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Genomic data have demonstrated strong clinical impact, enabling rational therapeutic design and improving outcomes for oncogene-addicted disease. By contrast, proteomics, transcriptomics, epigenetics, metabolomics, and microbiomics show comparatively limited clinical translation. Multiomic profiling may shift this, supporting precision oncology and improved care for non–oncogene-addicted NSCLC. The review summarizes current multiomic research, discusses spatial-omic and integrated approaches, outlines biomarkers and drug targets, and highlights challenges and unmet needs.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/current-insights-and-future-directions-of-multiomic-and-spatial-omic-analysis-in-non-small-cell-lung-cancer-review-article/358743/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/current-insights-and-future-directions-of-multiomic-and-spatial-omic-analysis-in-non-small-cell-lung-cancer-review-article/358743.png","ImageObject",300,407,{"name":92,"@type":93},"Asher","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23",true,{"@type":101,"interactionType":102,"userInteractionCount":14},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What clinical gap does the review highlight for non–oncogene-addicted NSCLC?","Question",{"text":111,"@type":112},"Only genomics has significantly affected NSCLC clinical care. 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Krebs, MD, PhD1,2  DOI [https://doi.org/10.1200/PO-25-00684](https://doi.org/10.1200/PO-25-00684)  \nABSTRACT  \nAdvancements in profiling technologies have deepened our understanding of cancer biology, particularly in non–small cell lung cancer (NSCLC) . Genomic data have demonstrated profound clinical impact, enabling the rational design of therapeutics and achieving excellent clinical outcomes for patients with oncogene-addicted disease. While proteomics, transcriptomics, epigenetics, metabolomics, and microbiomics have also generated a wealth of data in NSCLC, their clinical impact is comparatively limited. The increasing use of multiomic profiling has the capacity to change this paradigm, offering new opportunities for improving patient care, particularly for those with non–oncogene-addicted (NOA) NSCLC. This review will summarize the current landscape of multiomic research in NSCLC, emphasizing the potential role in precision oncology. Each omic field is discussed in turn, describing potential clinical applications and challenges of each. In addition, the developing fields of spatial-omic and integrated multiomics, which are becoming increasingly important in understanding cancer biology, are discussed. NSCLC samples have been extensively profiled across different omic technologies, revealing a range of biomarkers associated with prognosis or response to therapy and potential drug targets, many of which are being investigated. While the patient groups analyzed differ between studies, most are performed on early-stage resection samples, and many studies do not stratify results by genomic status, limiting our understanding of NOA-NSCLC. In addition, while many studies independently analyze several omics, fewer use multiomic integration algorithms. Despite significant research into spatial-omic and multiomics in NSCLC, only genomics has significantly affected NSCLC clinical care, leaving an unmet need in NOA-NSCLC. However, nongenomic technologies have significant potential for precision oncology, particularly when used alongside multiomic integration to discover biomarkers or to identify future precision medicine targets.  \nAccepted January 8, 2026 Published February 19, 2026  \nJCO Precis Oncol 10:e2500684 © 2026 by American Society of Clinical Oncology  \nCreative Commons Attribution Non-Commercial No Derivatives 4.0 License  \nINTRODUCTION  \nLung cancer is the leading cause of cancer mortality.1 Non– small cell lung cancer (NSCLC) represents approximately 85% of lung cancers; 20%-25% are squamous cell lung cancer (LUSC), and most nonsquamous cases are adenocarcinoma (LUAD; approximately 40%) .2 The majority of NSCLCs are diagnosed at the advanced stage, with poor prognostic implications.3 While cytotoxic chemotherapy and immune checkpoint inhibitors (ICIs) have shown efficacy across disease stages, remarkable benefits have come from the use of precision medicine agents directed at somatic genomic alterations.4,5  \nNon-DNA profiling technologies analyzing the proteomic, transcriptomic, epigenetic, metabolomic, and microbiomic landscape in NSCLC have seen significant advancements.6 Furthermore, spatially separate regions of tumors can now be sequenced in situ, through microdissection, or via singlecell sequencing.7,8 Despite this, nongenomic profiling is yet  \nto yield significant clinical impact. Given the highly intertwined nature of biology, a multiomic integration approach may be required to truly appreciate the clinical relevance of these omics.9 While several challenges impair this strategy, sophisticated algorithms may aid such analysis.10 This review will explore the current status of omic profiling in NSCLC and assess the potential of spatial-omic and multiomics, independently or through integration, to identify biomarkers and a","cbCaigiaWMGeUKpG","https://ap.wps.com/l/cbCaigiaWMGeUKpG","pdf",3519991,16,"English","# Abstract\n# Introduction\n# Oncogene-Addicted NSCLC and Non–Oncogene-Addicted NSCLC\n# Transcriptomic Analysis in NSCLC","[{\"question\":\"What clinical gap does the review highlight for non–oncogene-addicted NSCLC?\",\"answer\":\"Only genomics has significantly affected NSCLC clinical care. Non-genomic approaches have notable potential, but remain insufficiently translated, creating an unmet need for improved biomarker discovery and precision medicine targets in non–oncogene-addicted NSCLC.\"},{\"question\":\"How do multiomic approaches differ from single-omic studies in NSCLC?\",\"answer\":\"The review notes that many studies analyze multiple omics independently, while fewer use multiomic integration algorithms. Integration is presented as important for capturing the intertwined nature of biology and improving clinical relevance.\"},{\"question\":\"What does transcriptomic analysis enable in NSCLC?\",\"answer\":\"Transcriptomic analysis can evaluate differentially expressed genes, identify molecular subtypes, and detect novel gene fusion events. It supports selection of precision therapies and the design of RNA-based therapeutics.\"}]","Current Insights and Future Directions of Multiomic and Spatial-Omic Analysis in Non-Small Cell Lung Cancer - Review Article | PDF",1790135151]