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.

Establishment of a prognostic model for pancreatic cancer based on vesicle-mediated transport protein-related genes.

This study attempted to build a prognostic riskscore model for pancreatic cancer (PC) patients based on vesicle-mediated transport protein-related genes (VMTGs). We initially conducted differential expression analysis and Cox regression analysis, followed by the construction of a riskscore model to classify PC patients into high-risk (HR) and low-risk (LR) groups. The GEO GSE62452 dataset further validated the model. Kaplan-Meier survival analysis was employed to analyze the survival rate of the HR group and LR group. Cox analysis confirmed the independent prognostic ability of the riskscore model. Additionally, we evaluated immune status in both HR and LR groups, utilizing data from the GDSC database to predict drug response among PC patients. We identified six PC-specific genes from 724 VMTGs. Survival analysis revealed that the survival rate of the HR group was lower than that of the LR group (P<0.05). Cox analysis confirmed that the prognostic riskscore model could independently predict the survival status of PC patients (P<0.001). Immunological analysis revealed that the ESTIMATE score, immune score, and stroma score of the HR group were considerably lower than those of the LR group, and the tumor purity score of the HR group was higher. The IC50 values of Gemcitabine, Irinotecan, Oxaliplatin, and Paclitaxel in the LR group were considerably lower than those in the HR group (P<0.001). In summary, the VMTG-based prognostic riskscore model could stratify PC risk and effectively predict the survival of PC patients.

Bioinformatics analysis of an immunotherapy responsiveness-related gene signature in predicting lung adenocarcinoma prognosis.

Background: Immune therapy has become first-line treatment option for patients with lung cancer, but some patients respond poorly to immune therapy, especially among patients with lung adenocarcinoma (LUAD). Novel tools are needed to screen potential responders to immune therapy in LUAD patients, to better predict the prognosis and guide clinical decision-making. Although many efforts have been made to predict the responsiveness of LUAD patients, the results were limited. During the era of immunotherapy, this study attempts to construct a novel prognostic model for LUAD by utilizing differentially expressed genes (DEGs) among patients with differential immune therapy responses. Methods: Transcriptome data of 598 patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) database, which included 539 tumor samples and 59 normal control samples, with a mean follow-up time of 29.69 months (63.1% of patients remained alive by the end of follow-up). Other data sources including three datasets from the Gene Expression Omnibus (GEO) database were analyzed, and the DEGs between immunotherapy responders and nonresponders were identified and screened. Univariate Cox regression analysis was applied with the TCGA cohort as the training set and GSE72094 cohort as the validation set, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied in the prognostic-related genes which fulfilled the filter criteria to establish a prognostic formula, which was then tested with time-dependent receiver operating characteristic (ROC) analysis. Enriched pathways of the prognostic-related genes were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and tumor immune microenvironment (TIME), tumor mutational burden, and drug sensitivity tests were completed with appropriate packages in R (The R Foundation of Statistical Computing). Finally, a nomogram incorporating the prognostic formula was established. Results: A total of 1,636 DEGs were identified, 1,163 prognostic-related DEGs were extracted, and 34 DEGs were selected and incorporated into the immunotherapy responsiveness-related risk score (IRRS) formula. The IRRS formula had good performance in predicting the overall prognoses in patients with LUAD and had excellent performance in prognosis prediction in all LUAD subgroups. Moreover, the IRRS formula could predict anticancer drug sensitivity and immunotherapy responsiveness in patients with LUAD. Mechanistically, immune microenvironments varied profoundly between the two IRRS groups; the most significantly varied pathway between the high-IRRS and low-IRRS groups was ribonucleoprotein complex biogenesis, which correlated closely with the TP53 and TTN mutation burdens. In addition, we established a nomogram incorporating the IRRS, age, sex, clinical stage, T-stage, N-stage, and M-stage as predictors that could predict the prognoses of 1-year, 3-year, and 5-year survival in patients with LUAD, with an area under curve (AUC) of 0.718, 0.702, and 0.68, respectively. Conclusions: The model we established in the present study could predict the prognosis of LUAD patients, help to identify patients with good responses to anticancer drugs and immunotherapy, and serve as a valuable tool to guide clinical decision-making.

