Defining spatial molecular residual disease by personalized tumor tissue profiling
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PROVIDER: PRJNA1253787 | ENA |
REPOSITORIES: ENA
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Project description:Defining spatial molecular residual disease by personalized tumor tissue profiling
| PRJNA1253786 | ENA
Project description:Minimal residual disease (MRD) status in multiple myeloma (MM) is an important prognostic biomarker. Personalized blood-based targeted mass spectrometry (MS-MRD) detecting M-proteins was shown to provide a sensitive and minimally invasive alternative to MRD assessment in bone marrow. However, MS-MRD still comprises manual steps that hamper upscaling of sample size. Here, we introduce a proof-of-concept for a novel workflow using dia-PASEF technology and automated data processing.Using automated data processing of PASEF DDA and dia-PASEF measurements, we developed a workflow that identified unique targets from MM patient sera and personalized protein sequence databases. We generated patient-specific libraries linked to dia-PASEF methods and subsequently quantitated and reported M-protein concentrations in follow-up samples from MM patients. Assay performance of prm-PASEF and dia-PASEF workflows were compared and we tested mixing patient intake sera for multiplexed target identification and selection.
2025-06-10 | PXD050329 | Pride
Project description:Spatial organization, chromatin accessibility and gene-regulatory programs defining sensory neurons
| PRJNA1213725 | ENA
Project description:<p>Tumor relapse from treatment-resistant cells (minimal residual disease, MRD) underlies most breast cancer related deaths. Yet, the molecular characteristics defining their malignancy have largely remained elusive. Here we integrated multi-omics data from a tractable organoid system with a metabolic modelling approach to uncover the metabolic and regulatory idiosyncrasies of the MRD. We find that the resistant cells, despite their non-proliferative phenotype and the absence of oncogenic signaling, feature increased glycolysis and activity of certain urea cycle enzymes reminiscent of the tumor. This metabolic distinctiveness was also evident in a mouse model and in transcriptomic data from patients following neo-adjuvant therapy. We further identified a marked similarity in DNA methylation profiles between tumor and residual cells. Taken together, our data reveal a metabolic and epigenetic memory of the treatment-resistant cells. We further demonstrate that the memorized elevated glycolysis in MRD is crucial for their survival and can be targeted using a small molecule inhibitor without impacting normal cells. The metabolic aberrances of MRD thus offer new therapeutic opportunities for post-treatment care to prevent breast tumor recurrence.</p>
2021-09-14 | MTBLS1507 | MetaboLights
Project description:IntroductionLaser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.Areas coveredWe summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.Expert opinionLCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.
| S-EPMC10720974 | biostudies-literature
Project description:Our study utilized spatial transcriptomics (ST) to interpret the tumor microenvironment to examine spatial characteristics across different sites in eight patients with HGSOC divided into recurrent (R, n = 5) and non-recurrent (NR, n = 3) groups based on a 60-month recurrence criterion. This study identified diagnostic and therapeutic targets for HGSOC, marking a step towards personalized medicine.
2024-04-18 | GSE263920 | GEO
Project description:Recent breakthroughs in spatial transcriptomics technologies have enhanced our understanding of diverse cellular identities, spatial organizations, and functions. Yet existing spatial transcriptomics tools are still limited in either transcriptomic coverage or spatial resolution, hindering unbiased, hypothesis-free transcriptomic analyses at high spatial resolution. Here we develop Reverse-padlock Amplicon Encoding FISH (RAEFISH), an image-based spatial transcriptomics method with whole-genome coverage and single-molecule resolution in intact tissues. We demonstrate spatial profiling of 23,000 human or 22,000 mouse transcripts in single cells and tissue sections. Our analyses reveal transcript-specific subcellular localization, cell-type-specific and cell-type-invariant zonation-dependent transcriptomes, and gene programs underlying preferential cell-cell interactions. Finally, we further develop our technology for direct spatial readout of gRNAs in an image-based high-content CRISPR screen. Overall, these developments provide the research community with a broadly applicable technology that enables high-coverage, high-resolution spatial profiling of both long and short, native and engineered RNA species in many biomedical contexts.
2025-07-22 | GSE302564 | GEO
Project description:Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about the spatial intratumor heterogeneity (ITH) and the temporal clonal evolutionary processes in this cancer. Interestingly, the epigenetic profiling also showed strong evidence of spatial ITH, and the phyloepigenetic trees were extremely similar with the phylogenetic ones, indicating the interplay and co-dependency of genetic and epigenetic alterations in ESCC. We found that several genes were both mutated and hypermethylated at their promoters, such as ASXL1 and EPHA7. Our integrated investigations of the spatial ITH and the temporal clonal evolution might provide insights into developing biomarkers for early diagnosis of ESCC, as well as personalized therapeutic targets for treating this malignancy. DNA methylation profiles of 12 tumor regions and 2 matched normal esophageal epithelial tissues from three M-WES-examined ESCC cases (ESCC01, ESCC03 and ESCC05) were performed using Illumina Infinium HumanMethylation450K platform (Illumina, San Diego, CA) at the Epigenome Center of University of Southern California.
2016-08-20 | E-GEOD-79366 | biostudies-arrayexpress
Project description:Targeted therapy is effective in many tumor types including lung cancer, the leading cause of cancer mortality. Paradigm defining examples are targeted therapies directed against non-small cell lung cancer (NSCLC) subtypes with oncogenic alterations in EGFR, ALK and KRAS. The success of targeted therapy is limited by drug-tolerant persister cells (DTPs) which withstand and adapt to treatment and comprise the residual disease state that is typical during treatment with clinical targeted therapies. Here, we integrate studies in patient-derived and immunocompetent lung cancer models and clinical specimens obtained from patients on targeted therapy to uncover a focal adhesion kinase (FAK)-YAP signaling axis that promotes residual disease during oncogenic EGFR-, ALK-, and KRAS-targeted therapies. FAK-YAP signaling inhibition combined with the primary targeted therapy suppressed residual drug-tolerant cells and enhanced tumor responses. This study unveils a FAK-YAP signaling module that promotes residual disease in lung cancer and mechanism-based therapeutic strategies to improve tumor response.
2024-02-20 | GSE255958 | GEO
Project description:Targeted therapy is effective in many tumor types including lung cancer, the leading cause of cancer mortality. Paradigm defining examples are targeted therapies directed against non-small cell lung cancer (NSCLC) subtypes with oncogenic alterations in EGFR, ALK and KRAS. The success of targeted therapy is limited by drug-tolerant persister cells (DTPs) which withstand and adapt to treatment and comprise the residual disease state that is typical during treatment with clinical targeted therapies. Here, we integrate studies in patient-derived and immunocompetent lung cancer models and clinical specimens obtained from patients on targeted therapy to uncover a focal adhesion kinase (FAK)-YAP signaling axis that promotes residual disease during oncogenic EGFR-, ALK-, and KRAS-targeted therapies. FAK-YAP signaling inhibition combined with the primary targeted therapy suppressed residual drug-tolerant cells and enhanced tumor responses. This study unveils a FAK-YAP signaling module that promotes residual disease in lung cancer and mechanism-based therapeutic strategies to improve tumor response.
2024-02-29 | GSE260499 | GEO