Abstract

Background:

   Skin involvement is one of the many clinical manifestations of lung
   cancer patients. However, there are fewer in-depth studies exploring
   the causal relationship between skin rashes and lung cancer subtypes,
   and the causal relationship is unknown. This study aims to explore the
   potential causal relationship between rash development and lung cancer
   diagnosis.

Methods:

   From the Genome-wide Association Studies (GWAS) database, we sourced
   comprehensive data on skin rash, lung cancer, and gene expression
   Quantitative Trait Loci (eQTL). Drawing from this, we conducted a
   comprehensive analysis that integrated Mendelian Randomization (MR),
   protein-protein network analysis, and enrichment analysis to explore
   the causal relationship and potential mechanisms between rash and lung
   cancer.

Results:

   This study reveals an increased risk of rash in small and squamous cell
   lung cancer patients, with odds ratios of 1.08 and 1.26, respectively.
   However, no causal link between rash and lung cancer was found. Genetic
   analysis identified 3 genes positively associated with both conditions
   and 6 negatively associated, suggesting complex genetic interactions.
   Sensitivity analysis did not indicate heterogeneity or pleiotropy.

Conclusions:

   Our study shows that squamous cell lung cancer patients are more likely
   to get skin rashes. But the rash is not directly linked to lung cancer.
   Future research should explore rashes as a therapeutic target and
   prognostic indicator.

   Keywords: Lung cancer, rash, Mendelian randomization, causality,
   bidirectional Mendelian analysis

Introduction

   Skin involvement is a relatively rare occurrence, affecting
   approximately 1% of individuals diagnosed with lung cancer. This
   condition can manifest through various dermatological symptoms, such as
   rash, discoloration, or the development of nodules on the skin’s
   surface. While the rash is not a common symptom of squamous cell
   carcinoma of the lung, in some cases, it may be the only indication
   that the patient has a possibility of a cure.^ [33]1 To date, the basic
   research has scarcely established a connection between paraneoplastic
   rashes and squamous cell lung cancer. However, case report studies have
   suggested a potential link between lung cancer and
   leukocyte-agglutinating vasculitis.^ [34]2 Currently, the underlying
   mechanisms of paraneoplastic rashes associated with pulmonary
   malignancies are not well understood. It is important to consider that
   the observed correlation between lung cancer and the risk of developing
   rashes in observational studies may be influenced by potential
   confounding factors, such as treatment and medication, as well as the
   possibility of reverse causation. Consequently, such studies are unable
   to establish a causal relationship between lung cancer and the risk of
   developing rashes. Mendelian Randomization (MR) represents an
   innovative epidemiological approach that harnesses genetic variants
   (GVs) as instrumental variables (IVs) to elucidate the causal
   relationship between exposures and associated risk
   outcomes.^[35]3,[36]4 On the formation of gametes, GVs inherited from
   the parental generation are randomly allocated to the offspring, which
   reduces the influence of potential environmental confounders and the
   risk of reverse causality bias on their association with the outcome.^
   [37]5 The MR thereby enjoys a unique benefit in offering a more
   trustworthy assessment of causal relationships, a feat that traditional
   observational studies are unable to achieve.^ [38]6 To date, no studies
   have utilized MR to probe the causal relationship between rash and lung
   cancer risk. In our investigation, we explored this potential causal
   link by harnessing a comprehensive genome-wide association study (GWAS)
   database on rash and lung cancer, employing a bidirectional 2-sample MR
   analysis method.

Materials and Methods

Overview of the study design

   For the purpose of this MR analysis, we utilized GWAS data in the form
   of summary statistics extracted from previously published studies. We
   carefully selected single-nucleotide polymorphisms (SNPs) that
   demonstrated a strong association with the exposure in question to
   serve as IVs in order to investigate the causal relationship between
   the risk of lung cancer and the presence of rash. The expression
   quantitative trait loci (eQTL) data set, GWAS data of rash and lung
   cancer, and their subtypes were summarized, MR was performed to screen
   for relevant genes, and the genes related to rash and squamous lung
   cancer collated in the GeneCards database were subjected to Wien
   analysis, Protein-protein network, and enrichment analysis and other
   methods for the prediction of potential genes. These clinical studies
   were a reanalysis of previously collected and published data and
   therefore did not require further ethical approval.