Unveiling the therapeutic prospects of IFNW1 and IFNA21: insights into glioma pathogenesis and clinical significance.

Glioma, a type of brain tumor, poses significant challenges due to its heterogeneous nature and limited treatment options. Interferon-related genes (IRGs) have emerged as potential players in glioma pathogenesis, yet their expression patterns and clinical implications remain to be fully elucidated. We conducted a comprehensive analysis to investigate the expression patterns and functional enrichment of IRGs in glioma. This involved constructing protein-protein interaction networks, heatmap analysis, survival curve plotting, diagnostic and prognostic assessments, differential expression analysis across glioma subgroups, GSVA, immune infiltration analysis, and drug sensitivity analysis. Our analysis revealed distinct expression patterns and functional enrichment of IRGs in glioma. Notably, IFNW1 and IFNA21 were markedly downregulated in glioma tissues compared to normal tissues, and higher expression levels were associated with improved overall survival and disease-specific survival. Furthermore, these genes showed diagnostic capabilities in distinguishing glioma tissues from normal tissues and were significantly downregulated in higher-grade and more aggressive gliomas. Differential expression analysis across glioma subgroups highlighted the association of IFNW1 and IFNA21 expression with key pathways and biological processes, including metabolic reprogramming and immune regulation. Immune infiltration analysis revealed their influence on immune cell composition in the tumor microenvironment. Additionally, elevated expression levels were associated with increased resistance to chemotherapeutic agents. Our findings underscore the potential of IFNW1 and IFNA21 as diagnostic biomarkers and prognostic indicators in glioma. Their roles in modulating glioma progression, immune response, and drug sensitivity highlight their significance as potential therapeutic targets. These results contribute to a deeper understanding of glioma biology and may inform the development of personalized treatment strategies for glioma patients.

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Prognostic Value and Clinical Significance of Vesicular Transport-Related Genes in Clear Cell Renal Cell Carcinoma.

INTRODUCTION: Vesicular transport (VT) has a complex relationship with tumor progression and immunity. But prognostic significance of VT in clear cell renal cell carcinoma (ccRCC) is unclear. Thus, we aimed to establish a prognostic model according to VT to predict overall survival of ccRCC patients. METHODS: We used patient data from TCGA database and built a prognostic model with 13 VT-related genes (VTRGs) by differential expression analysis, LASSO regression, and univariate/multivariate Cox analysis. The model was validated internally and externally, and survival analysis and ROC curves depicted excellent predictive ability. Furthermore, higher modeled riskscores corresponded to more advanced tumor progression. To further understand the potential reasons for different prognoses in patients, we did enrichment analysis on differentially expressed genes identified by the model in risk groups. The expression levels and roles of SAA1 and KIF18B in ccRCC were verified by qRT-PCR and cell function experiments. RESULTS: Humoral immune response and cAMP signaling pathway may be the biological processes and pathways leading to poor prognosis. Further analysis of immune microenvironment presented that ccRCC patients with poor prognoses had highly immune-infiltrated characteristics. We compared the drug response data of samples from different prognostic patients in the GDSC database and identified drug sensitivity differences associated with prognosis. Finally, we demonstrated that SAA1 and KIF18B could increase the proliferation, migration, and invasion ability of ccRCC cells using cellular experiments. CONCLUSION: In summary, we further revealed the importance of VTRGs in ccRCC prognosis.

Exploration of the combined role of immune checkpoints and immune cells in the diagnosis and treatment of ankylosing spondylitis: a preliminary study immune checkpoints in ankylosing spondylitis.

