TONSL promotes lung adenocarcinoma progression, immune escape and drug sensitivity.

PURPOSE: The tonsoku-like DNA repair protein (TONSL) encoded by the TONSL gene, located on chromosome 8q24.3, is crucial for repairing DNA double-strand breaks through homologous recombination. However, TONSL overexpression in lung adenocarcinoma (LUAD) promotes tumor development, leading to a poor prognosis. METHODS: TONSL was verified as a reliable prognostic marker for LUAD using bioinformatics, and clinical features related to LUAD prognosis were screened from the TCGA database to establish the relationship between risk factors and TONSL expression. In addition, TONSL expression in normal and LUAD tissues was verified using real-time quantitative polymerase chain reaction and immunohistochemistry. To elucidate the possible functions of TONSL, TONSL-related differentially expressed genes were screened, and functional enrichment analysis was performed. Subsequently, siRNA was used to knock down TONSL expression in lung cancer cells for cytobehavioral experiments. The effects of TONSL expression on tumor immune escape were analyzed using the ESTIMATE algorithm and tumor immune-infiltration analysis. In addition, the half-maximal inhibitory concentration of LUAD with varying TONSL expression levels in response to first-line chemotherapeutic drugs and epidermal growth factor receptor-tyrosine kinase inhibitors was analyzed for drug sensitivity. RESULTS: Up-regulation of TONSL in LUAD promotes the proliferation, migration, and invasion of lung cancer cells, thereby contributing to a poor prognosis. Furthermore, TONSL overexpression promotes immune escape and drug sensitivity in LUAD. CONCLUSION: TONSL serves as a reliable prognostic marker for LUAD, and its up-regulation is associated with increased immune escape and drug sensitivity. These findings suggest that TONSL holds potential as a novel therapeutic target for LUAD.

Paired organoids from primary gastric cancer and lymphatic metastasis are useful for personalized medicine.

BACKGROUND: Organoids are approved by the US FDA as an alternative to animal experiments to guide drug development and for sensitivity screening. Stable organoids models of gastric cancer are desirable for personalized medicine and drug screening. METHODS: Tumor tissues from a primary cancer of the stomach and metastatic cancer of the lymph node were collected for 3D culture. By long-term culture for over 50 generations in vitro, we obtained stably growing organoid lines. We analyzed short tandem repeats (STRs) and karyotypes of cancer cells, and tumorigenesis of the organoids in nude mice, as well as multi-omics profiles of the organoids. A CCK8 method was used to determine the drugs sensitivity to fluorouracil (5-Fu), platinum and paclitaxel. RESULTS: Paired organoid lines from primary cancer (SPDO1P) and metastatic lymph node (SPDO1LM) were established with unique STRs and karyotypes. The organoid lines resulted in tumorigenesis in vivo and had clear genetic profiles. Compared to SPDO1P from primary cancer, upregulated genes of SPDO1LM from the metastatic lymph node were enriched in pathways of epithelial-mesenchymal transition and angiogenesis with stronger abilities of cell migration, invasion, and pro-angiogenesis. Based on drug sensitivity analysis, the SOX regimen (5-Fu plus oxaliplatin) was used for chemotherapy with an optimal clinical outcome. CONCLUSIONS: The organoid lines recapitulate the drug sensitivity of the parental tissues. The paired organoid lines present a step-change toward living biobanks for further translational usage.

Screening, epidemic trends and drug sensitivity analysis of nontuberculous mycobacteria in a local area of China.

OBJECTIVE: To analyze the isolation rate, prevalence trends, species distribution, and drug sensitivity of non-tuberculous mycobacteria (NTM) in Anhui Province, providing a reference for diagnosis and treatment strategies. METHODS: Specimens from suspected mycobacterial infection patients at Anhui Chest Hospital (including outpatients and inpatients) from January 2021 to December 2023 were cultured. Identified NTM strains were analyzed for species distribution and drug sensitivity. RESULTS: Of 10,519 mycobacteria strains cultured, 1,589 were NTM (15.11%). The top four species were Mycobacterium intracellulare (75.36%), Mycobacterium abscessus (11.78%), Mycobacterium kansasii (7.09%), and Mycobacterium avium (2.85%). NTM strains showed high sensitivity to amikacin and clarithromycin (≥90%) and significant sensitivity to rifabutin, moxifloxacin, and rifampicin (89.03%-79.61%). They exhibited high resistance to imipenem/cilastatin, sulfamethoxazole, minocycline, and doxycycline (≥95%). CONCLUSION: NTM isolation rates in Anhui have remained stable, with the predominant species being M. intracellulare, M. kansasii, M. abscessus, and M. avium. NTM strains are highly sensitive to amikacin, clarithromycin, rifabutin, moxifloxacin, and rifampicin. These findings can guide diagnosis, treatment strategies, and drug selection for NTM disease in Anhui Province.

