instability and sensitivity to radiation and chemotherapy. Tumor regions expressing CDKN2A exhibit distinctive SPP1+ tumor-associated macrophage (TAM) infiltration and MMP7 enrichment, along with unique signaling crosstalk with adjacent areas.
CDKN2A mediates cuproptosis resistance through regulating glycolysis and copper homeostasis, accompanied by a malignant phenotype and pro-tumor niche. Radiation and chemotherapy are expected to potentially serve as therapeutic approaches for cuproptosis-resistant colorectal cancer with high CDKN2A expression.

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UNASSIGNED: A 55-year-old male patient developed a mass in the left inguinal area with left lower limb swelling and first visited a local hospital 3 months earlier because of unrelieved pain. An MRI scan suggested left suprapubic branch and left acetabular bone destruction, abnormal soft tissue signals within the iliopsoas muscle of the anterior edge of the left iliac bone, and enlarged lymph nodes in the left iliac fossa and left inguinal region. The patient subsequently underwent left pelvic lesion open biopsy and inguinal lymph node resection biopsy. According to pathological reports, the left inguinal mass was considered to be a malignant tumor of cutaneous accessory origin (pilomatrix carcinoma) with extensive vitreous changes. The suprapupubis branch mass was considered to be a bone metastatic pilomatrix carcinoma. Immunohistochemistry (IHC) revealed a PDL1 combined positive score (CPS) of 8. DNA next-generation sequencing (NGS) showed CDKN2A L65Rfs*53 mutation. The patient received three cycles of gemcitabine and nedaplatin. However, the lesion progressed.
UNASSIGNED: Chemotherapy is not effective for treating pilomatrix carcinoma. PDL1 antibodies and CDK4/6 inhibitors might be treatment options for pilomatrix carcinoma.

BACKGROUND: Although CDKN2A alteration has been explored as a favorable factor for tumorigenesis in pan-cancers, the association between CDKN2A point mutation (MUT) and intragenic deletion (DEL) and response to immune checkpoint inhibitors (ICIs) is still disputed. This study aims to determine the associations of CDKN2A MUT and DEL with overall survival (OS) and response to immune checkpoint inhibitors treatment (ICIs) among pan-cancers and the clinical features of CDKN2A-altered gastric cancer.
METHODS: This study included 45,000 tumor patients that underwent tumor sequencing across 33 cancer types from four cohorts, the MSK-MetTropism, MSK-IMPACT, OrigiMed2020 and TCGA cohorts. Clinical outcomes and genomic factors associated with response to ICIs, including tumor mutational burden, copy number alteration, neoantigen load, microsatellite instability, tumor immune microenvironment and immune-related gene signatures, were collected in pan-cancer. Clinicopathologic features and outcomes were assessed in gastric cancer. Patients were grouped based on the presence of CDKN2A wild type (WT), CDKN2A MUT, CDKN2A DEL and CDKN2A other alteration (ALT).
RESULTS: Our research showed that CDKN2A-MUT patients had shorter survival times than CDKN2A-WT patients in the MSK MetTropism and TCGA cohorts, but longer OS in the MSK-IMPACT cohort with ICIs treatment, particularly in patients having metastatic disease. Similar results were observed among pan-cancer patients with CDKN2A DEL and other ALT. Notably, CDKN2A ALT frequency was positively related to tumor-specific objective response rates to ICIs in MSK MetTropism and OrigiMed 2020. Additionally, individuals with esophageal carcinoma or stomach adenocarcinoma who had CDKN2A MUT had poorer OS than patients from the MSK-IMPACT group, but not those with adenocarcinoma. We also found reduced levels of activated NK cells, T cells CD8 and M2 macrophages in tumor tissue from CDKN2A-MUT or DEL pan-cancer patients compared to CDKN2A-WT patients in TCGA cohort. Gastric cancer scRNA-seq data also showed that CDKN2A-ALT cancer contained less CD8 T cells but more exhausted T cells than CDKN2A-WT cancer. A crucial finding of the pathway analysis was the inhibition of three immune-related pathways in the CDKN2A ALT gastric cancer patients, including the interferon alpha response, inflammatory response, and interferon gamma response.
CONCLUSIONS: This study illustrates the CDKN2A MUT and DEL were associated with a poor outcome across cancers. CDKN2A ALT, on the other hand, have the potential to be used as a biomarker for choosing patients for ICI treatment, notably in esophageal carcinoma and stomach adenocarcinoma.