OBJECTIVE: Immune checkpoints have emerged as promising therapeutic targets for autoimmune diseases. However, the specific roles of immune checkpoints in the pathophysiology of ankylosing spondylitis (AS) remain unclear. METHODS: Hip ligament samples were obtained from two patient groups: those with AS and femoral head deformity, and those with femoral head necrosis but without AS, undergoing hip arthroplasty. Label-Free Quantification (LFQ) Protein Park Analysis was used to identify the protein composition of the ligaments. Peripheral blood samples of 104 AS patients from public database were used to validate the expression of key proteins. KEGG, GO, and GSVA were employed to explore potential pathways regulated by immune checkpoints in AS progression. xCell was used to calculate cell infiltration levels, LASSO regression was applied to select key cells, and the correlation between immune checkpoints and immune cells was analyzed. Drug sensitivity analysis was conducted to identify potential therapeutic drugs targeting immune checkpoints in AS. The expression of key genes was validated through immunohistochemistry (IHC). RESULTS: HLA-DMB and HLA-DPA1 were downregulated in the ligaments of AS and this has been validated through peripheral blood datasets and IHC. Significant differences in expression were observed in CD8 + Tcm, CD8 + T cells, CD8 + Tem, osteoblasts, Th1 cells, and CD8 + naive T cells in AS. The infiltration levels of CD8 + Tcm and CD8 + naive T cells were significantly positively correlated with the expression levels of HLA-DMB and HLA-DPA1. Immune cell selection using LASSO regression showed good predictive ability for AS, with AUC values of 0.98, 0.81, and 0.75 for the three prediction models, respectively. Furthermore, this study found that HLA-DMB and HLA-DPA1 are involved in Th17 cell differentiation, and both Th17 cell differentiation and the NF-kappa B signaling pathway are activated in the AS group. Drug sensitivity analysis showed that AS patients are more sensitive to drugs such as doramapimod and GSK269962A. CONCLUSION: Immune checkpoints and immune cells could serve as avenues for exploring diagnostic and therapeutic strategies for AS.

Isocucurbitacin B inhibits glioma growth through PI3K/AKT pathways and increases glioma sensitivity to TMZ by inhibiting hsa-mir-1286a.

Aim: Glioma accounts for 81% of all cancers of the nervous system cancers and presents one of the most drug-resistant malignancies, resulting in a relatively high mortality rate. Despite extensive efforts, the complete treatment options for glioma remain elusive. The effect of isocucurbitacin B (isocuB), a natural compound extracted from melon pedicels, on glioma has not been investigated. This study aims to investigate the inhibitory effect of isocuB on glioma and elucidate its underlying mechanisms, with the objective of developing it as a potential therapeutic agent for glioma. Methods: We used network pharmacology and bioinformatics analysis to predict potential targets and associated pathways of isocuB in glioma. Subsequently, the inhibitory effect of isocuB on glioma and its related mechanisms were assessed through Counting Kit-8 (CCK-8), wound healing, transwell, Western blot (WB), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and other in vitro experiments, alongside tumor formation experiments in nude mice. Results: Based on this investigation, it suggested that isocuB might inhibit the growth of gliomas through the PI3K-AKT and MAPK pathways. Additionally, we proposed that isocuB may enhance glioma drug sensitivity to temozolomide (TMZ) via modulation of hsa-mir-1286a. The CCK-8 assay revealed that isocuB exhibited inhibitory effects on U251 and U87 proliferation and outperformed TMZ. Wound healing and transwell experiments showed that isocuB inhibited the invasion and migration of U251 cells by suppressing the activity of MMP-2/9, N-cadherin, and Vimentin. The TdT-mediated dUTP-biotin nick end labeling (TUNEL) and flow cytometry (FCM) assays revealed that isocuB induced cell apoptosis through inhibition of BCL-2. Subsequently, we conducted RT-qPCR and WB experiments, which revealed that PI3K/AKT and MAPK pathways might be involved in the mechanism of the inhibition isocuB on glioma. Additionally, isocuB promoted the sensitivity of glioma U251 to TMZ by inhibiting hsa-mir-1286a. Furthermore, we constructed TMZ-resistant U251 strains and demonstrated effective inhibition by isocuB against these resistant strains. Finally, we confirmed that isocuB can inhibit tumor growth in vivo through experiments on tumors in nude mice. Conclusion: IsocuB may protect against glioma by acting on the PI3K/AKT and MAPK pathways and promote the sensitivity of glioma U251 to TMZ by inhibiting hsa-mir-1286a.