Drug sensitivity testing during dental pulp-dentin complex repair: its effect on treatment outcome and prognosis.

OBJECTIVE: To assess the efficacy of targeted therapy based on drug sensitivity testing (DST) results in patients with acute pulpitis (AP). METHODS: A total of 80 cases of AP were included retrospectively and divided into two groups: control (Ctrl) group (conventional drug palliative therapy, n=40) and experimental (Exp) group (DST + non-resistant drugs, n=40). The clinical data and laboratory examination data of patients, including bacterial culture data, drug sensitivity test results, Ca and P contents in dental pulp, visual analogue scale (AVS), treatment satisfaction, and dental pulp incidence, were collected and analyzed. RESULTS: Prevotella melaninogenica, Fusobacterium nucleatum, and Porphyromonas gingivalis exhibited higher resistance rates (RS) to penicillin and amoxicillin but no resistance to imipenem and metronidazole. The content of Ca and P in the dental pulp of the Exp group patients was significantly higher than that of the Ctrl group (P=0.006). The total response rate (95% vs. 77.5%, P=0.018) and overall patient satisfaction (92.5% vs. 80%, P=0.021) were also significantly higher in the Exp group than in the Ctrl group. Additionally, when the follow-up duration exceeded 1 year, the incidence of dental pulp reactions in the Exp group was significantly lower than that of the Ctrl group (P=0.026). CONCLUSIONS: These findings suggest that Gram-negative anaerobes are the predominant oral pathogens in patients with AP. Imipenem and metronidazole demonstrate the most effective anti-infective properties against these anaerobes. Utilizing DST to select non-resistant drugs for treatment prior to therapy effectively enhances clinical outcomes for patients with AP.

Ferroptosis-related LINC02535/has-miR-30c-5p/EIF2S1 axis as a novel prognostic biomarker involved in immune infiltration and progression of PDAC.

BACKGROUND: PDAC, also known as pancreatic ductal adenocarcinoma, is often diagnosed at a late stage due to nonspecific symptoms and a distinct lack of reliable biomarkers for timely diagnosis. Ferroptosis, a novel non-apoptotic cell death mode discovered in recent years, is strongly linked to the progression of PDAC and the evasion of the immune system. The objective of this study is to discover a novel ceRNA biomarker associated with ferroptosis and investigate its possible molecular mechanisms and therapeutic potential in PDAC. METHODS: Based on the FerrDb and TCGA databases, the R survival package was used to screen for ferroptosis-related mRNAs associated with PDAC prognosis. The ferroptosis-related ceRNA network was identified by miRTarBase, miRNet, and starBase and visualized using Cytoscape. The LASSO regression analysis was used to build a risk model associated with ceRNA. Additionally, we investigated the correlation between the ceRNA axis and the infiltration of immune cells in PDAC by employing the ssGSEA algorithm. Spearman correlation analysis was used to investigate the association between the ceRNA network and the expression levels of immune checkpoint genes in PDAC. The prediction of potential medications for PAAD patients with high risk scores was conducted using the R package oncoPredict and the Genomics of Drug Sensitivity in Cancer (GDSC) repository. Expression levels of LINC02535 in clinical specimens and PDAC cell lines were determined using qRT-PCR. CCK-8, colony formation, EdU, wound healing, and transwell assays were performed to assess the impact of reducing LINC02535 on the growth, migration, and invasion of PDAC cell lines BxPC3 and PANC1. RESULTS: We first discovered a new LINC02535/miR-30c-5p/EIF2S1 axis associated with ferroptosis and created a prognostic nomogram for predicting overall survival. Meanwhile, the risk scores of the LINC02535/miR-30c-5p/EIF2S1 axis associated with ferroptosis were linked to immune subtypes in PDAC. The high immune infiltration subtype exhibited elevated ceRNA risk scores and EIF2S1 expression. The correlation analysis revealed a positive correlation between ceRNA risk scores and four immune cells, namely Activated CD4 T cell, Memory B cell, Neutrophil, and Type 2 T helper cell, as well as four immune checkpoint genes, namely CD274, HAVCR2, PDCD1LG2, and TIGIT. The analysis of drug sensitivity indicated that individuals with a high-risk score may exhibit greater sensitivity to inhibitors targeting MEK1/2 compared to those with a low-risk score. In our validation experiments, it was observed that the expression of LINC02535 was increased in both PDAC tissues and cell lines. Additionally, the inhibition of LINC02535 resulted in decreased proliferation, migration, and invasion of PDAC cells. Rescue experiments demonstrated that LINC02535 promoted PDAC cell growth and metastasis by upregulating EIF2S1 expression. CONCLUSION: To summarize, a novel ferroptosis-associated LINC02535/miR-30c-5p/EIF2S1 ceRNA network for PDAC patients was established. The analysis of this network's functionality offers potential insights for clinical decision-making and the advancement of precision medicine.

