A retrospective study with whole-exome sequencing of tissue samples: analysis of risk factors in patients of persistent cough following lung segmentectomy
Highlight box
Key findings
• In this retrospective, segmentectomy-predominant cohort (n=20) of non-small cell lung cancer (NSCLC) patients, preoperative cough and somatic mutations in TBC1D2 and SEPT12 [single nucleotide polymorphisms (SNPs)/ insertion/deletions (INDELs) identified by whole-exome sequencing (WES)] were associated with persistent postoperative cough (CAP) in an exploratory comparison (CAP, n=9 vs. non-CAP, n=11).
What is known and what is new?
• CAP impairs postoperative quality of life; clinical risk factors are described but genetic contributors are understudied. This study is among the first to apply WES to airway stump tissue and to nominate TBC1D2 and SEPT12 as candidate CAP-associated genes.
• Provides novel, hypothesis-generating genomic leads linking somatic variation to CAP and a curated dataset to inform validation and mechanistic studies.
What is the implication, and what should change now?
• Results require confirmation in larger, multi-center cohorts with matched normal controls and functional validation before clinical translation.
Introduction
The gold standard for surgical treatment of resectable non-small cell lung cancer (NSCLC) is lobectomy combined with mediastinal lymph node dissection. However, persistent cough occurs in 24.7–50.0% of patients after lobectomy, significantly impairing quality of life (1). Cough after pulmonary resection (CAP) is defined as a dry cough lasting at least 2 weeks postoperatively and is among the most common surgical complications (2). Current studies on the mechanisms of CAP are predominantly single-center and retrospective in nature, often limited by data bias, and there remains considerable debate regarding its pathogenesis and risk factors (3).
Analysis of CAP risk factors after surgery involves multiple indicators. A history of smoking and preoperative lung function—measured by forced expiratory volume in one second (FEV1) and forced vital capacity (FVC)—is critical, as impaired function increases the risk of postoperative complications. Surgical variables, such as the type of resection and intraoperative conditions, directly influence pulmonary outcomes. Postoperative indicators, including chest tube drainage volume and pleural complications, reflect the recovery process. Symptom severity can be quantified using scoring systems such as the visual analogue scale (VAS) and the Cough Symptom Score (CSS), while instruments like the LCQ-MC assess long-term changes in cough-related quality of life. Gastroesophageal reflux, evaluated with the Reflux Disease Questionnaire (RDQ), may also contribute to CAP risk. These parameters assist clinicians in evaluating risk factors and developing preventive strategies (4). A meta-analysis including 19 studies and 4,755 patients demonstrated that younger patients, female sex, preoperative cough, right lung lobectomy, lobectomy, subcarinal and mediastinal lymph node dissection, stapler closure of the bronchial stump, and postoperative gastroesophageal reflux are independent risk factors for post-lobectomy cough (5). However, genetic-level analyses were not performed. Whole-exome sequencing (WES) allows comprehensive detection of single-nucleotide variants and insertions/deletions in coding regions, which are more likely to influence protein function and disease phenotypes (6). In NSCLC, WES has been widely employed to investigate tumor heterogeneity, treatment response, and prognosis (6). In this study, we used WES to explore whether specific gene mutations are associated with persistent postoperative cough (CAP), a relationship not previously reported (7).
To our knowledge, few studies have examined the incidence and risk factors of persistent cough after segmentectomy in NSCLC patients. To better characterize the potential impact of gene mutations on the development of CAP following lung resection, we performed WES on a small, multi-center cohort of 20 patients from multiple hospitals (8). This dataset provides, to date, one of the most detailed analyses of the association between gene mutations and CAP, yielding several novel observations, including preoperative cough and WES-identified mutations in TBC1D2 and SEPT12. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1061/rc).