Risk score constructed with neutrophil extracellular traps-related genes predicts prognosis and immune microenvironment in multiple myeloma.

Background: Multiple myeloma (MM) exhibits considerable heterogeneity in treatment responses and survival rates, even when standardized care is administered. Ongoing efforts are focused on developing prognostic models to predict these outcomes more accurately. Recently, neutrophil extracellular traps (NETs) have emerged as a potential factor in MM progression, sparking investigation into their role in prognostication. Methods: In this study, a multi-gene risk scoring model was constructed using the intersection of NTEs and differentially expressed genes (DEGs), applying the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram was established, and the prognostic model's effectiveness was determined via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were employed to evaluate the level of immune infiltration. The sensitivity of chemotherapy drugs was assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Ultimately, the presence of the detected genes was confirmed through quantitative real-time polymerase chain reaction (qRT-PCR) analysis in MM cell specimens. Results: 64 NETs-DEGs were yielded, and through univariate Cox regression and LASSO regression analysis, we constructed a risk score composed of six genes: CTSG, HSPE1, LDHA, MPO, PINK1, and VCAM1. MM patients in three independent datasets were classified into high- and low-risk groups according to the risk score. The overall survival (OS) of patients in the high-risk group was significantly reduced compared to the low-risk group. Furthermore, the risk score was an independent predictive factor for OS. In addition, interactions between the risk score, immune score, and immune cell infiltration were investigated. Further analysis indicated that patients in the high-risk group were more sensitive to a variety of chemotherapy and targeted drugs, including bortezomib. Moreover, the six genes provided insights into the progression of plasma cell disorders. Conclusion: This study offers novel insights into the roles of NETs in prognostic prediction, immune status, and drug sensitivity in MM, serving as a valuable supplement and enhancement to existing grading systems.

DUSP4 enhances therapeutic sensitivity in HER2-positive breast cancer by inhibiting the G6PD pathway and ROS metabolism by interacting with ALDOB.

BACKGROUND: Breast cancer (BC) poses a global threat, with HER2-positive BC being a particularly hazardous subtype. Despite the promise shown by neoadjuvant therapy (NAT) in improving prognosis, resistance in HER2-positive BC persists despite emerging targeted therapies. The objective of this study is to identify markers that promote therapeutic sensitivity and unravel the underlying mechanisms. METHODS: We conducted an analysis of 86 HER2-positive BC biopsy samples pre-NAT using RNA-seq. Validation was carried out using TCGA, Kaplan‒Meier Plotter, and Oncomine databases. Phenotype verification utilized IC50 assays, and prognostic validation involved IHC on tissue microarrays. RNA-seq was performed on wild-type/DUSP4-KO cells, while RT‒qPCR assessed ROS pathway regulation. Mechanistic insights were obtained through IP and MS assays. RESULTS: Our findings reveal that DUSP4 enhances therapeutic efficacy in HER2-positive BC by inhibiting the ROS pathway. Elevated DUSP4 levels correlate with increased sensitivity to HER2-targeted therapies and improved clinical outcomes. DUSP4 independently predicts disease-free survival (DFS) and overall survival (OS) in HER2-positive BC. Moreover, DUSP4 hinders G6PD activity via ALDOB dephosphorylation, with a noteworthy association with heightened ROS levels. CONCLUSIONS: In summary, our study unveils a metabolic reprogramming paradigm in BC, highlighting DUSP4's role in enhancing therapeutic sensitivity in HER2-positive BC cells. DUSP4 interacts with ALDOB, inhibiting G6PD activity and the ROS pathway, establishing it as an independent prognostic predictor for HER2-positive BC patients.

Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma.

PURPOSE: Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients. METHODS: The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines. RESULTS: A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line. CONCLUSIONS: The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Vesicle-mediated transport-related genes predict the prognosis and immune microenvironment in hepatocellular carcinoma.

