7082 results for "canc*"

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• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from a cetuximab-sensitive patient-derived xenograft (PDX) model. The objective of this analysis was to investigate, at single-cell resolution, the transcriptional changes previously identified in bulk RNA-seq analyses of PDX models exposed to anti-EGFR therapeutic pressure.

  Study EGAS50000001460

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Tumor implantation and expansion were performed in two 6-week-old NOD/SCID mice. Once tumors reached an average volume of approximately 700 mm³, mice were randomly assigned to one of two treatment arms: vehicle (physiological saline, intraperitoneally, twice weekly) or cetuximab (20 mg/kg, intraperitoneally, twice weekly). After 1 week of treatment, mice were sacrificed, and tumors were harvested and preserved in sCelLiVE® Buffer for downstream single-cell RNA sequencing analysis.

  Dataset EGAD50000002103

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Organoids were seeded in 12-well plates at a density of 5 × 10⁴ cells per well, embedded in 200 µL of Matrigel diluted 1:1 with culture medium, and maintained under EGF-deprived conditions. After four days of growth, organoids were either left untreated or treated with cetuximab (20 µg/mL). Following 72 hours of treatment, organoids were harvested, dissociated, and live single cells were sorted for single-cell RNA sequencing using the 10x Genomics platform.

  Dataset EGAD50000002104

• RNAseq for 208 patients with medulloblastoma cancer (MB_COMICS cohort)

  This dataset contains 208 paired fastq files sequenced with Illumina HiSeq 2500.

  Dataset EGAD50000000600

• Berlin Neuroblastoma Dataset

  Study EGAS00001004022

• Sequence data to study genomic CNVs that drive apoptotic resistance and relapses on immune checkpoint inhibitors

  This project investigates the genomic mechanisms underlying acquired resistance to immune checkpoint inhibitors (ICIs) across tumor types, addressing the critical clinical problem of treatment relapses where the molecular basis remains poorly understood. Through integrative genomic analyses of longitudinal clinical melanomas, functional CRISPR-Cas9 screens, and human and murine melanoma models, the study demonstrates that copy-number variant (CNV)-driven subclonal evolution is a primary driver of clinical relapses. The research identifies resistance-driver genes targeted by CNVs, including pro-apoptotic gene deletions and anti-apoptotic gene amplifications, which collectively downregulate apoptotic priming in resistant cells. The findings establish that modulating the apoptotic threshold can prevent or reverse ICI resistance, positioning CNV evolution as a key driver of acquired resistance and identifying apoptotic regulation as a therapeutic target to combat resistance evolution.

  Study EGAS50000001055

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Development and validation of multivariate predictors of primary endocrine resistance to tamoxifen and aromatase inhibitors in luminal breast cancer reveal drug-specific differences

  Background: Endocrine therapy is highly effective in blocking the estrogen receptor pathway in HR+/HER2- early breast cancer (EBC). However, up to 40% of patients experience relapse during or after adjuvant endocrine therapy. Here, we investigate molecular mechanisms associated with primary resistance to endocrine therapy and develop predictive models. Results: TP53 mutations were prominently associated with primary resistance to both tamoxifen (TAM) and aromatase inhibitors (AI), with AI non-responders exhibiting resistance in up to 32% of cases. Additionally, we identified distinct DNA methylation patterns in TAM and AI non-responders, with TAM non-responders showing global DNA methylation loss, associated with KRAS signaling, apical junctions and epithelial-mesenchymal transition (EMT). Conversely, we observed methylation gain in AI non-responders affecting developmental transcription factors, hypoxia and estrogen signaling. TAM or AI resistance was associated with increased methylation-inferred proportions of immune cells and decreased proportions of endothelial cells. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI stratified NR and R cases in both treatment groups and cohorts with high accuracy (ROC AUC TAM discovery 93.9%, validation 83%; AI discovery 98.6%, validation 76.9%). A simplified PERCI efficiently predicted progression-free survival in the TCGA-BRCA sub-cohort (Kaplan-Meier log-rank p-value = 0.03 between low and high PERCI groups). Conclusions: We identified genomic and epigenomic features associated with primary resistance to TMA and AI. By combining information on genomic alterations, patient age, differential methylation and tumor microenvironment (TME) composition, we developed PERCI TAM and PERCI AI as novel predictors of primary resistance, with potential additional prognostic value. Applying PERCI in a clinical setting may allow patient-specific drug selection to overcome resistance.

  Study EGAS50000001102

• Whole exome sequencing of patients with esophageal squamous cell carcinoma receiving chemoradiotherapy

  We performed multi-region whole exome sequencing (WES) of pre-treatment and recurrent esophageal cancer receiving chemoradiotherapy in order to characterize clonal evolution of treatment resistant clones. Furthermore, additional solitary pre-treatment tumor samples were subjected to WES to detect biomarkers predicting clinical outcome.

