 
                Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance
            Oncology, Nuclear Medicine and Transplantology, 1(2),  2025, onmt007, https://doi.org/10.63946/onmt/17300
        
        
                    
                    Publication date: Oct 18, 2025
                
        ABSTRACT
Spatial tumour heterogeneity, which denotes the changes in cellular and molecular attributes across distinct locations within a tumour, significantly influences cancer diagnosis and treatment resistance. The heterogeneity of tumour cells inside a singular mass facilitates tumour development, metastasis, and the ineffectiveness of standard therapy. Comprehending the geographical distribution of tumour cells is crucial for formulating more efficient treatment regimens. Diverse methodologies are employed to investigate spatial heterogeneity, encompassing modern imaging techniques such as MRI, PET, and multiplexed imaging, alongside omics approaches including genomes, transcriptomics, and proteomics. These instruments offer insights into the tumour microenvironment and facilitate the identification of resistant subpopulations. The amalgamation of imaging and genomic data via radiogenomics has emerged as a viable methodology, providing an extensive perspective on the spatial and molecular intricacies of tumours. Principal findings reveal that spatial heterogeneity fosters medication resistance by establishing microenvironments characterised by varying oxygen levels, immunological infiltration, and genetic alterations, hence complicating the efficacy of monotherapy strategies. Hypoxic environments and immunological evasion significantly contribute to treatment resistance. Addressing geographical heterogeneity has the potential to enhance cancer treatments. By analysing the molecular and geographical characteristics of tumours, physicians can customise therapies more efficiently, minimising resistance and improving therapeutic results. This methodology signifies a vital advancement in precision medicine, providing more individualised and efficacious cancer therapies in the future.        
        KEYWORDS
Spatial Tumor Heterogeneity Cancer Resistance Imaging Techniques Radiogenomics Drug Resistance Precision Medicine Tumor Microenvironment Hypoxia Immune Evasion Multiplexed Imaging Genomics Proteomics        
        CITATION (Vancouver)
            Taylor KE, Jacob H, Oladosu TA, Nwajiugo GK, Adigun MV, Nzunde MS, et al. Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance. Oncology, Nuclear Medicine and Transplantology. 2025;1(2):onmt007. https://doi.org/10.63946/onmt/17300
        
        APA
                        
                            Taylor, K. E., Jacob, H., Oladosu, T. A., Nwajiugo, G. K., Adigun, M. V., Nzunde, M. S., & Ugo, C. H. (2025). Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance. Oncology, Nuclear Medicine and Transplantology, 1(2), onmt007. https://doi.org/10.63946/onmt/17300
                        
                        Harvard
                        
                            Taylor, K. E., Jacob, H., Oladosu, T. A., Nwajiugo, G. K., Adigun, M. V., Nzunde, M. S., and Ugo, C. H. (2025). Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance. Oncology, Nuclear Medicine and Transplantology, 1(2), onmt007. https://doi.org/10.63946/onmt/17300
                        
                        AMA
                        
                            Taylor KE, Jacob H, Oladosu TA, et al. Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance. Oncology, Nuclear Medicine and Transplantology. 2025;1(2), onmt007. https://doi.org/10.63946/onmt/17300
                        
                        Chicago
                        
                            Taylor, Kwesi Egyin, Hycent Jacob, Tosin Ayodeji Oladosu, Godwin Kenechukwu Nwajiugo, Motunrayo Victoria Adigun, Markus Saerimam Nzunde, and Chinemerem Henry Ugo. "Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance". Oncology, Nuclear Medicine and Transplantology 2025 1 no. 2 (2025): onmt007. https://doi.org/10.63946/onmt/17300
                        
                        MLA
                        
                            Taylor, Kwesi Egyin et al. "Spatial Tumor Heterogeneity: The Next Frontier in Understanding Cancer Resistance". Oncology, Nuclear Medicine and Transplantology, vol. 1, no. 2, 2025, onmt007. https://doi.org/10.63946/onmt/17300
                        