Background: Liver hepatocellular carcinoma (LIHC) is one of the leading causes of cancer-related death. The prognostic outcomes of advanced LIHC patients are poor. Hence, reliable prognostic biomarkers for LIHC are urgently needed. Methods: Data for vesicle-mediated transport-related genes (VMTRGs) were profiled from 338 LIHC and 50 normal tissue samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct and optimize the prognostic risk model. Five GEO datasets were used to validate the risk model. The roles of the differentially expressed genes (DEGs) were investigated via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Differences in immune cell infiltration between the high- and low-risk groups were evaluated using five algorithms. The "pRRophetic" was used to calculate the anticancer drug sensitivity of the two groups. Transwell and wound healing assays were performed to assess the role of GDP dissociation inhibitor 2 (GDI2) on LIHC cells. Results: A total of 166 prognosis-associated VMTRGs were identified, and VMTRGs-based risk model was constructed for the prognosis of LIHC patients. Four VMTRGs (GDI2, DYNC1LI1, KIF2C, and RAB32) constitute the principal components of the risk model associated with the clinical outcomes of LIHC. Tumor stage and risk score were extracted as the main prognostic indicators for LIHC patients. The VMTRGs-based risk model was significantly associated with immune responses and high expression of immune checkpoint molecules. High-risk patients were less sensitive to most chemotherapeutic drugs but benefited from immunotherapies. In vitro cellular assays revealed that GDI2 significantly promoted the growth and migration of LIHC cells. Conclusions: A VMTRGs-based risk model was constructed to predict the prognosis of LIHC patients effectively. This risk model was closely associated with the immune infiltration microenvironment. The four key VMTRGs are powerful prognostic biomarkers and therapeutic targets for LIHC.

Relationships Among Serological Indicators and In Vitro High-Throughput Drug Sensitivity Screening Results in Patients with Hepatocellular Carcinoma.

AIM: The purpose of this study was to analyze the relationship between serum indicators and high-throughput drug screening (HDS) results, aiming to achieve specific therapy for hepatocellular carcinoma (HCC). METHODS: This study recruited patients with HCC who underwent surgical resection at the Hepatobiliary Surgery Center of the First Affiliated Hospital of Chongqing Medical University from December 2019 to December 2021. HCC tissues were obtained from patients during surgery and subjected to in vitro cell culture, and then HDS testing was performed on the cultured tissue samples. We used Spearman's correlation analysis to examine the relationships between drug sensitivity results for anti-hepatocellular carcinoma drugs, other antitumor drugs, and serological indicators, the Neutrophil Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), Systemic Immune Inflammatory Index (SII), Systemic Inflammatory Response Index (SIRI), Prognostic Nutritional Index (PNI), and Lymphocyte Monocyte Ratio (LMR). A significant correlation was considered when P<0.05 and |r|>0.40. Furthermore, linear regression analysis was conducted to elucidate the relationship between serological indicators and drug susceptibility, with significant results indicated by P<0.05 and R²≥0.50. RESULTS: In this study, 82 patients with HCC who had undergone hepatectomy and completed in vitro cell culture and HDS testing were evaluated. Using Spearman's correlation with a significance threshold of P<0.05 and |r|>0.40, we identified significant associations between serological indicators and specific drug regimens: NLR correlated with 5-Fluorouracil, 5- Fluorouracil+Calcium folinate (FOLFOX4), and Capecitabine + Cisplatin (XP); PLR with FOLFOX4; SII with XP, FOLFOX4, Doxorubicin + Oxaliplatin (ADM+L-OHP); and SIRI with XP and FOLFOX4. No correlations were found between PNI or LMR and any drug inhibition rates. A comprehensive evaluation using linear regression analysis-which included variables such as sex, age, hepatitis B virus and liver cirrhosis status, size and number of lesions, alphafetoprotein, total bilirubin, albumin, alanine aminotransferase, aspartate aminotransferase, and prothrombin time, alongside NLR, PLR, SII, and SIRI was conducted in relation to drug regimens. This analysis revealed that NLR, SII, and SIRI are significant predictors of FOLFOX4 inhibition rate, while NLR predicts the inhibition rate of XP effectively. However, no significant links were established between molecular targeted drugs, other antitumor drugs, and serological indicators. CONCLUSIONS: NLR, SII, and SIRI were correlated with FOLFOX4, and the higher the values of NLR, SII, and SIRI, the higher the in vitro inhibition of FOLFOX. Also, NLR was correlated with XP, and the higher the value of NLR, the higher the in vitro inhibition of XP.