Instrumental variable selection

Genetic variants associated with rash

   The genetic variation information expression of rash genes, 209 088 in
   all (rash GWAS ID:finn-b-R18_RASH_OTHER_NONSPECIFIC_SKIN_ERUPT) was
   downloaded from the GWAS database ([39]https://gwas.mrcieu.ac.uk/)
   ([40]Table 1).

Table 1.

   Detailed information for the data sources in the present study.
   Phenotypes GWAS ID Sample size SNPs Population Link
   Rash finn-b-R18_RASH_OTHER_NONSPECIFIC_SKIN_ERUPT 209088 16 380 436
   European
   [41]https://gwas.mrcieu.ac.uk/datasets/finn-b-R18_RASH_OTHER_NONSPECIFI
   C_SKIN_ERUPT/
   Small-cell lung cancer finn-b-C3_SCLC 218792 16 380 466 European
   [42]https://gwas.mrcieu.ac.uk/datasets/finn-b-C3_SCLC/
   Lung adenocarcinoma ieu-a-965 18336 8 881 354 European
   [43]https://gwas.mrcieu.ac.uk/datasets/ieu-a-965/
   Squamous cell lung cancer ieu-a-989 62467 10 341 529 European
   [44]https://gwas.mrcieu.ac.uk/datasets/ieu-a-989/
   [45]Open in a new tab

   Abbreviations: SNP, single-nucleotide polymorphism.

   According to the selection criteria with a significance threshold of
   P < 1 × 10^−8, we identified 3 loci (rs62402795, rs117461464, and
   rs112237409), and none of the loci were excluded in the linkage
   disequilibrium (LD) analysis due to exceeding the specified threshold
   (r^2 < 0.001). We used these 3 genetic variants to estimate the causal
   impact of rash on the risk of small-cell lung cancer and lung squamous
   cell carcinoma ([46]Table 3). For the evaluation of the causal
   relationship between rash and lung adenocarcinoma, due to the limited
   number of SNPs meeting the genome-wide significance, we obtained a more
   lenient threshold of 18 SNPs (P < 5 × 10^−6, while LD r^2 < 0.001).^
   [47]7 The following SNPs (rs11244410, rs117461464, rs112237409, and
   rs150562837) were not found in the lung adenocarcinoma GWAS database
   and were therefore excluded. Finally, we used the remaining 14 genetic
   variants for MR analysis.

Table 3.

   Mendelian randomization estimates for the causal effect of rash on lung
   cancer risk.
   Exposure Outcome Method nSNP P OR (95% CI)
   Rash Small-cell lung cancer MR-Egger 3 .419936397 4.19 (0.47–37.03)
   Weighted median 3 .232419317 1.58 (0.74–3.67)
   Inverse variance weighted 3 .206946926 1.48 (0.80–2.73)
   Lung adenocarcinoma MR-Egger 14 .224613993 0.96 (0.89–1.02)
   Weighted median 14 .772483544 0.99 (0.92–1.06)
   Inverse variance weighted 14 .124152424 0.96 (0.91–1.01)
   Squamous cell lung cancer MR-Egger 3 .418420039 1.27 (0.89–1.82)
   Weighted median 3 .158235566 1.10 (0.96–1.26)
   Inverse variance weighted 3 .108405784 1.10 (0.98-1.24)
   [48]Open in a new tab

Genome-wide Association Studies summary data on lung cancer

   Summary data for lung cancer were obtained from the publicly available
   GWAS data set, including 62 467 sample size of squamous cell lung
   cancer (data set ID: ieu-a-989), 218 792 sample size of small-cell lung
   cancer (data set ID: finn-b-C3_SCLC) and 18 336 sample size of lung
   adenocarcinoma (data set ID: ieu-a-965) to select strongly associated
   SNPs that could serve as IVs for lung cancer. In the study, the
   significance threshold for squamous cell lung cancer was set at P < 5 ×
   10^−8. To ensure an adequate number of SNPs for MR analysis, the
   P-value cutoff was adjusted to 5 × 10^−7 for lung adenocarcinoma, and
   to 5 × 10^−6 for small-cell lung cancer ([49]Table 1).

