Genome Wide Association Studies in Small-Cell Lung Cancer. A Systematic Review

Review Article Genome Wide Association Studies in Small-Cell Lung Cancer. A Systematic Review José Ramón Enjo-Barreiro, 1 , 2 , # Alberto Ruano-Ravina, 1 , 3 , 4 Mónica Pérez-Ríos, 1 , 3 , 4 Karl Kelsey, 5 Juan Miguel Barros-Dios, 1 , 3 , 4 Leonor Varela-Lema 1 , 3 , 4 Abstract Small cell lung cancer (SCLC) is one of the deadliest forms of lung cancer, but few information exists regarding the role of genetics, particularly on Genome Wide Association Studies (GWAS). The aim of the study is to explore the evidence available obtained through GWAS studies for SCLC using a systematic review. We performed a literature search in the main databases until July 31st, 2023. We included all human based studies on GWAS for lung cancer which presented results for SCLC. Only studies with participants diagnosed of SCLC with anatomopathological confirmation were included. Fourteen studies were identified; 8 studies showed a relationship between ASCL1 overexpression and SCLC, which may regulate CHRNA5/A3/B4 cluster, producing a consequent nAChR overexpression. Nine papers, including 8 of the previous, found a positive association between SNPs located in chromosome 15 and SCLC. The most important cluster of genes found is CHRNA5/A3/B4 but the mechanism for the role of these genes is unclear. Kyoto Encyclopaedia of Genes and Genome (KEGG) shows that these receptors were found to be overexpressed where nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N’-Nitrosonornicotine (NNN) acts, involving different routes in SCLC carcinogenesis. Clinical Lung Cancer, Vol. 25, No. 1, 9–17 © 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ) Keywords: Lung neoplasm, Small-cell lung carcinoma, Oncogenes, CHRNA5/A3/B4, ASCL1 Introduction Lung cancer, according to GLOBOCAN 2020, represents the leading cause of cancer death, comprising 18% of all cancer deaths worldwide. 1 The main risk factor for developing lung cancer is tobacco consumption, followed by indoor radon exposure. 2 , 3 However, though most of lung cancers are originated by tobacco or indoor radon exposure, produced mainly by the radioactive decay of uranium, 4 not all exposed to these substances develop lung cancer, suggesting that there are other factors involved, among these, genetic susceptibility factors. 1 Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain 2 Service of Preventive Medicine, A Coruña University Teaching Hospital Complex, A Coruña, Spain 3 Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Santiago de Compostela, Spain 4 Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Santiago de Compostela, Spain 5 Department of Epidemiology, Brown School of Public Health, Brown University, Providence, RI Submitted: May 12, 2023; Revised: Aug 28, 2023; Accepted: Oct 9, 2023; Epub: 12 October 2023 Address for correspondence: Ruano-Ravina Alberto, PhD, Department of Preventive Medicine and Public Health, School of Medicine, University of Santiago de Compostela, C/ San Francisco s/n, Santiago de Compostela 15782, Spain. E-mail contact: [email protected] # This research is part of the PhD work of José Ramón Enjo-Barreiro. Lung cancer is usually classified in 2 main histological groups attending to the characteristics of the tumor and the treatment response: non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). SCLC represents only 15% of lung cancer cases but it is characterized by the lowest survival rate, with 5-year survival lower than 7%. 5 , 6 SCLC occurs in the pulmonary neuroendocrine cells in the proximal airways, these cells sense stimuli such as nicotine and oxygen 7 . These type of cells highly express mammalian achaete-scute complex homolog-1 ( ASCL1 ) and neural cell adhesion molecule ( NCAM1 ), which are important for neuronal differentiation and maturation, having an important role in SCLC development. 8 Currently, this disease is starting to be considered a not uniform pathology, because authors like Rudin et al. 9 describe 4 molecular subtypes classified by the different expression of 4 key transcription regulators. 