The GJB3 correlates with the prognosis, immune cell infiltration, and therapeutic responses in lung adenocarcinoma.

Gap junction protein beta 3 (GJB3) has been reported as a tumor suppressor in most tumors. However, its role in lung adenocarcinoma (LUAD) remains unknown. The purpose of this study is to explore the role of GJB3 in the prognosis and tumor microenvironment of LUAD patients. The data used in this study were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and imvigor210 cohorts. We found that GJB3 expression was increased in LUAD patients and correlated with LUAD stages. LUAD patients with high GJB3 expression exhibited a worse prognosis. A total of 164 pathways were significantly activated in the GJB3 high group. GJB3 expression was positively associated with nine transcription factors and might be negatively regulated by hsa-miR-6511b-5p. Finally, we found that immune cell infiltration and immune checkpoint expression were different between the GJB3 high and GJB3 low groups. In summary. GJB3 demonstrated high expression levels in LUAD patients, and those with elevated GJB3 expression displayed unfavorable prognoses. Additionally, there was a correlation between GJB3 and immune cell infiltration, as well as immune checkpoint expression in LUAD patients.

Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.

With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent scientific and societal issues. To this end, the European Union passed the EU AI Act, proposing solution strategies that can be summarized under the umbrella term trustworthiness. In anti-cancer drug sensitivity prediction, machine learning (ML) methods are developed for application in medical decision support systems, which require an extraordinary level of trustworthiness. This review offers an overview of the ML landscape of methods for anti-cancer drug sensitivity prediction, including a brief introduction to the four major ML realms (supervised, unsupervised, semi-supervised, and reinforcement learning). In particular, we address the question to what extent trustworthiness-related properties, more specifically, interpretability and reliability, have been incorporated into anti-cancer drug sensitivity prediction methods over the previous decade. In total, we analyzed 36 papers with approaches for anti-cancer drug sensitivity prediction. Our results indicate that the need for reliability has hardly been addressed so far. Interpretability, on the other hand, has often been considered for model development. However, the concept is rather used intuitively, lacking clear definitions. Thus, we propose an easily extensible taxonomy for interpretability, unifying all prevalent connotations explicitly or implicitly used within the field.

Pan-cancer analyses reveal the molecular and clinical characteristics of TET family members and suggests that TET3 maybe a potential therapeutic target.

The Ten-Eleven Translocation (TET) family genes are implicated in a wide array of biological functions across various human cancers. Nonetheless, there is a scarcity of studies that comprehensively analyze the correlation between TET family members and the molecular phenotypes and clinical characteristics of different cancers. Leveraging updated public databases and employing several bioinformatics analysis methods, we assessed the expression levels, somatic variations, methylation levels, and prognostic values of TET family genes. Additionally, we explored the association between the expression of TET family genes and pathway activity, tumor microenvironment (TME), stemness score, immune subtype, clinical staging, and drug sensitivity in pan-cancer. Molecular biology and cytology experiments were conducted to validate the potential role of TET3 in tumor progression. Each TET family gene displayed distinct expression patterns across at least ten detected tumors. The frequency of Single Nucleotide Variant (SNV) in TET genes was found to be 91.24%, primarily comprising missense mutation types, with the main types of copy number variant (CNV) being heterozygous amplifications and deletions. TET1 gene exhibited high methylation levels, whereas TET2 and TET3 genes displayed hypomethylation in most cancers, which correlated closely with patient prognosis. Pathway activity analysis revealed the involvement of TET family genes in multiple signaling pathways, including cell cycle, apoptosis, DNA damage response, hormone AR, PI3K/AKT, and RTK. Furthermore, the expression levels of TET family genes were shown to impact the clinical staging of tumor patients, modulate the sensitivity of chemotherapy drugs, and thereby influence patient prognosis by participating in the regulation of the tumor microenvironment, cellular stemness potential, and immune subtype. Notably, TET3 was identified to promote cancer progression across various tumors, and its silencing was found to inhibit tumor malignancy and enhance chemotherapy sensitivity. These findings shed light on the role of TET family genes in cancer progression and offer insights for further research on TET3 as a potential therapeutic target for pan-cancer.