Gene expression Quantitative Trait Loci data

   We downloaded gene eQTL IDs for MR analysis from GWAS, and performed
   quality control on the SNPs to obtain IVs to ensure the reliability and
   accuracy of the data analysis. We also used the “TwoSampleMR” R package
   to exclude SNPs with allele inconsistencies and palindromic sequences
   between the 2 samples. The F statistic was used to assess the strength
   of the SNPs and calculate the F statistic to exclude weak instruments
   with an F statistic less than 10.

Mendelian randomization analyses

   To assess the causal relationship and explore specific associated genes
   between rash and lung cancer, this study employed 5 methods: inverse
   variance weighted (IVW), MR-Egger, weighted model (WM), simple mode,
   and weighted median (WME). The IVW estimation is the prevailing and
   fundamental approach in MR analysis, primarily used for estimating
   causal relationships.^ [50]8 This method estimates the specific causal
   relationship of IV as a weighted linear regression slope between the
   exposure factor and the outcome, with the intercept assumed to be zero.
   When the selected SNPs are all valid instruments, IVW can provide
   accurate estimates. In addition, MR-Egger, simple mode, WM, and WME
   were used as supplementary methods, with P < 0.05 considered
   statistically significant. This study follows the relevant EquatorNet
   guidelines—STROBE-MR ([51]Supplementary File 1).

Sensitivity analyses

   To examine potential bias and the influence of IVs on the outcome
   variable, sensitivity analysis was used to be conducted. After the main
   MR analysis, we performed a series of sensitivity, heterogeneity, and
   pleiotropy assessments to ensure that potential biases due to
   heterogeneity and pleiotropy among individual SNPs did not affect our
   MR results. Specifically, we first used the MR-Egger method to
   determine the level of multinomiality in the effect sensitivity
   estimates. Subsequently, we quantified the level of heterogeneity of
   individual SNPs using MR-Egger and IVW methods with Cochran’s Q
   statistic. We then applied a “leave-one-out” approach to assess the
   causal genetic effects of outlier SNPs and to determine whether MR
   estimates were affected by the exclusion of these SNPs. Afterwards, we
   utilized the “mr_pleiotropy_test” function within the “TwoSampleMR” R
   package (which incorporates the MR-Egger intercept method) to assess
   horizontal pleiotropy in the effect estimates. In addition, we
   performed an MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO)
   analysis by removing one or more fold-anomalous SNPs and then rerunning
   the MR analysis to provide adjusted estimates that take into account
   causal genetic associations of outliers.

Protein-protein network and pathway enrichment analysis

   Venn analysis was performed using the online website
   ([52]https://jvenn.toulouse.inra.fr/app/example.html) to identify
   intersecting genes between rash and lung squamous cell carcinoma.
   GeneCards database ([53]http://www.genecards.org) was utilized to
   retrieve genes with rash (score > 6) and lung squamous cell carcinoma
   (score > 75). Then, the gene set was subjected to functional and
   pathway enrichment analyses using the Search Tool for the Retrieval of
   Interacting Genes (STRING) database ([54]https://string-db.org/).^
   [55]9