6 , 9 Moreover, despite SCLC and NSCLC are different tumors, it is observed that a small group of NSCLC with an epidermal grow factor receptor (EGFR)-mutation display some resistance to therapies against EGFR showing a histological transformation to SCLC. 10 , 11 Regarding SCLC we know that some mutations are related to the development of this type of cancer, but the molecular landscape of this tumor is highly complex. To study this, GWAS is a useful research approach, which combine molecular genetic analysis techniques and epidemiological study designs, to sequence the 1525-7304/$ - see front matter © 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/bync-nd/4.0/ ) https://doi.org/10.1016/j.cllc.2023.10.002 Clinical Lung Cancer January 2024 9 Genome Wide Association Studies in Small-Cell Lung Cancer human genome and calculate the polygenic risk score for specific genetic variants. Alternatively, genotype imputation combine with low-pass sequencing is showing a higher statistical power in comparison with genotyping arrays, being an interesting substitute for polygenic scores calculation and trait mapping in genome-wide association studies. 12 GWAS evidence have made a slow progress probably due to the low number of cases included in many studies. The most common genetic alterations for SCLC are the loss of tumor suppressor P53 and retinoblastoma susceptibility gene (RB1). 13 Nevertheless, the available studies are scarce, probably due to the lower frequency of SCLC compared with NSCLC. The results of these studies are heterogeneous and there is a need to have a global picture of the genetic traits involved in SCLC appearance. To this end, Genome Wide Association Studies (GWAS) are a good tool to disentangle the role of genetics on the onset of small cell lung cancer from a global approach to the whole genome sequencing with no a priori hypotheses. We aim to compile the knowledge obtained through the available genome-wide association studies and characterize which genes might be more associated with the onset of this specific type of lung cancer from their results, using a systematic review of the scientific literature. Methods Literature Research A literature research was performed following the PRISMA methodology. 14 We searched the following databases: PubMed (Medline), EMBASE, Web of Science and GWAS Catalog. We used Mesh terms in our search strategy (genome-wide association studies; small-cell lung carcinoma and lung neoplasms) combined with free text. The search period comprised until July 31st, 2023, without any starting date. This review is registered in PROSPERO with the ID CRD42022319166. Eligibility Criteria Studies were selected by 2 investigators following specific inclusion and exclusion criteria. We only selected studies performed in humans which included SCLC cases. Due to the absence of specific GWAS that approached SCLC, we included studies based on GWAS for lung cancer which presented results for SCLC. Only studies with participants diagnosed of SCLC with anatomopathological confirmation were included. The search strategy included only studies written in Spanish and English. Assessment of the Study Quality We created a quality score for the purpose of ranking the different papers based on their quality. This scale is composed by several items similar to other scores previously used in other studies on lung cancer. 