Table 2 Biological findings by targeted sampling-based sorting technologies in cancer research
From: Mapping cancer biology in space: applications and perspectives on spatial omics for oncology
Target | Technology | Finding Type | Biological Findings | Cancer | Reference | Stats ( gene/cells (gc) or gene/mm^2 (gm) ) |
|---|---|---|---|---|---|---|
RNA | LCM | Biomarker | AVR7 is a tumor suppressive gene in gastric resistant prostate cancer | Prostate cancer | Cato et al.(2019) [212] | Â |
| Â | LCM | Biomarker | COL1A1 is a promising therapeutic marker in glioma | NSCLC | Baldelli et al(2022) [213] | 6-60 cells |
|  | LCM | Biomarker | Invasive lobular breast cancer's stroma and CAF pathway discovery and two genes were influenced survival rates. | Invasive lobular breast cancer | Gómez-Cuadrado et al.(2022) [214] |  |
| Â | LCM | Biomarker | Detection of EGFR and KRAS mutation with few cells, approximately 50 tumor cells | Lung adenocarcinoma | Chowdhuri et al. (2012) [215] | As few as 50 cells |
| Â | LCM | Biomarker | Efficiency of detecting EGFR and KRAS gene mutations increased significantly with LCM | Lung cancer | Malapelle et al. (2011) [216] | Â |
| Â | LCM | Heterogeneity | Recurrent nasopharyngeal carcinoma has a differential gene expression from non-recurrent tumor. | Nasopharyngeal cancer | Tay et al.(2022) [217] | Â |
| Â | SLACS | Biomarker | A-to-I editing events in a specific gene has a correlation with the therapeutic response | Triple Negative Breast Cancer | 3-5 c | |
DNA | LCM | Biomarker | LOH of 10q23.3 marker for metastatic progression | Node-positive prostate cancer | Rubin et al. (2000) [218] | Â |
| Â | LCM | Biomarker | Allelic loss at chromosome p16 and p53 consistent during cancer progression | Metastatic bladder cancer | Cheng et al. (2001) [219] | Â |
| Â | LCM | Biomarker | LOH (Loss of Heterozygosity) detection in tumor | Inflammatory Breast Cancer | Bertheau et al. (2001) [220] | 500 cells / 5000 cells |
| Â | LCM | Biomarker | Allelic loss of activated X chromosome related to carcinogenesis and progression | Bladder cancer | Cheng et al. (2004) [221] | 400-600 cells |
| Â | LCM | Biomarker | Observed AMACR (Alpha-methylacyl-coenzyme A racemase) regulation | Colon Adenoma-carcinoma | Zhang et al. (2009) [222] | Â |
| Â | LCM | Biomarker | Detection of somatic mutations | Various solid tissues and lobular carcinoma | Ellis et al. (2020) [74] | 100-1000 cells |
| Â | LCM | CTC genotyping | CTC genotyping in glioma | glioma | Zhu et al.(2022) [223] | Â |
| Â | LCM | Heterogeneity | Heterogeneity based on the observations of LOH (Loss of Heterozygosity) | Breast cancer | Wild et al. (2000) [224] | Â |
| Â | LCM | Heterogeneity | Detection of nonrandom X chromosome inactivation in different regions of same tumor sample | Bladder Carcinoma | Cheng et al. (2002) [225] | 400-600 cells |
| Â | LCM | Heterogeneity | Detection of geneitc divergence during clonal evolution | Cell renal cell carcinoma | Jones et al. (2005) [226] | 400-1000 cells |
| Â | LCM | Heterogeneity | Identification of frequent genetic divergence during metastases | Cutaneous melanoma | Katona et al. (2007) [227] | 400-1000 cells |
| Â | LCM | Heterogeneity | Structural variant analysis with LCM+ grouping tumor types | Post-pubertal testicular germ-cell tumours | Bryce et al.(2019) [73] | Â |
| Â | LCM | Heterogeneity | Somatic mutation pattern analysis of cancers | Various types | Olafsson et al.(2021) [228] | few hundreds cells |
| Â | SLACS | Heterogeneity | Genomic landscape of the cells in 3D tumor mass | Breast cancer | Kim et al. (2018) [92] | 3-5 cells |
| Â | SLACS | Prognosis | Mapping of clonal changes within hematopoietic lineages to performing prognosis liquid cancer | Myeloma and leukemia | Jeong et al. (2023) [96] | Â |
Protein | LCM | Biomarker | Using RRPA and LCM found cellular signaling protein in breast cancer | Breast cancer | Cowherd et al.(2004) [229] | Â |
| Â | LCM | Biomarker | Observation of 12 novel TVM (tumor vascular markers) | Ovarian cancer | Buckanovich et al. (2007) [230] | -2000 cells |
| Â | LCM | Biomarker | Finding a connection with protein and subcellular structure names invadosome about cancer | Cancer specimen | Ezzoukhry et al.(2018) [83] | 312 proteins enriched / 100, 350, 3000, 10000, 40000 cells |
|  | LCM | Biomarker | NMNT is a marker which affects CAF(Cancer-associated Fibroblast). | glioblastoma | Lam et al.(2022) [87] | 40,000,000 µm^2 for proteomics |
Epigenome | LCM | Biomarker | Detected 766 up or down-regulated genes with subtype comparisons | Lung adenocarcinoma | Selamat et al. (2012) [231] | 766 genes |
| Â | LCM | Heterogeneity | Using RRBS with LCM and found DNA methylation pattern of adrenoncoroticla | adrenocortical carcinoma | Schillebeeckx et al.(2013) [232] | Â |
| Â | LCM | CTC methylation profiling | Epigenetic features of CTC with LCM | Lung cancer | Zhao et al.(2021) [86] | 10, 50 cells |
DNA + RNA | LCM | Biomarker | Finding a biomarker for TNBC patients with phase2 neoadjuvant therapy | Breast cancer | Jovanovic et al. (2017) [233] | Â |
| Â | LCM | Heteogeneity | CNV and gene expression profiling in ROI of oral squamous cell carcinoma | Oral squamous cell carcinoma | Chen et al. (2022) [234] | 230 cells |
| Â | LCM | Heterogeneity | Landcape of genomic and transcriptomic of Lung Adenomatous Premalignancy | Lung cancer | Krysan et al. (2019) [235] | Â |
| Â | LCM | Tumor subtyping & heterogeneity | regrouping cancer subtypes with proteome analysis which leads to overcome therapy resistance and targeting heterogeneity | TNBC | Zhu et al. (2021) [88] | 50-200 cells |
Protein + RNA | LCM | Biomarker | Identification cancer promoting stromal component in proteomic and transciptomic aspects in canine mammary tumors | canine mammary tumors | Poschel et al (2021) [236] | Â |