Patient tissue-derived FGFR4-variant and wild-type colorectal cancer organoid development and anticancer drug sensitivity testing.

Objectives: FGFR4-variant and wild-type colorectal cancer (CRC) organoids were developed to investigate the effects of FGFR4-targeted drugs, including FGFR4-IN and erdafitinib, on CRC and their possible molecular mechanism. Methods: Clinical CRC tissues were collected, seven CRC organoids were developed, and whole exome sequencing (WES) was performed. CRC organoids were cultured and organoid drug sensitivity studies were conducted. Finally, an FGFR4-variant (no wild-type) CRC patient-derived orthotopic xenograft mouse model was developed. Western blot measured ERK/AKT/STAT3 pathway-related protein levels. Results: WES results revealed the presence of FGFR4-variants in 5 of the 7 CRC organoids. The structural organization and integrity of organoids were significantly altered under the influence of targeted drugs (FGFR4-IN-1 and erdafitinib). The effects of FGFR4 targeted drugs were not selective for FGFR4 genotypes. FGFR4-IN-1 and erdafitinib significantly reduced the growth, diameter, and Adenosine Triphosphate (ATP) activity of organoids. Furthermore, chemotherapeutic drugs, including 5-fluorouracil and cisplatin, inhibited FGFR4-variant and wild-type CRC organoid activity. Moreover, the tumor volume of mice was significantly reduced at week 6, and p-ERK1/2, p-AKT, and p-STAT3 levels were down-regulated following FGFR4-IN-1 and erdafitinib treatment. Conclusions: FGFR4-targeted and chemotherapeutic drugs inhibited the activity of FGFR4-variant and wild-type CRC organoids, and targeted drugs were more effective than chemotherapeutic drugs at the same concentration. Additionally, FGFR4 inhibitors hindered tumorigenesis in FGFR4-variant CRC organoids through ERK1/2, AKT, and STAT3 pathways. However, no wild-type control was tested in this experiment, which need further confirmation in the next study.

Pan-cancer analysis of the TRAF family genes and their correlation with prognosis, TME, immune and drug sensitivity.

BACKGROUND: Tumor necrosis factor receptor-associated factors family genes play a pivotal role in tumorigenesis and metastasis, functioning as adapters or E3 ubiquitin ligases across various signaling pathways. To date, limited research has explored the association between tumor necrosis factor receptor-associated factors family genes and the clinicopathological characteristics of tumors, immunity, and the tumor microenvironment (TME). This comprehensive study investigates the relationship between tumor necrosis factor receptor-associated factors family and prognosis, TME, immune response, and drug sensitivity in a pan-cancer context. METHODS: Utilizing current public databases, this study examines the expression levels and prognostic significance of tumor necrosis factor receptor-associated factors family genes in a pan-cancer context through bioinformatic analysis. In addition, it investigates the correlation between tumor necrosis factor receptor-associated factors expression and various factors, including the TME, immune subtypes, stemness scores, and drug sensitivity in pan-cancer. RESULTS: Elevated expression levels of tumor necrosis factor receptor-associated factor 2, 3, 4, and 7 were observed across various cancer types. Patients exhibiting high expression of these genes generally faced a worse prognosis. Furthermore, a significant correlation was noted between the expression of tumor necrosis factor receptor-associated factors family genes and multiple dimensions of the TME, immune subtypes, and drug sensitivity.

Improving the diagnosis of tuberculosis: old and new laboratory tools.