Results

Causal effect of lung cancer on rash

   Using 9 squamous cell lung cancer-related SNPs (Table S1), we found
   statistically significant evidence of a potential causal impact of
   squamous cell lung cancer on the risk of rash (odds ratio [OR] = 1.26,
   95% confidence interval [CI] = 1.07-1.47, P = .005). In addition,
   similar risk estimates were obtained using MR-Egger regression
   (OR = 1.85, 95% CI = 1.21-2.81, P = .02) and WME approaches (OR = 1.25,
   95% CI = 1.01-1.54, P = .37) ([56]Table 2 and [57]Figure 1B).
   Sensitivity analysis was then conducted to assess for any violations of
   MR results. In the heterogeneity assessment, no heterogeneity was found
   among the SNPs using the IVW method (Cochran’s Q = 6.186, Q df = 8,
   P = .62). The MR-Egger intercept indicated no horizontal pleiotropy
   (Egger intercept = −0.0725, Egger SE = 0.037, P = .09), suggesting the
   aforementioned causal relationship is reliable. Subsequently, the
   MR-PRESSO method results similarly showed no horizontal pleiotropy in
   our MR analysis (P = .67), and no outlier SNPs were detected. Exclusion
   analysis revealed that the estimated effects were not dependent on
   specific SNPs ([58]Figure 1D).

Table 2.

   Mendelian randomization estimates for the causal effect of lung cancer
   on rash risk.
   graphic file with name 10.1177_11795549251341559-img2.jpg
   [59]Open in a new tab

   Abbreviations: CI, confidence interval; OR, odds ratio; SNP,
   single-nucleotide polymorphism.

Figure 1.

   [60]Figure 1.
   [61]Open in a new tab

   Scatter plots and forest plot for causal effects of lung cancer on rash
   risk using 5 MR analysis methods. (A) Scatter plot for UVMR analysis of
   genetically causal relationship between small-cell lung cancer and
   rash. (B) Scatter plot for UVMR analysis of genetically causal
   relationship between squamous cell lung cancer and rash. (C and D)
   Plots for ’leave-one-out’ analysis of causal effect of genetically
   proxied small-cell lung cancer on rash risk (C) and squamous cell lung
   cancer on rash risk (D). The black points denote the causal effect
   estimates of lung cancer and rash after discarding a certain SNP, and
   the black lines signify the corresponding 95% CIs of estimates. The red
   points symbolize the overall causal effect estimate of the small-cell
   lung cancer on rash risk(C) and the overall causal effect estimate of
   the squamous cell lung cancer on rash risk(D) using a set of screened
   SNPs, and the red lines indicate the corresponding 95% CIs of the
   incorporated estimates. SNP, single-nucleotide polymorphism.

   Weak evidence of a potential causal impact of small-cell lung cancer on
   rash risk (OR = 1.08, 95% CI = 1.02-1.14, P = .01) was found with MR
   analysis([62]Figures 1A and [63]C) . However, the IVW analysis method
   did not provide evidence of a causal relationship between small-cell
   lung cancer and rash risk (OR = 1.05, 95% CI = 1.02-1.14, P = .09).
   Similarly, no causal relationship was found with other MR analysis
   methods. ([64]Table 2 and [65]Figure 1A). In the heterogeneity test, no
   heterogeneity was found among the SNPs (Table S2) using the IVW method
   (Cochran’s Q = 16.204, Q df = 8, P = .06) and MR-Egger method
   (Cochran’s Q = 14.979, Q df = 8, P = .06). The level of pleiotropy was
   not significant too (Egger intercept = −0.0465, Egger SE = 0.057,
   P = .44). Similarly, using the MR-PRESSO method for testing, the
   results indicated no horizontal pleiotropy (P = .08) and no outlier
   SNPs were identified. In addition, we used the “leave-one-out” method
   to test if any single SNP had a disproportionate influence on the
   results. However, the “leave-one-out” results have multiple SNPs that
   all span 0, suggesting that the causal link between small-cell lung
   cancer and rash may be driven by an influential SNPs. Therefore, the
   conclusion that small-cell lung cancer may increase the risk of rash
   needs to be further confirmed by larger sample sizes or more studies
   ([66]Figure 1C).

   In our 5 MR models, the estimates of the causal relationship between
   lung adenocarcinoma and rash were consistent. The IVW model with
   Cochran’s Q test did not find heterogeneity, and the MR-Egger intercept
   suggested no directional pleiotropy, indicating that the aforementioned
   causal relationship is reliable. We suggested that lung adenocarcinoma
   does not have a causal effect on the susceptibility to rash.

