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Updated: Jul 4, 2025
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Molecular heterogeneity in histomorphologic subtypes of lung adeno carcinoma represents a challenge for treatment
Tobias Kolb1, Sarah Müller1, Peter Möller1
1Institute of Pathology, Ulm University, Ulm, Germany.
Abstract:
Lung cancer is the leading cause in cancer related death, with non-small cell lung cancer (NSCLC) being the most frequent subtype. The importance of NSCLC is reflected by the various targeted therapy options especially for NSCLC adenocarcinomas (lung adeno carcinoma (LUAD)) as well as a set of options for immune therapies. However, despite these therapy advances, the majority of patients do not show a long-term response to either targeted therapy or immune checkpoint inhibition. One reason for treatment failure appears to be the NSCLC tumor heterogeneity. NSCLC heterogeneity might lead to an insufficient molecular characterization of a given sample due to the limited tumor material used for pathological assessment as the majority of analyses is performed on small biopsies. To get a more detailed insight into the tumor heterogeneity of NSCLC LUAD, especially in the light of its different histomorphological growth patterns, we analysed isolated NSCLC growth pattern areas and the corresponding entire tumor samples of a cohort of 31 NSLCS LUAD patients and compared their mutational landscape and their expression profiles. While significant differences of complex biomarkers, like tumor mutational burden (TMB) or microsatellite instability (MSI), were not detected between the five growth patterns -lepidic, papillary, micropapillary, acinar, and solid- we observed various subclonal mutations and copy number variants. Moreover, RNASeq analysis revealed growth pattern specific expression profiles affecting cellular processes like apoptosis, metastasis and proliferation. Taken together, our data provide novel insights into the tumor heterogeneity of LUAD required to overcome tumor heterogeneity related therapy resistance.
Insights
Tumor heterogeneity in lung adenocarcinoma (LUAD) impacts treatment response. Analyzing different growth patterns revealed subclonal mutations and distinct gene expression profiles, offering insights to overcome therapy resistance.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Non-small cell lung cancer (NSCLC), particularly lung adenocarcinoma (LUAD), is a leading cause of cancer death.
- Despite advances in targeted and immune therapies, many patients lack long-term response due to tumor heterogeneity.
- Current molecular characterization often relies on limited biopsy material, potentially missing crucial heterogeneity information.
Purpose of the Study:
- To investigate tumor heterogeneity in LUAD by analyzing distinct histomorphological growth patterns.
- To compare the mutational landscape and gene expression profiles across different LUAD growth patterns.
- To identify insights into overcoming therapy resistance driven by LUAD tumor heterogeneity.
Main Methods:
- Analysis of isolated growth pattern areas and entire tumor samples from 31 LUAD patients.
- Comparison of mutational landscapes, including tumor mutational burden (TMB) and microsatellite instability (MSI).
- RNA sequencing (RNASeq) to analyze gene expression profiles across different growth patterns.
Main Results:
- No significant differences in TMB or MSI were found between the five growth patterns (lepidic, papillary, micropapillary, acinar, solid).
- Various subclonal mutations and copy number variants were identified across different growth patterns.
- RNASeq revealed growth pattern-specific expression profiles impacting apoptosis, metastasis, and proliferation.
Conclusions:
- LUAD exhibits significant tumor heterogeneity at the subclonal mutation and gene expression levels across different growth patterns.
- Understanding these growth pattern-specific molecular alterations is crucial for developing strategies to overcome therapy resistance.
- This study provides novel insights into LUAD heterogeneity essential for improving patient treatment outcomes.