INTRODUCTION: Despite recent advances in diagnostic technologies and new drugs becoming available, tuberculosis (TB) remains a major global health burden. If detected early, screened for drug resistance, and fully treated, TB could be easily controlled. AREAS COVERED: Here the authors discuss M. tuberculosis culture methods which are considered the definitive confirmation of M. tuberculosis infection, and limited advances made to build on these core elements of TB laboratory diagnosis. Literature searches showed that molecular techniques provide enhanced speed of turnaround, sensitivity, and richness of data. Sequencing of the whole genome, is becoming well established for identification and inference of drug resistance. PubMed® literature searches were conducted (November 2022-March 2024). EXPERT OPINION: This section highlights future advances in diagnosis and infection control. Prevention of prolonged hospital admissions and rapid TAT are of the most benefit to the overall patient experience. Host transcriptional blood markers have been used in treatment monitoring studies and, with appropriate evaluation, could be rolled out in a diagnostic setting. Additionally, the MBLA is being incorporated into latest clinical trial designs. Whole genome sequencing has enhanced epidemiological evidence. Artificial intelligence, along with machine learning, have the ability to revolutionize TB diagnosis and susceptibility testing within the next decade.

A versatile dilution-treatment-detection microfluidic chip platform for rapid In vitro lung cancer drug combination sensitivity evaluation.

Combination drug therapy represents an effective strategy for treating certain drug-resistant and intractable cancer cases. However, determining the optimal combination of drugs and dosages is challenging due to clonal diversity in patients' tumors and the lack of rapid drug sensitivity evaluation methods. Microfluidic technology offers promising solutions to this issue. In this study, we propose a versatile microfluidic chip platform capable of integrating all processes, including dilution, treatment, and detection, for in vitro drug sensitivity assays. This platform innovatively incorporates several modules, including automated discrete drug logarithmic concentration generation, on-chip cell perfusion culture, and parallel drug treatments of cancer cell models. Moreover, it is compatible with microplate readers or high-content imaging systems for swift detection and automated monitoring, simplifying on-chip drug evaluation. Proof of concept is demonstrated by assessing the in vitro potency of two drugs, cisplatin, and etoposide, against the lung adenocarcinoma A549 cell line, under both single-drug and combination treatment conditions. The findings reveal that, compared to conventional microplate approaches with static cultivation, this on-chip automated perfusion bioassays yield comparable IC50 values with lower variation and a 50 % reduction in drug preparation time. This versatile dilution-treatment-detection microfluidic platform offers a promising tool for rapid and precise drug assessments, facilitating in vitro drug sensitivity evaluation in personalized cancer chemotherapy.

The Pattern of Bacterial Infections Among Chronic Suppurative Otitis Media Cases at a Tertiary Care Centre in North-East India.

BACKGROUND AND OBJECTIVES: Chronic suppurative otitis media (CSOM) is a chronic inflammation of the mucoperiosteal lining of the middle ear cleft, presenting with recurrent ear discharge through a tympanic membrane perforation. The present study aims to assess the spectrum of bacterial infection among CSOM cases and detect the isolated organism's antibiotic sensitivity pattern. METHODS: The prospective hospital-based observational study was conducted from June 2021 to June 2022 and included 94 CSOM cases. An aural swab of the ear discharge was collected from each patient under aseptic precautions. The swab was utilized for Gram's staining and the aerobic bacterial pathogen culture. The organisms isolated were tested for antibiotic sensitivity using the Kirby-Bauer disc diffusion method. RESULTS: The most affected age group was the second decade of life (27.7%, n=26), with a male-to-female ratio of 1.35:1. The mean duration of ear discharge was 24.0±14.7 months, mostly mucoid ear discharge (39.4%, n=37). Among gram-positive bacteria, methicillin-resistant Staphylococcus aureus was isolated in 16 (17.0%) cases. Pseudomonas aeruginosa was the most isolated gram-negative bacteria strain in 26 (27.7%) cases. Cotrimoxazole (67.7%, n=21) had the highest sensitivity towards gram-positive bacteria isolates. Amongst gram-negative bacteria, amikacin and ciprofloxacin were the most sensitive, with 78.0% (n=39) susceptibility. CONCLUSION: Evaluating the spectrum of infecting organisms of CSOM and their antibiotic sensitivity may help initiate prompt treatment with the appropriate antibiotic regimen, thereby preventing future complications.

