Lung Cancer Genomics

A large lung cancer genomics study has been making a big splash. Using SNP microarrays to look for changes in the copy number of genes across the genome, the group looked at a large batch of lung adenocarcinoma samples. Note: the paper will require a Nature subscription, but the supplementary materials are available to all.

As with most such studies, there was some serious sample attrition. They started with 528 tumor samples, of which 371 gave high-quality data. 242 of these had matched normal tissue samples. All of the samples were snap-frozen, meaning the surgeon cut it out and the sample was immediately frozen in liquid nitrogen.

The sub-morphology of the samples is surprisingly murky; much of the text focuses on Non-Small Cell Lung Cancer (NSCLC), the most common form of lung adenocarcinoma, but the descriptions of the samples do not rule out other forms.

After hybridizing these to arrays, a new algorithm called GISTIC, whose full description is apparently in press, was used to identify genomic regions which were either deficient or amplified in multiple samples.

Many changes were found, which is no surprise given that cancer tends to hash the genome. Some of these changes are huge: 26 recurrent events involving alteration of at least half a chromosome arm. Others are more focused.

One confounding factor is that no tumor sample is homogeneous, and in particular there is some contamination with normal cells. These cells contribute DNA to the analysis and in particular make it more difficult to detect Loss-of-Heterozygosity (LOH), in which a region is at normal copy number but both copies are the same, such as both carrying the same mutated tumor suppressor.

Seven recurrent focal deletions were identified, two of which cover the known tumor suppressors CDKN2A and CDKN2B, inhibitors of the cell cycle regulatory cyclin-dependent kinases. The corresponding kinases were found in recurrently amplified regions; an neat but evil symmetry. Tumor suppressors PTEN and RB1 were found also in recurrent deletions. The remaining recurrent deletions hit genes not well characterized as tumor suppressors. One hits the phosphatase PTPRD -- the first time such deletions have been found in primary clinical specimens. Another hits PDE4D, a gene known to be active in airway cells. A third takes out a gene of unknown function, AUTS2.

In order to gain further evidence that these deletions are not simply epiphenomena of genomic instability, targeted sequencing was used to look for point mutants. Only PTRPD yielded point mutants from tumor samples, several of which are predicted to disable the enzymatic function of this gene's product.

On the amplification side, 24 recurrent amplifications were observed. Three cover known bad actors: EGFR (target of Iressa, Tarceva, Erbitux, etc), KRAS and ERBB2 (aka HER2, the target for Herceptin). Another amplification covers TERT, a component of the telomerase enzyme which is required for cellular immortality, a hallmark of cancer. Another amplification covers VEGFA, a driver of angiogenesis and part of the system targeted by drugs such as Avastin. Other amplifications, as mentioned above, target cell cycle regulation: CDK4, CDK6 and CCND1.

The most common amplification has gotten a lot of press, as it covered a gene not previously implicated in lung cancer: NKX2-1. A neighboring gene (MBIP2) was present in all but one of the amplifications, and so NKX2-1 was focused on. Fluorescent In Situ Hybridization (FISH), a technique which can resolve amplification on a cell-by-cell basis in a tissue sample, confirmed the frequent amplification of NKX2-1 specifically in tumor cells. Resequencing of NKX2-1, however, failed to reveal any point mutations in the tumor samples. RNAi in lung cancer cell lines with NKX2-1 amplification showed a reduction of a commonly-used tumor-likeness measure (anchorage-independent growth). This effect was not seen in a cell line with undetectable NKX2-1 expression, nor was it detected when MBIP2 was knocked down. Previous knockout mouse data has pointed to a key role for NKX2-1 in lung cell development. The protein product is a transcription factor, and the amplification of lineage-specific transcription factors has been observed in other tumors.

What will the clinical impact of this research be? None of the targetable genes which were amplified are novel, so this will nudge interest further along (such as in using Herceptin in select lung cancers), but not radically change things. Transcription factors in general have no history of being targeted with drugs, so it is unlikely that anything will come rapidly from the NKX2-1 observations. On the other hand, there will probably be a lot of work to try to characterize how NKX2-1 drives tumor development, such as to identify downstream pathways.

At least some of the press coverage has remarked on the price tag for this work & the surrounding controversy over the Cancer Genome Project that this represents. The claimed figure is $1 million, which does not seem at all outrageous given the large number of microarrays used (over one thousand, if I'm adding the right numbers) -- a few hundred dollars per microarray for the chip and processing is not unreasonable, and the study did a bunch more (analysis, sequencing, RNAi). If such a study were to be repeated at todays prices in the next 5 big cancer killers (breast, ovarian, prostate, pancreatic, colon), it means another $5M not spent on other approaches. In particular, the debate centers around whether the focus should be on more functional approaches rather than genomics surveys. As fond as I am of genomics approaches, it is worth pondering how else society might spend these resources.

It is also worth noting what the study didn't or couldn't find. A large number of known lung cancer relevant genes did not turn up or turned up only weakly. In particular, p53 is mutated in huge numbers of cancers but didn't really turn up here. The technique used will be blind to point mutants and also can't detect balanced translocations. Nor could it detect epigenetic silencing. If you want to chase after those, then it is more genomics -- which is probably one of the things that eats at critics, the appearance that genomics will never stop finding ways to burn money.

Weir et al. Nature Advance Publication. Characterizing the cancer genome in lung adenocarcinoma. doi:10.1038/nature06358