Construction and validation of a prognostic model for overall survival time of patients with ovarian cancer by metabolism-related genes.

BACKGROUND: Ovarian cancer is a female-specific malignancy with high morbidity and mortality. The metabolic reprogramming of tumor cells is closely related to the biological behavior of tumors. METHODS: The prognostic signature of the metabolism-related gene (MRGs) was established by LASSO-Cox regression analysis. The prognostic signature of MRGs was also prognosticated in each clinical subgroup. These genes were subjected to functional enrichment analysis and tissue expression exploration. Analysis of the MRG prognostic signature in terms of immune cell infiltration and antitumor drug susceptibility was also performed. RESULTS: A MRG prognostic signature including 21 genes was established and validated. Most of the 21 MRGs were expressed at different levels in ovarian cancer than in normal ovarian tissue. The enrichment analysis suggested that MRGs were involved in lipid metabolism, membrane organization, and molecular binding. The MRG prognostic signature demonstrated the predictive value of overall survival time in various clinical subgroups. The monocyte, NKT, Tgd and Tex cell scores showed differences between the groups with high- and low-risk score. The antineoplastic drug analysis we performed provided information on ovarian cancer drug therapy and drug resistance. In vitro experiments verified that PLCH1 in 21 MRGs can regulate the apoptosis and proliferation of ovarian cancer cells. CONCLUSION: This metabolism-related prognostic signature was a potential prognostic factor in patients with ovarian cancer, demonstrating high stability and accuracy.

Exploring prognostic DNA methylation genes in bladder cancer: a comprehensive analysis.

The current study aimed to investigate the status of genes with prognostic DNA methylation sites in bladder cancer (BLCA). We obtained bulk transcriptome sequencing data, methylation data, and single-cell sequencing data of BLCA from public databases. Initially, Cox survival analysis was conducted for each methylation site, and genes with more than 10 methylation sites demonstrating prognostic significance were identified to form the BLCA prognostic methylation gene set. Subsequently, the intersection of marker genes associated with epithelial cells in single-cell sequencing analysis was obtained to acquire epithelial cell prognostic methylation genes. Utilizing ten machine learning algorithms for multiple combinations, we selected key genes (METRNL, SYT8, COL18A1, TAP1, MEST, AHNAK, RPP21, AKAP13, RNH1) based on the C-index from multiple validation sets. Single-factor and multi-factor Cox analyses were conducted incorporating clinical characteristics and model genes to identify independent prognostic factors (AHNAK, RNH1, TAP1, Age, and Stage) for constructing a Nomogram model, which was validated for its good diagnostic efficacy, prognostic prediction ability, and clinical decision-making benefits. Expression patterns of model genes varied among different clinical features. Seven immune cell infiltration prediction algorithms were used to assess the correlation between immune cell scores and Nomogram scores. Finally, drug sensitivity analysis of Nomogram model genes was conducted based on the CMap database, followed by molecular docking experiments. Our research offers a reference and theoretical basis for prognostic evaluation, drug selection, and understanding the impact of DNA methylation changes on the prognosis of BLCA.

Gene signature developed based on programmed cell death to predict the therapeutic response and prognosis for liver hepatocellular carcinoma.