Methods
Patient selection
From March 2021 to March 2022, a prospective cohort of 20 patients undergoing lung nodule resection via single-port video-assisted thoracoscopic surgery (VATS) was recruited from the Departments of Thoracic Surgery at Shenzhen People’s Hospital and Guangdong Provincial People’s Hospital. The inclusion criteria were: (I) age between 18 and 80 years; (II) underwent single-port VATS for lobectomy, segmentectomy, or wedge resection of the lung; among the segmentectomy cases, specific procedures included resection of segments S1+2 (n=3), S3 (n=2), S6 (n=2), and S9 (n=2); (III) a definitive postoperative pathological diagnosis; (IV) provision of written informed consent prior to surgery; and (V) postoperative pathological diagnosis of non-small-cell lung cancer or benign lung tumor. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Provincial Medical Ethics Committees (ethics Nos. KY-Q-2022-007-01, Guangdong Provincial People’s Hospital; LL-KY-2021851, Shenzhen People’s Hospital). Prior to participation, all patients were provided with detailed information about the study objectives and procedures, and written informed consent for use of clinical data and tissue samples for genetic analysis was obtained. CAP was defined as a dry cough persisting for at least 2 weeks after lung resection. Cough presence and severity were evaluated using the Mandarin Chinese version of the Leicester Cough Questionnaire (LCQ-MC) at 1, 3, and 6 months postoperatively. The exclusion criteria were: (I) use of antitussive medication within two weeks before surgery; (II) conversion to multi-port thoracoscopy or open thoracotomy during surgery, intraoperative blood loss >1,000 mL, or need for reoperation; (III) total lung resection; (IV) refusal to participate in the study; (V) preoperative comorbidities such as cavitary tuberculosis, bronchiectasis, asthma, respiratory infectious diseases, allergic rhinitis, rhinorrhea syndrome, or significant cough symptoms (VAS score >60); (VI) FEV1 <1.0 L/s or FEV1 <60% predicted; (VII) reoperation due to recurrent lung cancer; (VIII) contraindications to thoracoscopic surgery; or (IX) severe postoperative complications, including hemorrhage, severe infection, significant neurological injury, chylothorax, or pulmonary embolism. Known clinical risk factors for postoperative cough (e.g., younger age, female sex, preoperative cough, right lung lobectomy, lobectomy, subcarinal or mediastinal lymph node dissection, and gastroesophageal reflux) were not used as selection criteria to avoid bias, but were collected and analyzed separately in this cohort. Instead, these variables were collected and analyzed to assess their association with CAP in this cohort.
WES sequencing
Total DNA was extracted using the DNeasy Blood and Tissue Kit (QIAGEN). Fragmented DNA was used to construct sequencing libraries with the Covaris M220 Focused-Ultrasound Sonicator (Covaris, MA, USA). Exome capture was performed using either the Human Exome 2.0 Plus kit (Twist Bioscience, CA, USA) or the SureSelect Human All Exon V6 kit (Agilent Technologies, CA, USA). Libraries were sequenced on the Illumina NovaSeq 6000 platform (Illumina, CA , USA) at LC-Bio Technology Co., Ltd. (Hangzhou, China) with paired-end 150 bp reads, followed by bioinformatics analysis. All DNA samples were extracted from postoperative tumor tissue without matched adjacent normal tissue. Consequently, all variants were analyzed as putative somatic mutations, and germline status could not be confirmed, which is a recognized limitation of this study. Gastroesophageal reflux was assessed pre- and postoperatively using the RDQ.
Statistical analysis
Statistical analyses were performed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). Quantitative variables were tested for normality using the Shapiro-Wilk test. Normally distributed variables were compared using the independent-samples t-test, and non-normally distributed variables were compared using the Mann-Whitney U test. Categorical variables were analyzed using the Chi-squared test or Fisher’s exact test, as appropriate. All collected variables, including clinical and surgical factors previously reported as potential CAP risk factors, were first assessed in univariate analyses. Variables with P<0.05 were entered into a multivariate logistic regression model to identify independent associations. A two-sided P<0.05 was considered statistically significant. As this was an exploratory pilot study with a small sample size, no formal correction for multiple comparisons was applied; therefore, the results should be interpreted with caution due to the potential for type I error.
Results
Clinical characteristics of patients
We categorized the 20 NSCLC patients into two groups according to the presence or absence of persistent cough, defined as a dry cough lasting ≥2 weeks postoperatively and assessed at 1, 3, and 6 months using the LCQ-MC. Differences in categorical variables between groups were analyzed using the Chi-square test. Variables examined included sex, presence or absence of comorbidities, family history of cancer, lesion location, postoperative pathological diagnosis, pleural invasion, pathological stage, postoperative pleural effusion, postoperative pneumothorax, postoperative use of cough medication, preoperative cough, and the presence of insertion/deletion (INDEL) or single nucleotide polymorphism (SNP) mutations in the TBC1D2 gene.
Most variables showed P>0.05, indicating no statistically significant differences between the cough and non-cough groups. For example, sex, comorbidity status, family history of cancer, postoperative pathological diagnosis, pleural invasion, pathological stage, postoperative pleural effusion, and postoperative pneumothorax did not differ significantly between groups. In contrast, preoperative cough was significantly associated with postoperative cough (P<0.05). These results suggest that preoperative cough may be a relevant risk factor for postoperative cough, while other tested variables were not significantly associated in this cohort (Table 1). Complete individual patient characteristics, including age, sex, exact pathological stage, type of resection, and adjuvant treatment details, are provided in Table S1.