15 , 16 The items included in the score were: sample size, number of SCLC cases included in the study, covariates adjustment and study design. We assigned a weight to each item according to its relevance. The score with its items and weights assigned is shown in Table 1 . Synthesis of the Evidence We retrieved the same information, from the different studies included, in a spreadsheet form developed ad hoc . It was not possible to conduct a meta-analysis due to the different results collected among the published studies. A qualitative synthesis of the information compiled was therefore obtained. Results Search Results We identified 901 papers in Medline (PubMed), 904 in Embase, 70 in Web of Science and 3 at the GWAS catalog. After removing duplicates, and papers that were disregarded by title and reading all the abstracts of the resulting articles, we selected 310 papers for full-text reading, as shown in the PRISMA flow-diagram ( Figure 1 ). Only 14 fulfilled the inclusion/exclusion criteria and their characteristics are shown in Table 2 . We included: 2 GWAS studies, 17 , 18 Table 1 Quality Scale. Item Values Weight Sample size 50-100 0 101-500 1 > 500 2 SCLC cases N/A 0 1-50 1 51-100 2 > 100 3 Adjusted covariables 2 (gender and age) 0 > 2 2 Study design Hospital-based case-control study or series of cases 0 Population-based case-control study 1 Pooling study or meta-analysis 2 TWAS, GWAS or Cross-ancestry GWAS meta-analysis 3 Total 10 10 Clinical Lung Cancer January 2024 José Ramón Enjo-Barreiro et al Table 2 Articles Included in the Systematic Review. Author (year) Study Design Population Sample Size (Number of SCLC) Results Conclusion Total Score Niu X. (2010) 21 Case-control Han Chinese 1,096 (42) Risk rs3743073 (CHRNA3) was associated with SCLC risk 6 Shiraishi K. (2009) 22 Case-control Japanese 2,186 (297) Risk rs8034191 (LOC123688), rs1051730 (CHRNA3) and haplotype CAA were associated with SCLC risk. 8 Deng Q. (2013) 23 Case-control Han Chinese and Japanese 8,063 (561)/7,906 (554) Risk rs2282987 (CDK6)/rs2706748 (SH3RF1) were associated with SCLC 8 Cheng Y. (2017) 24 Case-control Chinese 3,255 (178) Risk rs6495304 (HYKK - 15q25) was associated with SCLC risk. 8 Bossé Y. (2020) 20 TWAS European 85,716 (2,664) Risk IREB2 (15q25), CHRNA3 (15q25), HIST1H2BD (6p22.2) and TMA16 (4q32.2) were associated with SCLC risk 10 Hu Z. (2011) 17 GWAS Han Chinese 5,408 (178) Risk/Protective rs465498 (CLPTM1L-5p15.33) protective, rs2736100 (TERT-5p15.33) and rs17728461 (NORMAD2), rs36600 (MTMR3-22q.12.2) risk 10 Brenner D.R. (2015) 25 Meta-analysis European 4,505 (2,216) Risk 15q25 (rs12914385 - CHRNA3 and rs3813565) were associated with SCLC risk. 9 Timofeeva M. (2012) 26 Meta-analysis European 28,400 (1,964)/28,442 (1,969) Risk rs3117582 (6p21.3) and rs1051730 (CHRNA3) were associated with SLCL risk. 9 Han S. (2015) 29 Pooling analysis Han Chinese 1,560 (520) Protective rs7963551 (RAD52 - 12p13.33) was associated with SCLC risk. 9 O´ Brien T.D. (2018) 30 Pooling analysis European 11,587 (678) Risk CHRNA5, PSMA4, RP11-650, L12.2, MYL4 and RPRML were associated with SCLC risk. 9 Truong T. (2010) 28 Pooling analysis N/A 11,703 (1,106) Risk rs16969968 (CHRNA5) was associated with SCLC risk. 9 Improgo Ma.R.D. (2010) 27 Series of cases N/A 123 (7) Risk ASCL1 regulate and overexpress CHRNA5/A3/B4 gene cluster associating it with SCLC risk. 2 Byun J. (2022) 19 Cross-ancestry GWMA European, East Asian and African 70,156 (2,482) Risk rs141178913 (IL17RC) for African and European ancestry and rs191133092 (LINC01556, HCGA15) for African 10 Enjo-Barreiro J.R. (2023) 18 GWAS European 828 (271) Risk/Protective rs47363076 (MAP4), rs47363076 (KLHL18), rs47546915 (ELP6), rs48185972 (CDC25A), rs81020709 (TLE1), rs2397873 (CD81) and rs59440199 (DIAPH3) risk and rs47098239, rs47160943, rs47247614 (HTR2A), rs126519658 (GRAMD2B), rs44750305 (DBF4B) and rs44647003 (LINC01180) protective. 10 Clinical Lung Cancer January 2024 11 Genome Wide Association Studies in Small-Cell Lung Cancer Figure 1 PRISMA flow-diagram. 1 Genome wide meta-analysis, 19 1 transcriptome wide association study (TWAS), 20 4 case-control studies, 21–24 2 meta-analysis, 25 , 26 1 case-series, 27 and 3 pooling analyses. 