  Study JGAS000227

• Genome sequencing of biliary tract cancers

  Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous with poor response to treatments. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed genome sequencing analyses for a large scale samples of BTCs to investigate their somatic and germline driver events and characterize their genomic landscape.

  Study JGAS000109

• A study on personalized medicine in genitourinary cancers using genetic biomarkers

  We present a patient with MSI-high castration-resistant PC who showed a remarkable and durable response to pembrolizumab. Whole exome sequencing revealed approximate tumor mutation burden of 61 mutations/Mb as well as biallelic loss of MSH2.

  Study JGAS000510

• Research for biological features by gene expression analysis and biomarkers at diagnosis/therapeutics in lung cancer

  WGS, WES, ATAC-seq and methylation analysis with DNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients. RNA-seq analysis with RNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients.

  Study JGAS000610

• Whole genome sequence analysis in patients with primary central nervous system lymphomas

  We performed target amplicon sequencing analysis in 28 patients with primary central nervous system lymphomas using target capture technology (NGS) on Cancer Panel to explore molecular targets.

  Study JGAS000258

• Phylogenetic analysis of combined lobular and ductal carcinoma of the breast

  Breast cancer manifests in diverse forms, with particular reference to various cell types harboring different mutations and gene expression profiles. To elucidate the clonal relationship between cancer cells in tumors composed of both ductal and lobular phenotypes, we analyzed two combined lobular and ductal carcinoma (CLDC) cases, including one mixed ductal-lobular carcinoma (MDL) lesion, by next generation sequencing.

  Study JGAS000300

• Common and rare germline variants in Japanese prostate cancer patients

  Study JGAS000487

• Identification of genetic mutations characteristic for recurrence and metastasis of lymphoma.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent B cell lymphoma, and the purpose of this study is to find the characteristics of recurrent B cell lymphoma by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000087

• Target sequencing of ROS1-rearranged lung cancer patients

  We performed target capture sequencing of ROS1-rearranged non-small cell lung cancer patients to develop and examine the efficacy of new molecular targeted drug against ROS1 tyrosine kinase.

  Study JGAS000189

• exploration of biomarkers discriminating squamous cell carcinoma from other lung cancers

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we initially performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). We furhter expanded the transcriptome profiling to cover additional 48 malignant neoplasm of bronchus and lung, including mesothelioma and metastatic lung cancers derived from other tissues.

  Study JGAS000488

• Exploration of predictive biomarkers for postoperative recurrence of stage II/III colorectal cancer using genomic sequencing

  To identify biomarkers that can predict treatment outcomes, we compared the mutational profiles of surgically resected specimens from patients with recurrent cancer with those from patients with non-recurrent cancer. Target sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS) was perfomed.

  Study JGAS000335

• Prediction of response to preoperative chemoradiotherapy in rectal cancer based on whole-exome sequencing and transcriptomic analysis

  Accumulating evidence suggests that radiotherapeutic success has an immune-associated component. We aimed to investigate the immunogenomic profiles associated with response to preoperative chemoradiotherapy (CRT) in patients with locally advanced rectal cancer.

  Study JGAS000158

• Identification of biomarkers for prediction of efficacy of microtubule inhibitors and antifolates in non-small cell lung cancer

  Identification of predictive markers based on transcriptome modules for microtubule inhibitors of lung adenocarcinoma patients

  Study JGAS000267

• Hi-C analysis of patient-derived pancreas neoplasm organoids

  Pancreatic cancers arise from two different precursors; intraductal papillary mucinous neoplasms (IPMN) and pancreatic intraepithelial neoplasm (PanIN), while biological differences in cancers originated from thme remain obscure. Here, we analyzed their three-dimensional genome structure by Hi-C using patient-derived organoids.

  Study JGAS000262

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000303

• Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000346

• Proteogenomic discovery of a novel class of cancer antigens by HLA ligandome analysis of colon cancer tissues

  CD8+ T cells recognize peptides displayed by HLA class I molecules on cell surfaces, monitoring pathological conditions such as cancer. Recent advances in proteogenomic analysis of HLA ligandomes have demonstrated that cells present a subset of cryptic peptides derived from non-coding regions of the genome; however, the roles of cryptic HLA ligands in tumor immunity remain unknown. In the present study, we comprehensively and quantitatively investigated the HLA class I ligandome of a set of human colorectal cancer (CRC) and matched normal tissues, showing that cryptic translation products account for a small fraction of the HLA class I ligandome and serve as antigens for patient T cell surveillance against colon cancer.

  Study JGAS000280