                REFERENCES
- MacDonald WJ, Purcell C, Pinho-Schwermann M, Stubbs NM, Srinivasan PR, El-Deiry WS. Heterogeneity in Cancer. Cancers (Basel). 2025 Jan 28;17(3):441. doi:10.3390/cancers17030441.
- Tonello S, Rolla R, Tillio PA, Sainaghi PP, Colangelo D. Microenvironment and Tumor Heterogeneity as Pharmacological Targets in Precision Oncology. Pharmaceuticals. 2025 Jun;18(6):915. doi:10.3390/ph18060915.
- Tanaka M, Lum L, Hu K, Ledezma-Soto C, Samad B, Superville D, et al. Tumor cell heterogeneity drives spatial organization of the intratumoral immune response in squamous cell skin carcinoma. bioRxiv. 2023 Jun 21;2023.04.25.538140. doi:10.1101/2023.04.25.538140.
- MacDonald WJ, Purcell C, Pinho-Schwermann M, Stubbs NM, Srinivasan PR, El-Deiry WS. Heterogeneity in Cancer. Cancers. 2025 Jan;17(3):441. doi:10.3390/cancers17030441.
- Dong M, Wang L, Hu N, Rao Y, Wang Z, Zhang Y. Integration of multi-omics approaches in exploring intra-tumoral heterogeneity. Cancer Cell Int. 2025 Aug 29;25:317. doi:10.1186/s12935-025-03518-w.
- Fu YC, Liang SB, Luo M, Wang XP. Intratumoral heterogeneity and drug resistance in cancer. Cancer Cell Int. 2025 Mar 18;25:103. doi:10.1186/s12935-025-03432-5.
- A MM, Kim JY, Pan CH, Kim E. The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response. PLOS Comput Biol. 2022 Mar 9;18(3):e1009919. doi:10.1371/journal.pcbi.1009919.
- Fu YC, Liang SB, Luo M, Wang XP. Intratumoral heterogeneity and drug resistance in cancer. Cancer Cell Int. 2025 Mar 18;25(1):103. doi:10.1186/s12935-025-03432-5.
- Chai X, Tao Q, Li L. Spatiotemporal Heterogeneity of Tumor Glucose Metabolism Reprogramming: From Single-Cell Mechanisms to Precision Interventions. Int J Mol Sci. 2025 Jan;26(14):6901. doi:10.3390/ijms26146901.
- Biray Avci C, Goker Bagca B, Nikanfar M, Takanlou LS, Takanlou MS, Nourazarian A. Tumor microenvironment and cancer metastasis: molecular mechanisms and therapeutic implications. Front Pharmacol. [Internet]. 2024 Nov 12 [cited 2025 Oct 1];15. Available from: https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2024.1442888/full doi:10.3389/fphar.2024.1442888.
- Kunachowicz D, Tomecka P, Sędzik M, Kalinin J, Kuźnicki J, Rembiałkowska N. Influence of Hypoxia on Tumor Heterogeneity, DNA Repair, and Cancer Therapy: From Molecular Insights to Therapeutic Strategies. Cells. 2025 Jul 10;14(14):1057. doi:10.3390/cells14141057.
- Huang R, Kang T, Chen S. The role of tumor-associated macrophages in tumor immune evasion. J Cancer Res Clin Oncol. 2024 May 7;150(5):238. doi:10.1007/s00432-024-05866-4.
- Tuo Z, Zhang Y, Li D, Wang Y, Wu R, Wang J, et al. Relationship between clonal evolution and drug resistance in bladder cancer: A genomic research review. Pharmacol Res. 2024 Aug 1;206:107302. doi:10.1016/j.phrs.2024.107302.
- Rampias T. Exploring the Eco-Evolutionary Dynamics of Tumor Subclones. Cancers. 2020 Nov;12(11):3436. doi:10.3390/cancers12113436.
- Dhungel N, Dragoi AM. Exploring the multifaceted role of direct interaction between cancer cells and fibroblasts in cancer progression. Front Mol Biosci. 2024 May 28;11:1379971. doi:10.3389/fmolb.2024.1379971.
- Allgayer H, Mahapatra S, Mishra B, Swain B, Saha S, Khanra S, et al. Epithelial-to-mesenchymal transition (EMT) and cancer metastasis: the status quo of methods and experimental models 2025. Mol Cancer. 2025 Jun 7;24:167. doi:10.1186/s12943-025-02278-x.
- Jiang M, Zhang K, Zhang Z, Zeng X, Huang Z, Qin P, et al. PI3K/AKT/mTOR Axis in Cancer: From Pathogenesis to Treatment. MedComm (2020). 2025 Jul 30;6(8):e70295. doi:10.1002/mco2.70295.
- Kay EJ, Zanivan S. The tumor microenvironment is an ecosystem sustained by metabolic interactions. Cell Rep. 2025 Mar 25;44(3):115432. doi:10.1016/j.celrep.2025.115432.
- Tan Q, Cao X, Zou F, Wang H, Xiong L, Deng S. Spatial Heterogeneity of Intratumoral Microbiota: A New Frontier in Cancer Immunotherapy Resistance. Biomedicines. 2025 May;13(5):1261. doi:10.3390/biomedicines13051261.