Causal effects of rash on lung cancer

   The reverse MR analysis showed that no evidence of a causal association
   between rash and lung cancer was found using the IVW analysis method
   when rash was the exposure factor and lung cancer was the outcome
   (small-cell lung cancer: OR = 1.48, 95% CI = 0.80-2.73, P = .21; lung
   adenocarcinoma: OR = 0.96, 95% CI = 0.91-1.01, P = 0.12; Squamous cell
   lung cancer: OR = 1.10, 95% CI = 0.98-1.24, P = .11). Similarly, other
   MR analysis methods found no evidence of a causal association between
   rash and lung cancer risk ([67]Table 3). To ensure the robustness of
   the reverse MR conclusions, we analyzed the SNPs associated with rash
   used in our reverse MR analysis with those associated with smoking and
   body mass index obtained through the literature^[68]10,[69]11 and found
   that the SNPs used in our MR analysis were not associated with either
   smoking or body mass index. Similarly, the sensitivity analysis did not
   reveal heterogeneity and pleiotropy.

Genes causally associated with rash and squamous cell lung cancer

   We obtained datasets for squamous cell lung cancer (GWAS ID: ieu-a-989)
   and rash (GWAS ID: finn-b-R18_RASH_OTHER_NONSPECIFIC_SKIN_ERUPT) from
   the GWAS database. We used eQTL data for 19 943 genes as the exposure
   data and conducted MR analysis. Meanwhile, we selected genes associated
   with squamous cell lung cancer (P < .05) and OR values across the 5
   methods. We found 690 genes associated with squamous cell lung cancer
   and 192 genes associated with rash. There are 19 intersected genes
   shown in [70]Figure 2A and [71]Table 4. Among the 19 intersected genes,
   3 genes (MTX1, THBS3, KIAA1191) were positively associated with
   squamous cell lung cancer and rash, while 6 genes (TTLL3, PMS2, NSUN2,
   IRS1, IER5, GBAP1) were negatively associated with them. The
   interactions of the above 19 intersection genes in terms of
   co-expression, text mining, and protein homology were determined by
   STRING analysis ([72]Figure 2B), as well as their interactions with
   lung squamous cell carcinoma and rash-related genes screened from
   genecards ([73]Figure 2C). In order to explore the biological functions
   and pathways of the genes screened in [74]Figure 2C, Kyoto Encyclopedia
   of Genes and Genomes (KEGG)^[75]12 -[76]14 and Gene Ontology (GO)
   analyses were performed. The KEGG pathways containing overlapping genes
   were Complement and coagulation cascades, systemic lupus erythematosus,
   Prion disease, ertussis, and Amoebiasis ([77]Figure 2D). The GO results
   were divided into 2 functional groups: biological process group (10
   items) and cellular component group (3 items). In [78]Figure 2E, 10
   GO_BP items were screened from the results containing intersecting
   genes according to P-values. Complement activationclassical pathway,
   activation of immune response, humoral immune response, cytolysis,
   leukocyte-mediated immunity, positive regulation of immune response,
   immune effector process, alternative pathway, and regulation of immune
   system process. The groups of cells involved in these genes are divided
   into Membrane attack complex, plasma membrane protein complex, and
   blood microparticle ([79]Figure 2E).

Figure 2.

   [80]Figure 2.
   [81]Open in a new tab

   Genes related to rash and squamous cell lung cancer screened through MR
   analysis and GeneCards database. (A) Venn analysis was performed to
   identify intersecting genes between rash and lung squamous cell
   carcinoma. (B and C) Protein-protein network and pathway enrichment
   analysis. (D) KEGG enrichment scatter plot. The colors of dots
   represent the enrichment significance, and the dot sizes represent the
   gene counts. (E) Bar graph of GO enrichment pathways. BP: Biological
   Process; CC: Cellular Component.

Table 4.