28-30 The most common exclusion criteria were not including results for SCLC in GWAS performed in lung cancer patients. Ten studies were selected because they were based on previous GWAS for lung cancer. Included Papers Hu et al. 17 analyses, in their GWAS study, the genes implicated in lung cancer for Han Chinese population, including 178 SCLC cases and identifying 3 single nucleotide polymorphism (SNPs) related with an increased risk of SCLC: rs2736100 (TERT), rs17728461 (HORMAD2) and rs36600 (MTMR3) and 1 protective for this histological type: rs465498 (CLPTM1L). Enjo-Barreiro et al. 18 identified, in their GWAS study, several interesting SNPs without reaching the genome-wide significance but bordering it. This study included 271 SCLC cases and has been developed at a radon-prone area, adjusting the analysis by indoor radon exposure. In addition, it is the only one developed for SCLC exclusively. Seven SNPs were identified as risk factors for SCLC: rs47363076 (MAP4), rs47363076 (KLHL18), rs47546915 (ELP6), rs48185972 (CDC25A), rs81020709 (TLE1), rs2397873 (CD81) and rs59440199 (DIAPH3) and 6 as protective: rs47098239, rs47160943, rs47247614 (HTR2A), rs126519658 (GRAMD2B), rs44750305 (DBF4B) and rs44647003 (LINC01180). Byun et al. 19 performed a cross-ancestry genome-wide Metaanalysis (GWMA) including 2482 cases of SCLC among other histological subtypes of lung cancer and controls. Data were validated in combination with an external validation dataset, which added 1297 SCLC cases. This study included cases of European, African, and east Asian ancestry. The rs1411789913 (IL17RC) showed a strong association with SCLC for African and European ancestry case. The rs191133092 (LINC01556, HCG15) was associated with SCLC for African ancestry cases. 12 Clinical Lung Cancer January 2024 José Ramón Enjo-Barreiro et al The TWAS study 20 was performed on a previous GWAS. In this paper 2664 SCLC were included studying the genetic variants in neverand ever-smokers. The results showed a significant association for SCLC for IREB2 and CHRNA3 on 15q25, HIST1H2BD on 6p22.2 and TMA16 on 4q32.2. The 4 case-control studies included analyzed different SNPs for lung cancer, based on previous GWAS, detailing specific results for SCLC. Niu et al. 21 identified that rs3743073, located in CHRNA3 gene, increases SCLC risk in Asian population, and it is also related to NSCLC, that may predict its risk and prognosis in NSCLC advanced stages. 21 Shiraishi et al. 22 observed that rs8034191 (LOC123688), rs1051730 (CHRNA3) and the Haplotype CAA (rs1800624, rs1800625 and rs2070600, located in advanced glycosylation end product-specific receptor [RAGE]), also increase SCLC risk. Deng et al. 23 described an association for rs2282987 (CDK6) and rs2706748 (SH3RF1). Cheng et al. 24 identified rs6495304 (HYKK) as having an association with SCLC. The 3 pooling analysis 28-30 were based in previous GWAS for lung cancer which identified different SNPs which had been studied for different histological subtypes including SCLC. Truong et al. 28 in 2009 performed a pooling analysis of 21 case-control studies. They observed that, for 1,106 SCLC cases, rs16969968 (CHRNA5) showed an OR of 1.21 (95% CI 1.10-1.33). The second study selected 30 was based on the results of a GWAS which obtained the cases and controls from 4 studies, observing that CHRNA5, PSMA4, RP11-650, L12.2, MYL4 and RPRML posed an association with SCLC. On the other hand, Han et al. 29 in 2015 performed another pooling analysis of 2 case-control studies, which included 520 SCLC cases, obtaining as a result that rs7963551 (RAD52 –a DNA repair protein) had a protective role for SCLC in Han Chinese population. One case-series was selected. 27 In this paper the correlation between SCLC and the nicotinic acetylcholine receptors (nAChR) gene cluster was studied based on GWAS evidence, and it was observed, in accordance with previous literature, that this gene cluster is overexpressed and ASCL1 may be the responsible of this deregulation. Regarding the 2 meta-analyses selected, 25 , 26 the one published by Brenner et al. 25 in 2015 was based in 13 lung cancer GWAS that included 2216 SCLC patients, observing that mutations on rs12914385 and rs3813565 at the 15q25 region increased the risk of SCLC. On the contrary, mutations on rs8034191 and rs1051730 had a protective effect on this tumor. Timofeeva et al. 26 found that rs3117582 (6p21.3) increased the risk (OR = 