- Kunachowicz D, Tomecka P, Sędzik M, Kalinin J, Kuźnicki J, Rembiałkowska N. Influence of Hypoxia on Tumor Heterogeneity, DNA Repair, and Cancer Therapy: From Molecular Insights to Therapeutic Strategies. Cells. 2025 Jan;14(14):1057. doi:10.3390/cells14141057.
- Jiménez-Santos MJ, García-Martín S, Rubio-Fernández M, Gómez-López G, Al-Shahrour F. Spatial transcriptomics in breast cancer reveals tumour microenvironment-driven drug responses and clonal therapeutic heterogeneity. NAR Cancer. 2024 Dec 18;6(4):zcae046. doi:10.1093/narcan/zcae046.
- Roszkowska M. Multilevel Mechanisms of Cancer Drug Resistance. Int J Mol Sci. 2024 Jan;25(22):12402. doi:10.3390/ijms252212402.
- Liu X, Kong Y, Qian Y, Guo H, Zhao L, Wang H, et al. Spatial heterogeneity of infiltrating immune cells in the tumor microenvironment of non-small cell lung cancer. Transl Oncol. 2024 Oct 3;50:102143. doi:10.1016/j.tranon.2024.102143.
- Zielińska MK, Ciążyńska M, Sulejczak D, Rutkowski P, Czarnecka AM. Mechanisms of Resistance to Anti-PD-1 Immunotherapy in Melanoma and Strategies to Overcome It. Biomolecules. 2025 Feb;15(2):269. doi:10.3390/biom15020269.
- Imtiaz S, Ferdous UT, Nizela A, Hasan A, Shakoor A, Zia AW, et al. Mechanistic study of cancer drug delivery: Current techniques, limitations, and future prospects. Eur J Med Chem. 2025 Jun 5;290:117535. doi:10.1016/j.ejmech.2025.117535.
- Sherafat NS, Keshavarz A, Mardi A, Mohammadiara A, Aghaei M, Aghebati-Maleki L, et al. Rationale of using immune checkpoint inhibitors (ICIs) and anti-angiogenic agents in cancer treatment from a molecular perspective. Clin Exp Med. 2025;25(1):238. doi:10.1007/s10238-025-01555-1.
- Ebrahimi F, Rasizadeh R, Jafari S, Baghi HB. Prevalence of HPV in anal cancer: exploring the role of infection and inflammation. Infect Agents Cancer. 2024 Dec 18;19(1):63. doi:10.1186/s13027-024-00630-4.
- Lyubetskaya A, Rabe B, Fisher A, Lewin A, Neuhaus I, Brett C, et al. Assessment of spatial transcriptomics for oncology discovery. Cell Rep Methods. 2022 Nov 15;2(11):100340. doi:10.1016/j.crmeth.2022.100340.
- Li S, Dai Y, Chen J, Yan F, Yang Y. MRI-based habitat imaging in cancer treatment: current technology, applications, and challenges. Cancer Imaging. 2024 Aug 15;24:107. doi:10.1186/s40644-024-00813-7.
- Proietto M, Crippa M, Damiani C, Pasquale V, Sacco E, Vanoni M, et al. Tumor heterogeneity: preclinical models, emerging technologies, and future applications. Front Oncol. 2023 Apr 28;13:1164535. doi:10.3389/fonc.2023.1164535.
- Jing SY, Wang H qi, Lin P, Yuan J, Tang Z xuan, Li H. Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments. NPJ Precis Oncol. 2025 Mar 11;9:68. doi:10.1038/s41698-025-00712-9.
- Molla Desta G, Birhanu AG. Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research. Acta Biochim Pol. 2025 Feb 5;72:13922. doi:10.3389/abp.2025.13922.
- Robles-Remacho A, Sanchez-Martin RM, Diaz-Mochon JJ. Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling. Anal Chem. 2023 Oct 10;95(42):15450–60. doi:10.1021/acs.analchem.3c01416.
- Okafor CE, Egwuatu EC, Owosagba VA, Njei T, Adeyemi BI, Onuche PUO, et al. From Bench to Bedside: Medicinal Chemistry Strategies in the Development of Kinase Inhibitors for Cancer Therapy. J Cancer Tumor Int. 2025 May 10;15(2):79–96. doi:10.9734/jcti/2025/v15i2340.
- Martinelli AL, Rapsomaniki MA. ATHENA: analysis of tumor heterogeneity from spatial omics measurements. Bioinformatics. 2022 Apr 29;38(11):3151–3. doi:10.1093/bioinformatics/btac293.
- Alharbi F, Vakanski A. Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review. Bioengineering (Basel). 2023 Jan 28;10(2):173. doi:10.3390/bioengineering10020173.
- Scianna M. Selected aspects of avascular tumor growth reproduced by a hybrid model of cell dynamics and chemical kinetics. Math Biosci. 2024 Apr 1;370:109168. doi:10.1016/j.mbs.2024.109168.
- He W, Huang W, Zhang L, Wu X, Zhang S, Zhang B. Radiogenomics: bridging the gap between imaging and genomics for precision oncology. MedComm (2020). 2024 Sep 9;5(9):e722. doi:10.1002/mco2.722.