Background: The prognosis and therapeutic response of patients with liver hepatocellular carcinoma (LIHC) can be predicted based on programmed cell death (PCD) as PCD plays a crucial role during tumor progression. We developed a PCD-related gene signature to evaluate the therapeutic response and prognosis for patients with LIHC. Methods: Molecular subtypes of LIHC were classified using ConsensusClusterPlus according to the gene biomarkers related to PCD. To predict the prognosis of high- and low-risk LIHC patients, a risk model was established by LASSO regression analysis based on the prognostic genes. Functional enrichment analysis was conducted using clusterProfiler package, and relative abundance of immune cells was quantified applying CIBERSORT package. Finally, to determine drug sensitivity, oncoPredict package was employed. Results: PCD was correlated with the clinicopathologic features of LIHC. Then, we defined four molecular subtypes (C1-C4) of LIHC using PCD-related prognostic genes. Specifically, subtype C1 had the worst prognosis with enriched T cells regulatory (Tregs) and Macrophage_M0 and higher expression of T cell exhaustion markers, meanwhile, C1 also had a relatively higher TIDE score and metastasis potential. A risk model was established using 5 prognostic genes. High-risk patients tended to have higher expression of T cell exhaustion markers and TIDE score and unfavorable outcomes, and they were more sensitive to small molecule drug 5.Fluorouracil. Conclusion: A PCD-related gene signature was developed and verified to be able to accurately predict the prognosis and drug sensitivity of LIHC patients.

Analysis of the resistance profile of real-world alectinib first-line therapy in patients with ALK rearrangement-positive advanced non-small cell lung cancer using organoid technology in one case of lung cancer.

Background: Alectinib has achieved excellent therapeutic efficacy in anaplastic lymphoma kinase (ALK) fusion gene-positive non-small cell lung cancer (NSCLC) patients, however, patients eventually develop resistance to it. Exploring the gene variant mapping after alectinib resistance provides a basis for the whole management of ALK-positive advanced NSCLC. This study aimed to characterize the mutation profiles of real-world ALK rearrangement-positive advanced NSCLC patients after first-line alectinib treatment resistance. The research also investigated the treatment options and coping strategies after resistance. Methods: Clinical data of patients with advanced NSCLC who received first-line alectinib treatment in the First Affiliated Hospital of Guangzhou Medical University between November 2018 and April 2022 were collected. Moreover, next-generation sequencing (NGS) data of the patient's baseline and post-resistance tissues were gathered. One patient underwent lung cancer organoid culture and drug sensitivity testing. Results: Out of 35 first-line alectinib-treated patients with advanced NSCLC, 31 are presently in progression-free survival (PFS; 4.3-35.0 months). Four patients experienced progressive disease, and all of them were sequentially treated with ceritinib. Tissue NGS results before sequential treatment in three patients indicated an echinoderm microtubule-associated protein-like 4-ALK fusion that remained at the original baseline, and the PFS for ceritinib treatment was 0.5-1.3 months. One patient developed acquired resistance mutations in the structural domain of ALK protein kinase (V1180L and E1161D), and the PFS for ceritinib treatment was 6.7 months. For one patient who maintained original baseline ALK rearrangement positive without acquired mutation after progression of ceritinib resistance, lung cancer-like organ culture with sequential brigatinib and lorlatinib led to a PFS of 3.2 and 1.9 months, respectively, which aligned with the corresponding drug susceptibility testing results for this patient. Conclusions: For ALK rearrangement-positive patients, blind sequencing of other second-generation tyrosine kinase inhibitors (TKIs) or third-generation lorlatinib may not guarantee satisfactory tumor suppression following first-line second-generation ALK-TKI alectinib administration for treatment progression. NGS testing of patients' blood or tissue samples after disease progression may provide insight into the etiology of alectinib resistance. Patient-sourced drug sensitivity testing of lung cancer-like organs selects drug-sensitive medications based on NGS results and provides a reference for subsequent drug therapy for patients after drug resistance, particularly those who remain ALK rearrangement-positive at baseline.

An Apoptosis-Related Specific Risk Model for Breast Cancer: From Genomic Analysis to Precision Medicine.

