Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise
Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/12/9/2572 |
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| author | Sanjna Nilesh Nerurkar Denise Goh Chun Chau Lawrence Cheung Pei Qi Yvonne Nga Jeffrey Chun Tatt Lim Joe Poh Sheng Yeong |
| author_facet | Sanjna Nilesh Nerurkar Denise Goh Chun Chau Lawrence Cheung Pei Qi Yvonne Nga Jeffrey Chun Tatt Lim Joe Poh Sheng Yeong |
| author_sort | Sanjna Nilesh Nerurkar |
| collection | DOAJ |
| description | Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies. |
| first_indexed | 2024-03-10T16:27:29Z |
| format | Article |
| id | doaj.art-7af354d44d5e44f8a33714f0310ba92e |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T16:27:29Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-7af354d44d5e44f8a33714f0310ba92e2023-11-20T13:08:30ZengMDPI AGCancers2072-66942020-09-01129257210.3390/cancers12092572Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and PromiseSanjna Nilesh Nerurkar0Denise Goh1Chun Chau Lawrence Cheung2Pei Qi Yvonne Nga3Jeffrey Chun Tatt Lim4Joe Poh Sheng Yeong5Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, SingaporeInstitute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), Singapore 169856, SingaporeDuke-NUS Medical School, Singapore 169857, SingaporeInstitute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), Singapore 169856, SingaporeInstitute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), Singapore 169856, SingaporeInstitute of Molecular and Cell Biology (IMCB), Agency of Science, Technology and Research (A*STAR), Singapore 169856, SingaporeIntratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.https://www.mdpi.com/2072-6694/12/9/2572heterogeneityclonal diversitytranscriptomicsin situ hybridizationdigital spatial profilingcancer |
| spellingShingle | Sanjna Nilesh Nerurkar Denise Goh Chun Chau Lawrence Cheung Pei Qi Yvonne Nga Jeffrey Chun Tatt Lim Joe Poh Sheng Yeong Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise Cancers heterogeneity clonal diversity transcriptomics in situ hybridization digital spatial profiling cancer |
| title | Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise |
| title_full | Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise |
| title_fullStr | Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise |
| title_full_unstemmed | Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise |
| title_short | Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise |
| title_sort | transcriptional spatial profiling of cancer tissues in the era of immunotherapy the potential and promise |
| topic | heterogeneity clonal diversity transcriptomics in situ hybridization digital spatial profiling cancer |
| url | https://www.mdpi.com/2072-6694/12/9/2572 |
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