   Intersecting genes of potentially relevant genes for lung squamous
   carcinoma and rash MR results of potentially relevant crossover genes
   for squamous lung cancer and rash.
   Rash Squamous cell lung cancer
   Gene Method nSNP P OR nSNP P OR
   ABHD4 Inverse variance weighted 3 .000585 1.878294 6 .002358 0.828065
   C5 Inverse variance weighted 5 .023201 0.764829 11 .000241 1.112494
   CASP3 Inverse variance weighted 3 .045136 1.206857 6 .001041 0.890515
   GBAP1 Inverse variance weighted 5 .008784 0.796218 10 .000745 0.899397
   HPCAL4 Inverse variance weighted 7 .027913 0.833934 13 .001907 1.082393
   HSPA1 L Inverse variance weighted 3 .000656 0.419922 4 .006672 1.174811
   IER5 Inverse variance weighted 4 .044624 0.841664 7 .033168 0.935331
   IRS1 Inverse variance weighted 3 .015768 0.761719 6 .043745 0.926227
   KIAA1191 Inverse variance weighted 3 .010921 1.322397 6 .001281
   1.134601
   LITAF Inverse variance weighted 4 .004781 1.500747 7 .023258 0.877125
   MTX1 Inverse variance weighted 3 .00679 1.545732 5 .00026 1.297621
   NSFL1C Inverse variance weighted 4 .049358 1.159453 7 .044503 0.951165
   NSUN2 Inverse variance weighted 7 .003966 0.880118 13 .008403 0.946525
   PIP4P2 Inverse variance weighted 3 .034045 0.650709 6 .045471 1.163382
   PMS2 Inverse variance weighted 3 .023108 0.729185 6 .014462 0.876636
   RNF182 Inverse variance weighted 9 .002464 1.156461 18 .020545 0.957
   SERPING1 Inverse variance weighted 4 .020167 0.83802 6 1.94E-05
   1.134843
   THBS3 Inverse variance weighted 6 .016806 1.198035 12 .005306 1.075824
   TTLL3 Inverse variance weighted 3 .021715 0.831584 6 .016719 0.926634
   [82]Open in a new tab

Discussion

   A rash is a clinical manifestation that can be seen in a variety of
   conditions and manifests in a variety of forms. It can be a clinical
   symptom of a certain skin system disease, or it can be a manifestation
   of other system diseases. The causal association between rash and lung
   cancer is unclear. Employing a bidirectional 2-sample Mendelian
   Randomization study design, we posited that SNPs are linked to the
   outcome exclusively via the exposure pathway. In conclusion, our
   analysis revealed convincing associations confirming a significant
   causal relationship between squamous lung cancer and the risk of
   developing a rash. However, statistically significant differences were
   observed only in the WME in the analysis of the association between
   small-cell lung cancer and rash. It is worth noting that in performing
   the Mendelian randomization analysis of small-cell lung cancer and
   rash, our missing IVs exceeded 20%, and this missing proportion may
   lead to biased estimation of causal effects, thus limiting the
   generalizability of the findings and potentially weakening the
   robustness of the causal inference. In light of this, future studies
   may need to add more reliable IVs or explore different study designs to
   further enhance the evidence support for causality. Dermatoses
   associated with malignancy encompass a diverse array of conditions,
   characterized by hyperproliferation and inflammation, disorders arising
   from tumor-derived hormonal or metabolic factors, and autoimmune
   disorders affecting connective tissue, among other manifestations.
   Dermatomyositis exhibits a variety of cutaneous symptoms, yet it is
   particularly distinguished by a heliotrope rash and the presence of
   Gottron’s papules. Typically occurring on the eyelids, the heliotrope
   rash may sometimes be accompanied by swelling. Individuals with
   dermatomyositis, particularly those aged 60 and above, are considered
   to be at an increased risk of developing cancerous tumors. According to
   a population-based investigation, the risk of cancer in male
   dermatomyositis patients was 2.4 times greater than that in the general
   population (95% CI = 1.6-3.6), while for female patients, the risk was
   3.4 times higher (95% CI = 2.4-4.7).^ [83]15 Research has revealed the
   presence of a novel autoantibody that reacts with nuclear proteins of
   155 and 140 kDa in patients with dermatomyositis, and this antibody has
   been linked to the development of malignancies.^ [84]16 Furthermore,
   paraneoplastic syndromes associated with bronchial carcinoma encompass
   a range of manifestations, including endocrine and neurological
   disorders, as well as arthropathy, claudication, and dermatosis.^
   [85]17 Similar to the enigmatic nature of numerous cutaneous
   paraneoplastic phenomena, the precise pathophysiological underpinnings
   remain shrouded in mystery. Yet, a prevailing hypothesis suggests that
   tumors could instigate alterations within the surrounding extracellular
   matrix, which subsequently result in the induction of antigenicity
   within otherwise normal tissues.^ [86]18