BACKGROUND: To assess the genetic characteristics of central nervous system (CNS) metastases from non-small-cell lung cancer (NSCLC), we gathered the genetic profiles of brain metastases (BM) and leptomeningeal metastases (LM). Our objective was to identify genetic factors contributing to poorer overall survival (OS) in NSCLC patients with LM.
METHODS: This study included 25 consecutive patients with BM and 52 patients with LM from Guangdong Sanjiu Brain Hospital. All participants underwent 168-target panel sequencing.
RESULTS: Among the 25 patients with BM, TP53 was the most frequently mutated gene (44%), followed by driver genes such as EGFR and BRAF (40% and 20%, respectively). In patients with BM, EGFR_amp and CDK4 were also frequently mutated, with rates of 20% and 16%, respectively. The genetic landscape of patients with LM differed, with the top mutated genes being EGFR, TP53, EGFR_amp, CDKN2A, CCNE1, CDK4, PMS2, and PIK3CA, with mutation rates of 77%, 69%, 31%, 29%, 13%, 13%, 13%, and 12%, respectively. In our study, patients with LM exhibited significantly worse OS compared to those with BM (p = 0.029). The mutation rates of TP53, EGFR_amp, and CDKN2A varied between patients with LM and those with BM, at 69.23% vs. 44%, 30.77% vs. 20%, and 28.85% vs. 12%, respectively. Further exploration revealed that patients with BM with TP53 mutations had a shorter OS than patients without TP53 mutations (p = 0.014). Similarly, patients with LM and TP53 mutations presented with worse OS than those without TP53 mutations (p = 0.0067). LM patients with CDKN2A deletions had worse OS than those without CDKN2A deletions (p = 0.037). Additionally, patients with EGFR_amp had a shorter OS than those without EGFR_amp (p = 0.044).
CONCLUSIONS: Patients with LM exhibited significantly worse OS than those with BM. Gene signatures, such as TP53, EGFR_amp, and CDKN2A, may account for shorter outcomes in patients with LM.

This study aims to enhance the prognosis prediction of Head and Neck Squamous Cell Carcinoma (HNSCC) by employing artificial intelligence (AI) to analyse CDKN2A gene expression from pathology images, directly correlating with patient outcomes. Our approach introduces a novel AI-driven pathomics framework, delineating a more precise relationship between CDKN2A expression and survival rates compared to previous studies. Utilizing 475 HNSCC cases from the TCGA database, we stratified patients into high-risk and low-risk groups based on CDKN2A expression thresholds. Through pathomics analysis of 271 cases with available slides, we extracted 465 distinctive features to construct a Gradient Boosting Machine (GBM) model. This model was then employed to compute Pathomics scores (PS), predicting CDKN2A expression levels with validation for accuracy and pathway association analysis. Our study demonstrates a significant correlation between higher CDKN2A expression and improved median overall survival (66.73 months for high expression vs. 42.97 months for low expression, p = 0.013), establishing CDKN2A\'s prognostic value. The pathomic model exhibited exceptional predictive accuracy (training AUC: 0.806; validation AUC: 0.710) and identified a strong link between higher Pathomics scores and cell cycle activation pathways. Validation through tissue microarray corroborated the predictive capacity of our model. Confirming CDKN2A as a crucial prognostic marker in HNSCC, this study advances the existing literature by implementing an AI-driven pathomics analysis for gene expression evaluation. This innovative methodology offers a cost-efficient and non-invasive alternative to traditional diagnostic procedures, potentially revolutionizing personalized medicine in oncology.

The intensification of the aging population is often accompanied by an increase in agerelated diseases, which impair the quality of life of the elderly. The characteristic feature of aging is progressive physiological decline, which is the largest cause of human pathology and death worldwide. However, natural aging interacts in exceptionally complex ways within and between organs, but its underlying mechanisms are still poorly understood. Long non-coding RNA (lncRNA) is a type of noncoding RNA that exceeds 200 nucleotides in length and does not possess protein-coding ability. It plays a crucial role in the occurrence and development of diseases. ANRIL, also known as CDKN2B-AS1, is an antisense ncRNA located at the INK4 site. It can play a crucial role in agerelated disease progression by regulating single nucleotide polymorphism, histone modifications, or post-transcriptional modifications (such as RNA stability and microRNA), such as cardiovascular disease, diabetes, tumor, arthritis, and osteoporosis. Therefore, a deeper understanding of the molecular mechanisms of lncRNA ANRIL in age-related diseases will help provide new diagnostic and therapeutic targets for clinical practice.

Thyroid cancer (THCA) is the most prevalent endocrine tumor, and its incidence continues to increase every year. However, the processes underlying the aggressive progression of thyroid cancer are unknown. We concentrated on the prognostic and biological importance of thyroid cancer cuproptosis-related genes in this investigation. Genomic and clinical data were obtained from the UCSC XENA website, and cuproptosis-related genes were obtained from the FerrDb website. We performed differential expression analysis and Cox regression analysis to identify possible predictive targets associated with thyroid cancer prognosis. To assess the role of CDKN2A in thyroid cancer and the ability to predict prognosis on the basis of the CDKN2A expression level, we performed immunohistochemical staining, survival analysis, immunological analysis, functional analysis, and clinical analysis with respect to CDKN2A gene expression. CDKN2A expression levels were found to be inversely correlated with thyroid cancer prognosis. Higher levels of CDKN2A expression were associated with higher T, N, and clinicopathological stage and more residual tumor cells. Through univariate and multivariate Cox regression analyses, the CDKN2A expression level was shown to be linked with thyroid cancer patients\' overall survival (OS). Moreover, we discovered that CDKN2A expression was linked to a dysfunctional tumor immune microenvironment. The study shows that CDKN2A, a cuproptosis-related gene, can be used as a prognostic marker for thyroid cancer.