1.16) of SCLC (n = 1964) and rs1051730 (CHRNA3), in contrast with Brenner et al., 25 showed a similar risk (OR = 1.31) for SCLC (n = 1969). On the other hand, rs10849605 (RAD52) had a protective effect (OR = 0.86; 95%CI: 0.80-0.91). Table 3 synthesized the risk of the SNPs or genes of the studies included in the review. This information should be analyzed cautiously due to the different study designs and methodologies. Quality of the Included Studies We included a TWAS, 2 GWAS and a Cross-ancestry GWMA that achieved the highest punctuation based on the items recorded in Table 1 , based on previous reviews. 15 , 16 Two meta-analyses, there pooling of cases and 3 case-control studies achieved the highest score, only limited by the study design. One case-control obtained a score of 6 over 10, due to the scarce number of SCLC included, and the article with lower punctuation is a case series that includes a low number of SCLC, but its results are in accordance with the evidence available. Their quality ranged from 1 to 10 as described in Tables 1 and 2 . Discussion This review of GWAS performed on SCLC patients shows that it is possible that specific genes may be involved in SCLC onset. This is the case of CHRNA3, CHRNA5, or RAD52. These findings might pave the way for the development of drugs directed to certain molecular targets located in those genomic regions. Other relevant result is the lack of information based on GWAS studies on the deadliest histological lung cancer type, which calls to further and ambitious research. SCLC comprises only approximately 15% of all lung cancer cases and this may partially explain the lack of evidence on the causes of its genetic onset when compared to other more frequent histological types. The available studies must have a multicentric nature with a long recruitment period to achieve a high sample size and this explains the low number of participants diagnosed with SCLC included, along with the small number of GWAS with information for SCLC compared to NSCLC studies. Some authors started considering SCLC a heterogeneous disease due to the highly different gene expression. Rudin et al. 9 classified it in 4 groups by key transcription regulators; on the one hand, we have 2 different types of neuroendocrine cancers: the first is when ASCL1 is overexpressed, and in the second NEUROD1 is overexpressed. These 2 transcription factors target different oncogenic genes: ASCL1 targets MYCL1, BCL2, SOX2, and DLL3. On the contrary, NEURO1 acts over MYC, but they also have common targets as INSM1, HES1, an inhibitor of HES1 and a NOTCH mediated repression of ASCL1 transcriptional activity. 9 , 31 The other 2 groups of SCLC do not express neuroendocrine markers such as ASCL1 or NEUROD1 , they are yes-associated protein 1 ( YAP1 ), which is overexpressed in some tumors, and POU class 2 homeobox 3 (POU2F3 ), which suggest that this SCLC may have a different cell origin. 9 However, after Baine et al. 32 immunohistochemical analysis concluded that the role of subtype-defining transcriptional drivers is not well established, authors such as Gay et al. 33 disagree with considering YAP1 overexpression as a single group. In terms of the origin of SCLC, there is a minority of cases of SCLC that are likely to have arisen from an EGFR-mutated NSCLC that has shown resistance to EGRF inhibitors, but this is not exclusive of this mutation. P53 and RB1 downregulations and TERT amplification may also favor this transformation. In relation with the results observed in our review, due to the lack of GWAS specifically developed for SCLC, we ought to include articles focused on expanding the information obtained in previous GWAS developed for lung cancer, including mostly other histological types. Firstly, we observed that ASCL1 is the most common key transcription regulator implicated. It is a gene that codifies a protein identified with the same name, which is overexpressed in this type Clinical Lung Cancer January 2024 13 Genome Wide Association Studies in Small-Cell Lung Cancer Table 