BACKGROUND: Breast cancer (BC) ranks as the most prevalent malignancy affecting women globally, with apoptosis playing a pivotal role in its pathological progression. Despite the crucial role of apoptosis in BC development, there is limited research exploring the relationship between BC prognosis and apoptosis-related genes (ARGs). Therefore, this study aimed to establish a BC-specific risk model centered on apoptosis-related factors, presenting a novel approach for predicting prognosis and immune responses in BC patients. METHODS: Utilizing data from The Cancer Gene Atlas (TCGA), Cox regression analysis was employed to identify differentially prognostic ARGs and construct prognostic models. The accuracy and clinical relevance of the model, along with its efficacy in predicting immunotherapy outcomes, were evaluated using independent datasets, Receiver Operator Characteristic (ROC) curves, and nomogram. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were used to predict potential mechanical pathways. The CellMiner database is used to assess drug sensitivity of model genes. RESULTS: A survival risk model comprising eight prognostically relevant apoptotic genes (PMAIP1, TP53AIP1, TUBA3D, TUBA1C, BCL2A1, EMP1, GSN, F2) was established based on BC patient samples from TCGA. Calibration curves validated the ROC curve and nomogram, demonstrating excellent accuracy and clinical utility. In samples from the Gene Expression Omnibus (GEO) datasets and immunotherapy groups, the low-risk group (LRG) demonstrated enhanced immune cell infiltration and improved immunotherapy responses. Model genes also displayed positive associations with sensitivity to multiple drugs, including vemurafenib, dabrafenib, PD-98059, and palbociclib. CONCLUSIONS: This study successfully developed and validated a prognostic model based on ARGs, offering new insights into prognosis and immune response prediction in BC patients. These findings hold promise as valuable references for future research endeavors in this field.

Development of a Novel Prognostic Panel for Colorectal Cancer Based on Cancer Functional Status, and Validation of STC2 as a Promising Biomarker.

BACKGROUND: Improving the clinical outcome of colorectal cancer (CRC) patients remains a major challenge. This study aimed to develop a new predictive classifier for CRC and to examine its relationship with the immune environment and therapeutic response. METHODS: A comprehensive bioinformatics analysis was applied to develop a risk panel comprised of cancer function status-related genes (CFSRGs). This panel was evaluated for prognostic utility by Area Under the Curve (AUC) and Kaplan-Meier (KM) analyses. Differences between high- and low-risk groups were subsequently investigated using multi-omics data. Immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (qRT-PCR), and cell phenotype assays were also employed to ascertain the clinical value of STC2 expression. RESULTS: Significant differences were observed in the survival rate between high- and low-risk groups defined by our 7-CFSRG panel, both in internal and external CRC patient cohorts. The AUC for prediction of survival at 1-, 3- and 5-years was satisfactory in all cohorts. Detailed analysis revealed that tumor mutation burden, drug sensitivity, and pathological stage were closely associated with the risk score. Elevated expression of STC2 in CRC tissues relative to normal paraneoplastic tissues was associated with less favorable patient outcomes. qRT-PCR experiments confirmed that STC2 expression was significantly upregulated in several CRC cell lines (HCT116, SW480, and LOVO) compared to a normal intestinal epithelial cell line (NCM460). The proliferation, migration, and invasion of CRC cells were all significantly inhibited by knockdown of STC2. CONCLUSIONS: Our 7-CFSRG panel is a promising classifier for assessing the prognosis of CRC patients. Moreover, the targeting of STC2 may provide a novel therapeutic approach for improving patient outcomes.

DNA Methylation as Drug Sensitivity Marker in RCC: A Systematic Review.

Patient response after treatment of renal cell cancer (RCC) with systemic agents, which include various drug categories, is generally poor and unpredictable. In this context, the ideal drug administration includes tools to predict the sensitivity of the disease to therapy. The aim of this study was to systematically summarize the reports on the predictive value of the methylation status in the systemic therapy of RCC. Only original articles reporting on the association of promoter methylation with the response of patients or cell lines to systemic agents were included in this review. We applied PRISMA recommendations to the structure and methodology of this systematic review. Our literature search concluded with 31 articles conducted on RCC cell lines and patient tissues. The majority of the studies demonstrated a methylation-dependent response to systemic agents. This correlation suggests that the methylation pattern can be used as a predictive tool in the management of RCC with various classes of systemic agents. However, although methylation biomarkers show promise for predicting response, the evidence of such correlation is still weak. More studies on the gene methylation pattern in patients under systemic therapy and its correlation with different degrees of response are needed.

PER2 binding to PDK1 enhances the cisplatin sensitivity of oral squamous cell carcinoma through inhibition of the AKT/mTOR pathway.