Table 1
| Variables | CAP (n=9) | Non-CAP (n=11) | P value | χ2 |
|---|---|---|---|---|
| Gender | 0.24 | 1.367 | ||
| Male | 5 | 4 | ||
| Female | 4 | 7 | ||
| Comorbidities | 0.31 | 1.027 | ||
| Without | 4 | 6 | ||
| With | 5 | 5 | ||
| Family history of cancer | 0.58 | 0.304 | ||
| Without | 7 | 9 | ||
| With | 2 | 2 | ||
| Lesion distribution | >0.99 | 0.000 | ||
| Right lung | 5 | 6 | ||
| Left lung | 4 | 5 | ||
| Postoperative pathological diagnosis | 0.58 | 0.304 | ||
| Squamous cell carcinoma | 2 | 3 | ||
| Adenocarcinoma | 7 | 8 | ||
| Pleural invasion | 0.78 | 0.080 | ||
| Without | 7 | 9 | ||
| With | 2 | 2 | ||
| Pathological stage | 0.32 | 0.984 | ||
| Stage I | 7 | 9 | ||
| Stage III | 2 | 2 | ||
| Postoperative pleural effusion | >0.99 | 0.000 | ||
| Without | 4 | 5 | ||
| With | 5 | 6 | ||
| Postoperative pneumothorax | >0.99 | 0.000 | ||
| Without | 2 | 9 | ||
| With | 7 | 2 | ||
| Postoperative use of cough medicine | 0.30 | 1.069 | ||
| No | 3 | 5 | ||
| Yes | 6 | 6 | ||
| Surgery type | 0.892 | 0.003 | ||
| Segmentectomy | ||||
| S1+2 | 2 | 2 | ||
| S3 | 1 | 2 | ||
| S6 | 2 | 2 | ||
| S9 | 1 | 1 | ||
| Lobectomy | ||||
| Perineural invasion (PNI) | 0.436 | 0.606 | ||
| Without | 2 | 10 | ||
| With | 7 | 1 | ||
| Gastroesophageal reflux (RDQ +) | 0.007 | 3.500 | ||
| Yes | 6 | 3 | ||
| No | 3 | 8 | ||
| Chronic bronchitis, asthma, or emphysema (excluded) | ||||
| Preoperative cough | 0.030 | 4.557 | ||
| Yes | 8 | 3 | ||
| No | 1 | 8 |
CAP, cough after pulmonary resection; RDQ, Reflux Disease Questionnaire.
We also compared continuous variables between the two groups, including age, body mass index (BMI), smoking history, tumor size, percent-predicted forced vital capacity (FVC%), number of lymph nodes removed, intraoperative blood loss, anesthesia time, chest tube drainage volume, and duration of chest tube placement. None of these variables showed statistically significant differences (all P>0.05). The number of lymph nodes removed approached significance (P=0.13) but did not reach the threshold for statistical significance (Table 2).
Table 2
| Variables | P value | t |
|---|---|---|
| Age | 0.38 | 0.566 |
| BMI | 0.93 | 0.566 |
| Smoking | 0.28 | 0.566 |
| Size | 0.24 | 0.566 |
| FVC% | 0.41 | 0.566 |
| Lymph nodes removed | 0.13 | 0.566 |
| Intraoperativ bleeding | 0.34 | 0.566 |
| Anaesthesia time | 0.89 | 0.566 |
| Chest tube drainage | 0.817 | 0.566 |
| Chest tube removal time | 0.586 | 0.566 |
BMI, body mass index; FVC%, percent-predicted forced vital capacity.
NSCLC patients with CAP exhibit significantly specific germline mutation INDEL patterns
Postoperative tumor specimens were collected for WES to identify genetic mutations. The incidence of INDEL mutations was higher in the postoperative cough group than in the non-cough group. For example, in the cough group, chromosome 1 mutations occurred nine times, dbSNP rs3217220 was detected once, mutations in the JTB gene were identified twice, and the TA/T allele type was observed five times, and variant allele frequencies (VAF) in the range of 0.48–0.53 occurred three times. Similar mutation patterns were observed for other chromosomes, including chr2, chr4, and chr6 (Table 3). In the non-cough group, chromosome 1 mutations occurred five times, dbSNP rs11337905 appeared twice, the MTF1 gene was mutated three times, and the T/TA allele type occurred three times; additional mutations were recorded for chromosomes such as chr8, chr12, and chr15 (Table 4).