3 Risk of the SNPs and Genes Identified by the Studies Included. Author (year) SNPs (Gene) Risk or Probability Niu X. (2010) 21 rs3743073 (CHRNA3) OR = 1.69; 95% CI (1.06-2.70) Shiraishi K. (2009) 22 rs8034191 (LOC123688) OR = 2.0; 95% CI (1.1-3.4) rs1051730 (CHRNA3) OR = 2.6; 95% CI (1.5-4.7) rs1800624, rs1800625 and rs2070600 (RAGE) - Haplotype CAA OR = 2.2; 95% CI (1.0-4.9) Deng Q. (2013) 23 rs2282987 (CDK6) OR = 1.25; 95% CI (1.10-1.43) rs2706748 (SH3RF1) OR = 1.22; 95% CI (1.04-1.44) Cheng Y. (2017) 24 rs6495304 (HYKK) OR = 1.33; 95% CI (1.01-1.77) Bossé Y. (2020) 20 (IREB2) pTWAS = N/A (CHRNA3) pTWAS = 3.51 ×10−5 (HIST1H2BD) pTWAS = 1.54 ×10−6 (TMA16) pTWAS = 4.2 ×10−6 Hu Z. (2011) 17 rs465498 (CLPTM1L) OR = 0.80; 95% CI (0.69-0.93) rs2736100 (TERT) OR = 1.14; 95% CI (1.02-1.27) rs17728461 (NORMAD2) OR = 1.24; 95% CI (1.09-1.41) rs36600 (MTMR3) OR = 1.45; 95% CI (1.24-1.70) Brenner D.R. (2015) 25 rs12914385 (CHRNA3) OR = 1.34; 95% CI (1.24-1.45) rs3813565 (LOC105370913) OR = 1.28; 95% CI (1.18-1.40) Timofeeva M. (2012) 26 rs3117582 (BAG6, APOM) OR = 1.16 ( p = 0.01) rs1051730 (CHRNA3) OR = 1.31 ( p = 3.4 ×10−14 ) Han S. (2015) 29 rs7963551 (RAD52) OR = 0.48; 95% CI (0.33-0.69) O´ Brien T.D. (2018) 30 (CHRNA5) N/A (PSMA4) N/A (RP11-650) N/A (L12.2) N/A (MYL4) N/A (RPRML) N/A Truong T. (2010) 28 rs16969968 (CHRNA5) OR = 1.21; 95% CI (1.10-1.33) Improgo Ma.R.D. (2010) 27 ASCL1 N/A CHRNA5/A3/B4 N/A Byun J. (2022) 19 rs141178913 (IL17RC) EUR: OR = 5.36 ( p = 2.37 ×10−9 ) AFR: OR = 76.69 ( p = 2.37 ×10−9 ) rs191133092 (LINC01556, HCGA15) EUR: OR = 12.56 ( p = 1.52 ×10−8 ) AFR: OR = 5.30 ( p = 1.52 ×10−8 ) Enjo-Barreiro J.R. (2023) 18 rs47363076 (MAP4) OR = 5.19; 95% CI (2.58-10.44) rs2397873 (CD81) OR = 5.75; 95% CI (2.76-11.98) rs47363076 (KLHL18) OR = 4.11; 95% CI (2.33-7.22) rs47546915 (ELP6) OR = 4.51; 95% CI (2.37-8.61) rs48185972 (CDC25A) OR = 3.95; 95% CI (2.23-6.99) rs81020709 (TLE1) OR = 1.96; 95% CI (1.47-2.63) rs59440199 (DIAPH3) OR = 2.52; 95% CI (1.7-3.73) rs47098239 (HTR2A) OR = 0.15; 95% CI (0.07-0.33) rs47160943 (HTR2A) OR = 0.07; 95% CI (0.02-0.21) rs47247614 (HTR2A) OR = 0.12; 95% CI (1.7-3.73) rs44647003 (LINC01180) OR = 0.40; 95% CI (0.28-0.58) rs44750305 (DBF4B) OR = 0.49; 95% CI (0.37-0.65) rs126519658 (GRAMD2B) OR = 0.55; 95% CI (0.42-0.71) Abbreviations: OR = odds ratio; CI = confidence interval; N/A = Not available; EUR = European ancestry; AFR = African ancestry. 14 Clinical Lung Cancer January 2024 José Ramón Enjo-Barreiro et al Figure 2 ASCL1 overexpression in SCLC. ASCL1 = achaete-scute complex homolog-1; nAChR = nicotinic acetylcholine receptors; α3 = nAChR α3 subunit gene; α5 = nAChR α5 subunit gene; β4 = nAChR β4 subunit gene; NNK = 4-(metilnitrosamino)-1-(3-piridil)-1-butanone. of tumor. Improgo et al. 27 described this overexpression in lung cancer patients as an important factor in SCLC pathogenesis, in accordance with Rudin et al. 9 ASCL1 may regulate the gene cluster CHRNA5/A3/B4, especially acting over CHRNA3 and CHRNB4, which in turn regulates the expression of the nAChR, for which acetylcholine is an endogenous ligand with an autocrine growth factor function 27 as it is shown in Figure 2 . In addition, Improgo et al 27 described for SCLC that after the knockdown of ASCL1 , the nicotinic receptors overexpressed in this tumor, diminish their expression, whereas in NSCLC this pattern does not change. As we can observe in the Kyoto Encyclopedia of Genes and Genomes (KEGG), this type of receptors not only interact with nicotine but also with 4-(metilnitrosamino)-1-(3-piridil)-1butanone (NNK), which is classified by the IARC as a carcinogenic chemical compound for humans, which is derived from nicotine and it uses the nAchR to inhibit the apoptotic process, stimulate the angiogenesis and the cell proliferation, contributing to carcinogenesis. It is important that NNK is produced during the combustion of cured tobacco and SCLC is the lung cancer most associated with tobacco consumption. It is difficult to find SCLC never smoking patients 34 and therefore a role related with specific pathways related to nicotine addiction is apparently logical. In relation with CHRNA5/A3/B4 genes cluster, we found several papers 20-22 , 25-28 , 30 relating this overexpression with a higher risk of developing SCLC. The SNP rs16969968 (CHRNA5) was related with an increased risk for SCLC in European and Asian populations in 3 different studies. 