   The intricacies of the skin changes induced by lung malignancies remain
   elusive, with research having not yet fully unraveled these mechanisms.
   In contrast to paraneoplastic neurological syndromes, which are
   characterized by immune-mediated damage that can result in neuronal
   death and irreversible functional impairment,^ [87]19 a case has been
   documented where a lung cancer patient experienced a remarkable and
   sustained improvement in their skin symptoms following chemotherapy.
   This improvement was achieved despite the patient’s prior
   non-responsiveness to a range of optimal supportive measures, including
   corticosteroids and phototherapy.^ [88]20

   Cancer-related dermatoses are rare in lung cancer.^ [89]21 Erythema
   gravidarum (EGR) is a rare and dramatic paraneoplastic disorder.^
   [90]21 The rash spreads rapidly, averaging about 1 cm per day,
   beginning on the trunk and then gradually spreading to the extremities.
   Pruritus is particularly prominent in EGR, and patients often have
   peripheral eosinophilia. According to a study, malignancy is present in
   about 70% of patients with EGR.^ [91]22 Lung cancer is the most common
   associated malignancy, accounting for 43% of cases, followed by
   gastric, esophageal, and breast cancers. The exact pathogenesis of EGR
   has not been clarified, but studies have hypothesized that it may be
   related to the similarity of tumor-produced antigens to skin antigens,
   deposition of immune complexes in the skin, and tumor-induced
   alterations in skin antigenicity.^ [92]22 Other associated diseases
   include tuberculosis, erythema filiformis, psoriasis, and connective
   tissue diseases. Fortunately, this usually resolves once the underlying
   malignancy is treated. Studies have shown that patients with a
   combination of other paraneoplastic syndromes, such as neurological
   symptoms caused by small-cell lung cancer, may have a more favorable
   prognosis.^ [93]23 However, another case report^ [94]20 mentioned that
   a patient with early-stage squamous cell lung cancer developed a
   pruritic rash 5 months after radiofrequency ablation therapy, and skin
   biopsy confirmed inflammatory changes. Despite dermatologic treatment,
   the rash did not resolve. Further examination revealed recurrence of
   lung cancer with lung metastasis. After antitumor therapy, the
   patient’s condition was controlled and the rash improved, a situation
   consistent with a previous case study^ [95]1 report. In summary,
   although rash is relatively rare in squamous cell lung cancer, it may
   be the only warning sign of this potentially curable malignancy. When a
   squamous lung cancer patient develops a rash unrelated to the side
   effects of treatment, it may signal a worsening of the disease.

   One crucial benefit of Mendelian analysis over earlier observational
   studies that investigated the link between skin rashes and lung cancer
   is its capacity to eliminate the influence of conventional confounding
   factors, including treatments and medications. Consequently, our
   research successfully navigates around the inherent constraints of
   these observational approaches, firmly establishing squamous cell lung
   cancer as a risk factor for the development of rashes.