- Liu Z, Duan T, Zhang Y, Weng S, Xu H, Ren Y, et al. Radiogenomics: a key component of precision cancer medicine. Br J Cancer. 2023 Sep 21;129(5):741–53. doi:10.1038/s41416-023-02346-3.
- Reddy S, Lung T, Muniyappa S, Hadley C, Templeton B, Fritz J, et al. Radiomics and Radiogenomics in Differentiating Progression, Pseudoprogression, and Radiation Necrosis in Gliomas. Biomedicines. 2025 Jul;13(7):1778. doi:10.3390/biomedicines13071778.
- Lekkas G, Vrochidou E, Papakostas GA. Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma. Bioengineering. 2025 Aug;12(8):849. doi:10.3390/bioengineering12080849.
- Ottaiano A, Grassi F, Sirica R, Genito E, Ciani G, Patanè V, et al. Associations between Radiomics and Genomics in Non-Small Cell Lung Cancer Utilizing Computed Tomography and Next-Generation Sequencing: An Exploratory Study. Genes. 2024 Jun;15(6):803. doi:10.3390/genes15060803.
- Zhang H, Deng Y, Xiaojie MA, Zou Q, Liu H, Tang N, et al. Construction of a radiomics-based model for predicting the efficacy of radiotherapy and chemotherapy for non-small cell lung cancer. Heliyon. 2024 Jan 15;10(1):e23923. doi:10.1016/j.heliyon.2024.e23923.
- Filippi L, Urso L, Manco L, Olivieri M, Badrane I, Evangelista L. Insights into pet-based radiogenomics in oncology: an updated systematic review. Eur J Nucl Med Mol Imaging. 2025;52(11):4184–99. doi:10.1007/s00259-025-07175-3.
- Zhang T, Zhao L, Cui T, Zhou Y, Li P, Luo C, et al. Spatial-temporal radiogenomics in predicting neoadjuvant chemotherapy efficacy for breast cancer: a comprehensive review. J Transl Med. 2025 Jun 18;23:681. doi:10.1186/s12967-025-06141-x.
- Onwuemelem LA, Orobator ET, Onyedum NN, Chibueze ES, Kanu I, Christopher AA, et al. Molecular Mechanisms of Clonal Hematopoiesis in Age-Related Cardiovascular Disease and Hematologic Malignancies: Review Article. J Pharma Insights Res. 2025 Apr 5;3(2):358–72. doi:10.70094/jpir2025v3i2a3.
- Song D, Fan G, Chang M. Research Progress on Glioma Microenvironment and Invasiveness Utilizing Advanced Multi-Parametric Quantitative MRI. Cancers. 2025 Jan;17(1):74. doi:10.3390/cancers17010074.
- Zubair M, Hussain M, Albashrawi MA, Bendechache M, Owais M. A comprehensive review of techniques, algorithms, advancements, challenges, and clinical applications of multi-modal medical image fusion for improved diagnosis. Comput Methods Programs Biomed. 2025 Dec 1;272:109014. doi:10.1016/j.cmpb.2025.109014.
- Zuo C, Zhu J, Zou J, Chen L. Unravelling tumour spatiotemporal heterogeneity using spatial multimodal data. Clin Transl Med. 2025 May 7;15(5):e70331. doi:10.1002/ctm2.70331.
- Brancato V, Esposito G, Coppola L, Cavaliere C, Mirabelli P, Scapicchio C, et al. Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine. J Transl Med. 2024 Feb 5;22:136. doi:10.1186/s12967-024-04936-y.
- Nieszporek A, Wierzbicka M, Khan A, Jeziorny M, Kraiński P, Cybinska J, et al. Spatial profiling technologies for research and clinical application in head and neck squamous cell cancers. Curr Res Biotechnol. 2025 Jan 1;10:100321. doi:10.1016/j.crbiot.2025.100321.
- Hatoum F, Fazili A, Miller JW, Wang X, Yu X, Lu X, et al. Current Role and Future Frontiers of Spatial Transcriptomics in Genitourinary Cancers. Cancers. 2025 Jan;17(17):2774. doi:10.3390/cancers17172774.
- Atalor SI, Soliman AMM, Adedokun OK, Modinat Aina A, Unegbu CC, Okayo OD, et al. Beyond Inhibition: Emerging Small-Molecule Modalities in Oncology (Molecular Glues, Covalents, and Radiotheranostics). Aust J Biomed Res. 2025 Sep 19;1(2):aubm007. https://doi.org/10.63946/aubiomed/17089
- Fagbenle EO, Solomon O, Khameneh JZ, Arokodare OE. Forecasting Physician Burnout Risk: The Role of Electronic Health Record (EHR) and Operational Data in Predictive Models of Burnout. Aust J Biomed Res. 2025 Aug 22;1(1):aubm004. https://doi.org/10.63946/aubiomed/16810
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