21 , 22 , 28 Some of these papers expand to other ethnicities the results obtained for Europeans, such as Niu et al. 21 for Han Chinese and Shiraishi et al. 22 for Japanese, because the mutations identified are less common in Asian population in contrast with Europeans, confirming the association described. Niu et al related rs3743073 (CHRNA3) with an increased risk for SCLC, while Shiraishi et al. 22 related rs8034191 (LOC123688), rs3743073 (CHRNA3) and rs3743073 (CHRNA5). Additionally, Shiraishi et al. 22 observed that patients carrying this haplotype have an increased OR for smokers and nonsmokers, suggesting that the association of these SNPs are independent of the patient smoking status with lung cancer. In agreement with the previous authors, Bossé et al. 20 identified in their TWAS, CHRNA3 (15q25) as a risk for SCLC among other genes like IREB2(15q25), HIST1H2BD (6p22.2) and TMA16 (4q32.2), being the last one, for the first time, associated with lung cancer. Timofeeva et al. 26 observed that rs3117582 (BAG6) on 6p21.3 and rs1051730 (CHRNA3) increase the risk of SCLC. Rs3117582 is in BAG6, a gene encoding BCL2, which is a target of ASCL1, 9 that may affect cellular behavior 35 and plays an important role in p53 apoptosis by genotoxic stress 36 . On the other hand, this metaanalysis identified 3 other SNPs as posing protection for SCLC such as rs401681 (CLPTM1L), rs10849605 (RAD52) and rs6495309 (CHRNA3/CHRNB4). Similarly to Timofeeva et al., 26 Han et al. 29 identified the SNP rs7963551 (RAD52), in a Han Chinese ethnic group, as a protective factor, but it only varies significantly in smokers. This is probably due to RAD52 gene which codifies a protein related with the DNA repair, important in smokers who accumulates more DNA damage. Another gene has been identified in coordination with ASCL1, known as TTF-1, which regulates the expression of Bcl-2, not having relation with the other neuroendocrine molecular type, the Neurogenic differentiation factor 1 (NEUROD1) which is more related with MYC. 37 Most part of these genes identified are in chromosome 15, taking an especial relevance the 15q24 and 15q25.1. Several of the SNPs identified for Shiraishi et al., 22 Bossé et al., 20 or Niu et al. 21 are in the chromosome 15. Consistent with them, Truong et al. 28 identified 3 chromosomal regions at 15q25, 5q15 and 6p21 and Brenner et al. 25 observed this association with the 15q25 region, relating SNPs such as rs12914385 (CHRNA3) and rs3813565 (LOC105370913) with an increased risk for SCLC. On the contrary, they found SNPs with a protective effect rs8034191 (LOC123688) and rs1051730 (CHRNA3), which is in discordance with the data observed in other studies. 21 , 22 , 26 Cheng et al. 24 associated 15q25 with lung cancer too in Han Chinese population. They observed that rs6495304 (HYKK) is a SCLC risk factor, having an important association with smoking habit, with a multiplicative interaction with gender, though this may be due to the different smoking habits among sexes in their study population. Not only genes related with ASCL1 were observed in our revision, O´ Brien et al. 30 identified 5 genes related with SCLC risk, and Clinical Lung Cancer January 2024 15 Genome Wide Association Studies in Small-Cell Lung Cancer some of them overlap other lung cancer histological types, such as CHRNA5, PSMA4, RP11-650 L12.2, MYL4, and RPRML, being the first 2 only associated with lung cancer. 27 It is interesting that this research observed that the focal adhesion pathway has an important role in SCLC, which is relevant in cancer metastasis because it is involved in the epithelial-mesenchymal transition. 