Cisplatin (CDDP) is a cornerstone chemotherapeutic agent used to treat oral squamous cell carcinoma (OSCC) and many solid cancers. However, the mechanisms underlying tumor resistance to CDDP obscure the enhancement of its therapeutic efficacy. In this study, we unveil diminished expression of the biological clock gene PER2 in OSCC, negatively correlated with the expression of multidrug resistance protein 1 (MDR1) and multidrug resistance-associated protein 1 (MRP1). The overexpression of PER2 suppressed MDR1 and MRP1 expression and increased intracellular CDDP levels and DNA damage, thereby bolstering OSCC cell sensitivity to CDDP. In vivo tumorigenic assays corroborated that PER2 overexpression notably increased OSCC sensitivity to CDDP, augmenting the suppression of OSCC tumorigenesis. Co-immunoprecipitation, GST pull-down, and cycloheximide tracking assays revealed that PER2, via its C-terminal domain, bound to and diminishes PDK1 stability. The degradation of PDK1 was further dependent on the suppression of the AKT/mTOR pathway to enhance the sensitivity of OSCC cells to CDDP. Our study supports PER2 as a target for improving CDDP sensitivity in OSCC, and the combination of PER2 and CDDP is a novel strategy with potential clinical therapeutic value.

A Multi-Omics Analysis of an Exhausted T Cells' Molecular Signature in Pan-Cancer.

T cells are essential tumor suppressors in cancer immunology, but their dysfunction induced by cancer cells can result in T cell exhaustion. Exhausted T cells (Tex) significantly influence the tumor immune environment, and thus, there is a need for their thorough investigation across different types of cancer. Here, we address the role of Tex cells in pan-cancer, focusing on the expression, mutations, methylation, immune infiltration, and drug sensitivity of a molecular signature comprising of the genes HAVCR2, CXCL13, LAG3, LAYN, TIGIT, and PDCD1across multiple cancer types, using bioinformatics analysis of TCGA data. Our analysis revealed that the Tex signature genes are differentially expressed across 14 cancer types, being correlated with patient survival outcomes, with distinct survival trends. Pathway analysis indicated that the Tex genes influence key cancer-related pathways, such as apoptosis, EMT, and DNA damage pathways. Immune infiltration analysis highlighted a positive correlation between Tex gene expression and immune cell infiltration in bladder cancer, while mutations in these genes were associated with specific immune cell enrichments in UCEC and SKCM. CNVs in Tex genes were widespread across cancers. We also highlight high LAYN methylation in most tumors and a negative correlation between methylation levels and immune cell infiltration in various cancers. Drug sensitivity analysis identified numerous correlations, with CXCL13 and HAVCR2 expressions influencing sensitivity to several drugs, including Apitolisib, Belinostat, and Docetaxel. Overall, these findings highlight the importance of reviving exhausted T cells to enhance the treatment efficacy to significantly boost anti-tumor immunity and achieve better clinical outcomes.

Antifungal Activity of Morinda citrifolia Methanolic Extract against Candida albicans: An In Vitro Study.

Aim: Natural medicine used as an alternative and/or complementary treatment to counteract diseases is of great importance in public health. Therefore, the purpose of the present study was to assess the in vitro antifungal activity of Morinda citrifolia methanolic extract of peel, pulp, and seed against Candida albicans. Materials and Methods: The present study was experimental in vitro and cross-sectional. Eight replicates were prepared in Sabouraud dextrose agar with five wells each, where 0.12% chlorhexidine, distilled water, and methanolic extract of seed, peel, and pulp of Morinda citrifolia fruit were placed at concentrations of 10,690, 8,270, and 6,430 mg/mL, respectively, to evaluate sensitivity according to Duraffourd's scale. In addition, the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined by dilution and agar seeding method. Statistical analysis was performed by analysis of variance (ANOVA) and Tukey's post hoc test, considering a significance level of P < 0.05. Results: The inhibition halos of Morinda citrifolia methanolic extract of seed, peel, and pulp against Candida albicans measured on average 15.94, 11.94, and 11.56 mm, respectively. The MIC of seed, peel, and pulp extract were 1366.25, 2067.5, and 1607.5 mg/mL respectively, whereas the MFC for seed, peel, and pulp extract were 2672.50, 2067.5, and 3215 mg/mL, respectively. Moreover, seed extract presented significantly higher antifungal activity than peel and pulp (P < 0.001). Conclusions: Morinda citrifolia methanolic extract of peel, pulp, and seed showed fungistatic and fungicidal effect against Candida albicans, being this very sensitive to seed extract with a MIC of 1366.25 mg/mL and a MFC of 2672.5 mg/mL, which allows recommending the development of effective pharmacological formulations for the control of candidiasis.

Comprehensive bioinformatics analysis and cell line experiments revealed the important role of CDCA3 in sarcoma.

