Vaguely seen on images, lung nodules’ genomics outline progression to cancer

Small precancerous growths in the lungs are capable of progressing to invasive lung cancer, but so little has been known about them that understanding the risk of progression and how to deal with it has remained a puzzle.

A research team led by MD Anderson physicians and scientists has conducted the first large-scale multi-region exome sequencing of these nodules, building a picture of their genomics that unveiled a few surprises but also reinforced that precancerous growths have simpler molecular profiles that would make them easier to treat than tumors.

“More of these nodules are being found as ‘incidentalomas’ by CT imaging for injuries from accidents and low-dose CT screening of long-term heavy smokers for lung cancer,” says  Jianjun  Zhang, M.D., Ph.D., assistant professor of Thoracic/Head and Neck Medical Oncology and senior author of the paper in Nature Communications.  “They have become endemic, and their discovery has been technology-driven.”

Based on imaging, many of these growths are characterized as indeterminate pulmonary modules. These nodules are too small to biopsy, so U.S. practice has been to observe them rather than remove them. “Because we don’t know what they are, we don’t know how to treat them,” Zhang says.

Oncologists in other countries take an aggressive approach, surgically removing these growths, which provided Zhang and colleagues an opportunity to study them. From collaborators in Japan and China, they gained access to 116 resected IPNS from 53 patients, which were histologically characterized by pathologists.

There are four types of nodule, listed in ascending order of malignancy:

· Atypical adenomatous hyperplasia (AAH), 22 precancerous growths

· Adenocarcinoma in situ (AIS) 27 nodules

· Minimally invasive adenocarcinoma (MIA) 54  tumors

· Invasive adenocarcinoma (ADC) 13 tumors

It’s not known whether every one of these states is achieved by precancerous growths that progress to invasive lung cancer, Zhang says. 

Whole exome sequencing of multiple regions of a tumor or a precancerous growth helps researchers identify mutations that have occurred during the early steps of cancer development.  Those found in every region were early events, while those found in just a few regions occurred later.

The majority of cancer driver gene mutations found by studying invasive cancers are early events. The current study using precancerous specimens demonstrated some of these driver mutations occur relatively late in the cancer development process, providing a far more detailed road map, Zhang says.

Genetic heterogeneity grows

The team found a number of distinct differences or patterns in genetic mutations.

Total mutational burden was analyzed by assessing single nucleotide variations.  The team found mutational burden increased progressively starting with the precancerous AAH through the invasive adenocarcinoma.  While this finding was expected, the team’s study was the first to document progression to greater mutational burden.

They identified six mutational signatures that have potential roles in early lung carcinogenesis.

Chromosomal analysis revealed a more complex picture, with possible chromosomal macroevolution during transitions from AAH, the simplest stage, to AIS, the next stage and then from AIS to minimally invasive disease (MIA).

This study provides new molecular evidence to support the evolution of lung adenocarcinoma from AAH, AIS, MIA and ADC, a model that was long proposed, Zhang explains, but constantly debated for lack of molecular evidence.

Clonal complexity

The team explored the clonal architecture of each type. Clonal mutations are present in every cell of a nodule or tumor and subclonal mutations are less commonly present.

Overall, the nodules studied had an average of 48.8 percent clonal mutations, compared to an average of 68.2 percent in invasive lung cancers.

Precancerous AAH was surprisingly complex, with more subclonal than clonal mutations. Both clonal and subclonal mutations progressively increased, with invasive adenocarcinoma having the highest clonal mutational burden but also the highest subclonal burden, a surprising finding.

When mutations become more clonal, dominant mutations endure while less common mutations are eliminated – a model called clonal sweep – the burden of uncommon mutations usually decreases, Zhang explains. In this case, both common and uncommon mutations increased in the more advanced nodules. Genetic heterogeneity increased across nodule type, and was substantial among patients at each stage.

A variety of commonly mutated cancer genes were identified, including EGFR, KRAS, RBM10, TP52, as well as chromosomal loss of two common tumor suppressors: STK11 and CDKN2A.

EGFR was the most commonly mutated cancer gene found at levels ranging from 29.6% to 46.2% of the three advanced types of growth, but not found at all in the 22 precancerous AAH lesions. A second analysis found EGFR mutations present as minor subclones in AAH, but as major subclones in each of the more advanced growths, implying an advantage for cells with EGFR mutations.

Future research

Zhang notes larger studies will be needed to further illuminate the progression between stages and to shed light on tumor heterogeneity among patients. Additional endpoints, such as recurrence and overall survival would also better define the molecular subtypes and assess their prognostic values.

Further deciphering how the genomic landscape evolves with progression requires a clinical trial that includes longitudinal biopsies.  Zhang has one such clinical trial open.  He and colleagues also study immune surveillance across the spectrum of preneoplasia to lung cancer.

This study was supported by the MD Anderson Khalifa Scholar Award, a grant from the National Cancer Institute of the National Institutes of Health (R01CA234629-01), an  AACR-Johnson & Johnson Lung Cancer Innovation Science Grant, the MD Anderson Physician Scientist Program, the MD Anderson Lung Cancer Moon Shot®, T.J. Martell Foundation Award, Sabin Family Foundation Award, Duncan Family Institute Cancer Prevention Research Seed Funding Program, the Major Science and Technology Project of Zhejiang Province of China, the Cancer Prevention and Research Institute of Texas, the University of Texas Systems Stars Award, the Welch Foundation, the U.S. Department of Defense, and the UT Lung Specialized Programs of Research Excellence Grant from the NCI (P50CA70907).