38 In addition, Deng et al. 23 identified rs2282987 (CDK6) and rs2706748 (SH3RF1) as a risk factor for SCLC in Chinese Han population. It is remarkable that CDK6 take an important role in carcinogenesis regulating the G1 phase progression 39 and it is known that SH3RF1 is a proapoptotic protein that can interact when an apoptotic stimulus appears. Attending to the unique specific GWAS developed for SCLC and adjusted by indoor radon exposure, 18 CHRNA5/A3/B4 gene cluster or the chromosome 15 were not identified as a risk factor for this histologic subtype, may be due to the small sample. On the other hand, new SNPs were identified like rs47363076 located in Microtubule associated protein 4 (MAP4), being correlated with prognosis in NSCLC patients treated with atezolizumab 40 or rs48185972 located in CDC25A, a gene overexpressed in SCLC samples. 41 In addition to MAP4 and CDC25A, this GWAS relates alterations at the chromosome 3 at rs47363076 located in Kelch like family member 18 (KLHL18) and rs47546915 in elongator acetyltransferase complex subunit 6 (ELP6) adding new SNPs in comparison with other studies included in our review. Byun et al. 19 identified rs141178913 (IL17RC) and rs191133092 (LINC01556, HCG15) as a risk factor for SCLC, both described for the first time. Finally, Hu et al. 17 identified rs2736100 (TERT) as a risk factor for SCLC but Timofeeva et al. 26 and Brenner et al. 25 related it with adenocarcinoma. It is remarkable because the gene TERT overexpression is also related with NSCLC-EGFR mutated transformation into SCLC, predisposing TP53 and RB1 alterations, 10 , 11 , 13 , 42 in congruence with Mc Leer et al. 42 Another SNP identified is rs17728461 (HORMAD2), which was related with NSCLC in Han Chinese population. 43 On the other hand, they identified rs465498 (CLPTM1L) as a protective factor, in contrast with Timofeeva et al. 26 who identified other SNP for this gene as a risk factor. This study has several advantages. To our knowledge, it is the first systematic review focused exclusively on GWAS on SCLC. A further advantage is that we have used common criteria to include different available studies and therefore the studies included share some similar results. Nevertheless, there are some disadvantages, such as the scarce number of specific GWAS for SCLC, which forced us to include studies with different methodologies and designs based on previous lung cancer GWAS that extend the information for SCLC, the low number of women included and the impossibility of differentiating the characteristics of smokers and never-smokers. Another limitation is the heterogeneity of the included studies. Finally, the low sample size in most of these studies may limit the robustness of our results. Conclusion We observed that there is a lack of GWAS performed specifically for SCLC and the results obtained are heterogeneous. The most important cluster of genes found, in accordance with the different studies included, is CHRNA5/A3/B4 but the mechanism for the role of these genes is unclear. It is interesting that in the Kyoto Encyclopedia of Genes and Genome (KEGG) these receptors were found to be overexpressed where nicotine, NNK and NNN acts, involving different routes in SCLC carcinogenesis such as PI3KAkt signaling pathway and MAPK signaling pathway among others. More studies are clearly needed to disentangle the complex genetics of Small Cell Lung Cancer. Among them, it could be interesting to develop studies to validate the different SNPs identified and try to recognize oncogenic routes involving CHARNA5/A3/B4 cluster or chromosome 15. Finally, attending to the SCLC cancer classification, it could be interesting study the routes of the different SCLC groups, especially ASCL1. Disclosure Karl Kelsey is a founder and scientific advisor to Cellintec, which had no role in this research. The other authors declare not to have any conflict of interest. Acknowledgments This work was supported by PI15/01211 –ISCIII – co-financed FEDER . References 1. 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