Perinatal group A streptococcal infection in vagina and its impact on pregnancy outcomes.

OBJECTIVE: To investigate the prevalence, antimicrobial susceptibility, and the effects on pregnancy and neonatal outcomes of Group A Streptococcal (GAS) infections in the vagina of perinatal women. METHODS: From June 2020 to October 2022, 270 perinatal pregnant women underwent vaginal swabs for GAS culture. The antibiotic sensitivity of the positive strains was assessed. Based on GAS detection results, the patients were divided into an observation group (GAS positive) and a control group (GAS negative). Clinical data from both groups were collected to compare the vaginal microecological changes. The adverse outcomes for pregnancy and infants in both groups were retrospectively analyzed. Univariate and multivariate analyses were used to identify the risk factors for adverse outcomes. RESULTS: Among the 270 pregnant women, 30 tested positive for GAS and 240 tested negative, with a colonization rate of 11.1%. No resistance to penicillin, ampicillin, linezolid, vancomycin, or tigecycline was found among the GAS strains. The resistance rates to tetracycline and clindamycin were 73.3% and 70.0%, respectively. Higher vaginal pH (≥4.5), and increased incidences of bacterial vaginitis, aerobic vaginitis, and microecological imbalances were observed in the observation group compared to the control group (all P<0.05). The observation group also experienced more adverse pregnancy and infant outcomes, such as chorioamnionitis, postpartum infections, fetal distress, and neonatal pneumonia (all P<0.05). Univariate and multivariate analyses indicated that a vaginal pH≥4.5 and microecological imbalance were positively associated with poor maternal and infant outcomes in women with GAS infections (all P<0.05). CONCLUSIONS: The study found no ß-lactam resistant GAS strains. Additionally, a higher vaginal pH (≥4.5) and microecological imbalance were linked to an increased risk of adverse pregnancy and infant outcomes in women with GAS infections.

To explore the prognostic characteristics of colon cancer based on tertiary lymphoid structure-related genes and reveal the characteristics of tumor microenvironment and drug prediction.

In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive system. At present, there is no effective prognostic marker to predict the prognosis of patients. Tertiary lymphoid structure (TLS) affects cancer progression by regulating immune microenvironment. Mining COAD biomarkers based on TLS-related genes helps to improve the prognosis of patients. In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. The mRNA expression data and clinical information of COAD and adjacent tissues were downloaded from the Cancer Genome Atlas database. The differentially expressed TLS-related genes of COAD relative to adjacent tissues were obtained by differential analysis. TLS gene co-expression analysis was used to mine genes highly related to TLS, and the intersection of the two was used to obtain candidate genes. Univariate, LASSO, and multivariate Cox regression analysis were performed on candidate genes to screen prognostic markers to construct a risk assessment model. The differences of immune characteristics were evaluated by ESTIMATE, ssGSEA and CIBERSORT in high and low risk groups of prognostic model. The difference of genomic mutation between groups was evaluated by tumor mutation burden score. Screening small molecule drugs through the GDSC library. Finally, a nomogram was drawn to evaluate the clinical value of the prognostic model. Seven TLS-related genes ADAM8, SLC6A1, PAXX, RIMKLB, PTH1R, CD1B, and MMP10 were screened to construct a prognostic model. Survival analysis showed that patients in the high-risk group had significantly lower overall survival rates. Immune microenvironment analysis showed that patients in the high-risk group had higher immune indicators, indicating higher immunity. The genomic mutation patterns of the high-risk and low-risk groups were significantly different, especially the KRAS mutation frequency was significantly higher in the high-risk group. Drug sensitivity analysis showed that the low-risk group was more sensitive to Erlotinib, Savolitinib and VE _ 822, which may be used as a potential drug for COAD treatment. Finally, the nomogram constructed by pathological features combined with RiskScore can accurately evaluate the prognosis of COAD patients. This study constructed and verified a TLS model that can predict COAD. More importantly, it provides a reference standard for guiding the prognosis and immunotherapy of COAD patients.