Background: Sarcoma mainly originate from bone and soft tissue and are highly aggressive malignant tumors. Cell division cycle-related protein 3 (CDCA3) is a protein involved in the regulation of the cell cycle, which is highly expressed in a variety of malignant tumors. However, its role in sarcoma remains unclear. This study aims to investigate the function and potential mechanism of CDCA3 in sarcoma and to elucidate its importance in sarcoma. Methods: We first studied the expression and prognosis of CDCA family members in sarcoma by Oncomine and the Gene Expression Profiling Interactive Analysis (GEPIA). The role of CDCA3 protein in sarcoma was further analyzed by the Cancer Genome Atlas Program (TCGA), the Cancer Cell Lineage Encyclopedia (CCLE), and Linke-dOmics. In addition, immunohistochemistry and Western blot were used to verify the expression of CDCA3 protein in clinical samples as well as sarcoma cell lines (U2OS, SAOS2, MG63, and HOS). Subsequently, in vitro experiments (cloning and scratching experiments) were performed using sh-NC as well as sh-CDCA3 group cells to reveal the biological functions of CDCA3. Results: We found that the CDCA family (CDCA3, CDCA4, and CDCA8) is highly expressed in sarcoma, and the expression level of CDCA3, CDCA4, and CDCA8 negatively correlates with the prognosis of sarcoma patients. CDCA3 mRNA was highly expressed in pan-cancer by CCLE and TCGA database analysis. KEGG analysis showed that CDCA3 was mainly enriched in the cell cycle signaling pathway (It promoted the transition of the cell cycle from the G0/G1 phase to the S phase). In the level of immune infiltration, CDCA3 was negatively correlated with pDC cells, CD8+T cells, and cytotoxic cells. Finally, patients with high CDCA3 expression in sarcoma were analyzed for resistance to NU7441 and others, while sensitive to Fulvestrant and Dihydrorotenone. Furthermore, we demonstrated high expression of CDCA3 protein in sarcoma tissues and cell lines by immunohistochemistry and Western blot experiments. Cloning, EDU, scratching, and migration experiments showed that the knockdown of CDCA3 inhibited the Proliferation and progression of sarcoma cells. Conclusion: These results suggest for the first time that knockdown of CDCA3 may inhibit sarcoma progression. CDCA3 may be an effective target for the treatment of sarcoma.

Inhibition of NNMT enhances drug sensitivity in lung cancer cells through mediation of autophagy.

Introduction: This study aimed to investigate the role of Nicotinamide N-methyltransferase (NNMT) in the drug sensitivity of non-small cell lung cancer (NSCLC) cells, with a focus on its impact on autophagy and resistance to the chemotherapeutic agent osimertinib. The study hypothesized that NNMT knockdown would enhance drug sensitivity by modifying autophagic processes, providing a potential new therapeutic target for overcoming chemoresistance in lung cancer. Methods: Proteomic analysis was utilized to identify changes in protein expression following NNMT knockdown in H1975 and H1975 osimertinib resistance (H1975OR) lung cancer cell lines. Gene expression patterns and their correlation with NNMT expression in lung cancer patients were analyzed using The Cancer Genome Atlas (TCGA) dataset. Additionally, a predictive model for lung cancer survival was developed via lasso regression analysis based on NNMT-associated gene expression. Drug sensitivity was assessed using the IC50 values and apoptosis ratio, and autophagy was evaluated through Western blot and flow cytometric analysis. Results: Significant variations in the expression of 1,182 proteins were observed following NNMT knockdown, with a significant association with autophagy-related genes. Analysis of gene expression patterns unveiled a significant correlation between NNMT expression and specific changes in gene expression in lung cancer. The predictive model successfully forecasted lung cancer patient survival outcomes, highlighting the potential of NNMT-associated genes in predicting patient survival. Knockdown of NNMT reversed osimertinib resistance in H1975 cells, as evidenced by altered IC50 values and apoptosis ratio, and changes were observed in autophagy markers. Discussion: Knockdown of NNMT in lung cancer cells enhances drug sensitivity by modulating autophagy, providing a promising therapeutic target to overcome chemoresistance in NSCLC. The study underscores the importance of NNMT in lung cancer pathology and underscores its potential as a predictive marker for clinical outcomes. Additionally, the developed predictive model further supports the clinical relevance of NNMT-associated gene expression in improving the prognosis of lung cancer patients.