Using Large-Scale Genomics Data to Identify Driver Mutations in Lung Cancer: Methods and Challenges

Figures & data

Figure 1. Summary schematic highlighting the factors leading to biases and heterogeneity of mutational data.

In areas of uniform mutational rates longer coding genes will demonstrate a higher mutational frequency if the data are not length corrected. Genes that are not expressed and those that replicate late in the cell cycle will have higher mutational rates. Genes with large GC-rich regions will have inadequate sequencing coverage and potential mutations will be missed leading to an underreporting of mutations in these genes.

Table 1A. Top 20 frequently mutated genes in squamous lung cancer with number of mutated cases and longest corresponding protein length. 

Gene	Number mutated cases (out of 178 cases)	Longest protein length (amino acids)
TTN	92	35991
CSMD3	55	3707
RYR2	53	4967
ZFHX4	53	3616
MUC16	51	14507
LRP1B	48	4599
USH2A	43	5202
SYNE1	35	8797
RYR3	34	4873
FLG	31	4061
DNAH5	29	4624
PKHD1	29	4074
MUC17	29	4493
MUC5B	28	5762
AHNAK2	28	5795
SI	28	1827
FAM135B	28	1406
KMT2D	27	5537
HCN1	27	890
CSMD1	27	3565

Seven of these top 20 mutated genes encode proteins in the top 20 longest proteins in the TCGA dataset.

Table 1B. Top 20 frequently mutated genes in squamous lung cancer normalized for length of longest protein and ranked by length corrected score. 

Gene	Length corrected score	Longest protein length (amino acids)	Number of mutations	Comments
CDKN2A	0.152941176	170	26	Evidence of role in lung cancer [38]
REG3A	0.057142857	175	10
REG1B	0.054216867	166	9
REG1A	0.054216867	166	9
KRTAP19–3	0.049382716	81	4	Hair cortex – keratin-associated protein
COX7B2	0.049382716	81	4
OR5D18	0.044728435	313	14	Olfactory receptor
SST	0.043103448	116	5
SPANXN1	0.041666667	72	3	Sperm protein associated with the nucleus
OR2T4	0.040229885	348	14	Olfactory receptor
REG3G	0.04	175	7
OR6F1	0.035714286	308	11	Olfactory receptor
OR5L2	0.035369775	311	11	Olfactory receptor
MANBAL	0.035294118	85	3
PRAC1	0.035087719	57	2
NFE2L2	0.033057851	605	20	Evidence of role in lung cancer [39]
LENEP	0.032786885	61	2
TPTE	0.032667877	551	18
STATH	0.032258065	62	2
SLN	0.032258065	31	1

Proteins previously demonstrated to play a role in lung cancer feature in the list (CDKN2A, NFE2L2) as well as proteins such as olfactory receptors that are unlikely to be expressed in lung cancer and are therefore less likely to undergo transcription coupled repair of somatic mutations. The length correction means that very small proteins with a small number of incidental mutations are also represented.

Table 2. Mutation predictor data for the three pathogenic mutations discovered with a targeted siRNA screen [61].

Target	Cell line	Mutation	Provean (cut-off = -2.5)	Sift (cut-off = 0.05)	Mutationassessor.org	Polyphen2
FGFR4	H2122	P712T	Neutral (-0.09)	Tolerated (0.242)	Low functional impact	Possibly damaging
MAP3K9	H2009	E179K	Neutral (-2.21)	Tolerated (0.085)	Low functional impact	Possibly damaging
PAK5	H2087	T538N	Deleterious (-2.92)	Damaging (0.045)	Neutral	Probably damaging

The FGFR4 and MAP3K9 mutations would be classified as nonpathological by three out of four of these assessors.

Andujar P , WangJ , DescathaAet al. P16ink4a inactivation mechanisms in non-small-cell lung cancer patients occupationally exposed to asbestos . Lung Cancer67 ( 1 ), 23 – 30 ( 2010 ).

 PubMed Web of Science ®Google Scholar

Singh A , Boldin-AdamskyS , ThimmulappaRKet al. RNAI-mediated silencing of nuclear factor erythroid-2-related factor 2 gene expression in non-small cell lung cancer inhibits tumor growth and increases efficacy of chemotherapy . Cancer Res.68 ( 19 ), 7975 – 7984 ( 2008 ).

 PubMed Web of Science ®Google Scholar

Fawdar S , TrotterEW , LiYet al. Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer . Proc. Natl Acad. Sci. USA110 ( 30 ), 12426 – 12431 ( 2013 ).

 PubMed Web of Science ®Google Scholar