   For other types of lung cancer, such as small-cell lung cancer and lung
   adenocarcinoma, we did not find a significant correlation between them
   and the rash. In addition, we used the “stay one” approach and found
   the result that there were multiple SNPs that all spanned 0, suggesting
   that the causal relationship between small-cell lung cancer and rash
   could be driven by an influential SNPs. Although we found some cases of
   small-cell lung cancer-reported dermatomyositis was suspected to be a
   paraneoplastic syndrome associated with small-cell lung cancer.^ [96]24
   However, in our research, the IVW analysis method did not provide
   evidence of a causal relationship between small-cell lung cancer and
   rash risk. We suspected that small-cell lung cancer may increase the
   risk of rash needs to be further confirmed by larger sample sizes or
   more studies. Most of the paraneoplastic skin findings are the result
   of ectopic humoral syndromes, caused by hormone-secreting tumors. While
   some paraneoplastic disorders are inflammatory or proliferative skin
   conditions that can also occur in the absence of associated malignancy.
   We did not find a correlation between lung adenocarcinoma and the rash.
   We surmise the reasons for this result are because the lung
   adenocarcinoma has a low level of inflammation in the body and the
   proportion of hormone-secreting type in adenocarcinoma is relatively
   low.

   In our study, we found statistically significant evidence of a
   potential causal impact of squamous cell lung cancer on the risk of
   rash. Three genes (MTX1, THBS3, KIAA1191) were positively associated
   with squamous cell lung cancer and rash. It is assumed that the
   increased expression of these 3 genes at the cellular level in the body
   will increase the risk of lung squamous cell carcinoma and rash.
   Articles on expression data of the THBS3 gene in kidney cancer were
   mentioned, which may be related to tumor-associated skin
   manifestations,^ [97]25 although it is not specific to skin rash. For
   the KIAA1191 gene, although an article was found on lung metastasis
   from breast cancer,^ [98]26 it was not directly associated with skin
   rash. The KIAA1191 mRNA was present at increased quantities in lung
   metastatic tissues as compared with primary tumors of the breast.
   Modulation of KIAA1191 expression may be relevant to the biology by
   which tumor cells metastasize from the breast to the lung in humans
   with metastatic breast cancer. Six genes (TTLL3, PMS2, NSUN2, IRS1,
   IER5, GBAP1) were negatively associated with squamous cell lung cancer
   and rash. It may suggest that the increased expression of these 6 genes
   will reduce the risk of lung squamous cell carcinoma and rash.

   For clinicians, a rash is a presence of these types of paraneoplastic
   manifestations of squamous cell lung cancer, and it can elicit an
   important indication for the commencement of systemic anticancer
   therapy during palliative setting. Meanwhile, the consideration of rash
   caused by squamous cell lung cancer itself as an important signal for
   assessing the efficacy of lung cancer treatment and disease progression
   will also be an important direction for future research.

   However, there are some limitations. First, all of GWAS’s data comes
   from the European population. Whether the findings we describe are
   consistent in other populations remains to be investigated. Second,
   although the F statistics of genetic variation indicate that no weak
   tools were used, the statistical power of some outcomes is modest. This
   modest strength may be due to insufficient sample size or genetic
   variation, so “false negatives” cannot be completely ruled out.
   Therefore, it is expected that the researchers will have access to
   larger GWAS data to further validate these results.

Conclusion

   Our study found that patients with squamous cell lung cancer have an
   increased risk of developing skin rashes. However, there was no direct
   link between rash and lung carcinogenesis. Future studies should
   consider the role of squamous cell lung cancer in the risk of rash and
   assess its value as a therapeutic target, as well as use lung
   cancer-induced rash as an indicator for assessing treatment efficacy
   and disease progression.

Supplemental Material

   sj-docx-1-onc-10.1177_11795549251341559 – Supplemental material for
   Causal Association Between Lung Cancer and Rash: A Bidirectional
   Mendelian Randomization Study
   [99]sj-docx-1-onc-10.1177_11795549251341559.docx^ (14.2KB, docx)

   Supplemental material, sj-docx-1-onc-10.1177_11795549251341559 for
   Causal Association Between Lung Cancer and Rash: A Bidirectional
   Mendelian Randomization Study by Yang Xiao, Tian-Tian Li, Ming Li Yuan,
   Wen Yin and Jing Zhu in Clinical Medicine Insights: Oncology

Acknowledgments