APOBEC affects tumor evolution and age at onset of lung cancer in smokers

Tongwu Zhang1, Jian Sang1, Phuc H Hoang1

  • 1Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.

PubMed

Insights

Lung cancer subtypes show distinct APOBEC mutagenesis patterns. High APOBEC3A (A3A) activity correlates with TP53 mutations and progenitor cells, while APOBEC3B (A3B) links to KRAS mutations in smokers.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Somatic mutations from APOBEC3A (A3A) and APOBEC3B (A3B) are common in solid tumors.
  • The impact of A3A/B enzymes on tumor evolution alongside external mutagens is not well understood.

Purpose of the Study:

  • To investigate how APOBEC mutagenesis subtypes influence lung cancer development in smokers.
  • To characterize the distinct genomic and cellular features of these subtypes.

Main Methods:

  • Multi-omics profiling of 309 lung cancers from smokers.
  • Analysis of mutation patterns, including APOBEC3A-like and APOBEC3B-like signatures.
  • Comparison of tumor subtypes based on APOBEC mutagenesis levels (LAS vs. HAS).

Main Results:

  • Two lung cancer subtypes identified: Low APOBEC Signature (LAS) and High APOBEC Signature (HAS).
  • LAS tumors showed A3B-like mutagenesis, KRAS mutations, and were linked to smoking.
  • HAS tumors exhibited A3A-like mutagenesis, TP53 mutations, older age at onset, progenitor cells, more neoantigens, and distinct signaling pathways.

Conclusions:

  • APOBEC mutagenesis heterogeneity, combined with smoking and cell type, drives lung cancer evolution.
  • Distinct APOBEC signatures (A3A vs. A3B) define tumor subtypes with different characteristics and origins.
  • Findings highlight the interplay between endogenous mutational processes and external factors in cancer development.

Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
278
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
6.2K
Cancer Prevention02:59

Cancer Prevention

Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
6.0K
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
5.7K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
318
The Retinoblastoma Gene01:20

The Retinoblastoma Gene

Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
The first-ever tumor suppressor gene called Rb was identified in retinoblastoma - a rare eye tumor in children. In inherited forms of the disease, a child inherits one defective copy of the Rb gene, which predisposes them to retinoblastoma. However,...
4.0K