Table 3
| Chromosome and its frequency | dbSNP appearance frequency | Gene with predicted variant effect (occurrence) | Allele type | VAF two types of allele frequency |
|---|---|---|---|---|
| chr1: 9 times; chr2: 12 times; chr4: 2 times; chr6: 5 times; chr9: 8 times; chr10: 3 times; chr11: 4 times; chr12: 5 times; chr15: 4 times; chr16: 3 times; chr17: 4 times; chr18: 5 times; chrX: 6 times |
rs3217220: 1 time; rs35761232: 3 times; rs377528224: 1 time; rs142016242: 3 times; rs140182714: 3 times; rs369622005: 2 times; rs367698876: 1 time; rs55774067: 2 times; rs71402568: 1 time |
JTB: 2 times; DDX1: 3 times; PTGR1: 3 times; SLC9B1P3: 2 times; TBC1D2: 4 times; SPON1: 3 times; MYO1H: 2 times; PRR4: 2 times; NEO1: 4 times; SEPT12: 3 times; SLC16A6: 4 times; TMX3: 3 times; RBBP7: 3 times; WDR44: 2 times; CUL4B: 3 times |
TA,T: 5 times; A,AT: 4 times; CT,C: 2 times; GA,G: 4 times; CAAT,C: 2 times; G,GA: 3 times; AT,A: 3 times; C,CA: 4 times; T,TA: 2 times; G,GT: 2 times; CA,C: 3 times; TA,T: 3 times; GTTT,G: 2 times |
0.48–0.53: 3 times; other: 34 times |
CAP, cough after pulmonary resection; INDEL, insertion/deletion; SNP, single nucleotide polymorphism; VAF, variant allele frequency.
Table 4
| Chromosome and its frequency | dbSNP appearance frequency |
Variant effect predictor gene (and appearance frequency) |
Allele type | VAF two types of allele frequency |
|---|---|---|---|---|
| chr1: 5 times; chr8: 3 times; chr12: 5 times; chr15: 4 times; chr19: 4 times; chrX: 1 time |
rs11337905: 2 times; rs199729083: 3 times; rs35117128: 3 times; rs113859565: 2 times |
MTF1: 3 times; FUT10: 2 times; CCDC42B: 3 times; CRTC3: 3 times; PPFIA3: 4 times |
T,TA: 3 times; GA,G: 2 times; GAA,G: 3 times; CAGA,C: 3 times; A,ATG: 3 times |
0.48–0.53: 0 time; other: 5 times |
CAP, cough after pulmonary resection; INDEL, insertion/deletion; SNP, single nucleotide polymorphism; VAF, variant allele frequency.
NSCLC patients with CAP exhibit significantly specific germline mutation SNP patterns
The incidence of germline mutation SNPs in the postoperative cough population is significantly higher than in the non-coughing population. For example, mutations on chromosome 1 occurred 37 times, the PRAMEF2 gene was mutated 4 times, and the allele type C,T appeared 45 times. Mutations on chromosome 2 occurred 21 times, the CD247 gene appeared 4 times, and the allele type G,A appeared 37 times. For other chromosomes, such as chr3 to chrY, the table also lists the corresponding number of mutations, related genes, allele types, and VAF frequencies. Notably, records for chromosome Y show mutations occurred 4 times, involving multiple genes such as MAP4K2, IGHMBP2, etc. In contrast, the SNP characteristics of the non-coughing population include: mutations on chromosome 1 occurred 33 times, the C1orf222 gene appeared 13 times, and the allele type C,T appeared 19 times. Records for chromosome Y show mutations occurred 4 times, involving multiple genes such as IFI27L1, SNORD115-9, etc., and the allele type A,G appeared 13 times. The number of chromosomal SNP mutations in the samples from the coughing population is generally higher, and there are records of “other range of frequencies” appearing 135 times in the VAF column. The number of chromosomal mutations in the table for the coughing population’s samples is lower. Both populations have records of SNP mutations on chromosome Y, but the gene and VAF frequency records in the coughing population’s samples are more diverse, which may be related to male smoking (Table 5).
Table 5
| Chromosome and its frequency | Variant effect predictor gene (and appearance frequency) |
Allele type | VAF two types of allele frequency |
|---|---|---|---|
| chr1: 33 times; chr2: 14 times; chr3: 8 times; chr5: 2 times; chr6: 2 times; chr7: 6 times; chr8: 18 times; chr11: 12 times; chr12: 8 times; chr14: 4 times; chr15: 10 times; chr17: 4 times; chr19: 36 times; chrX: 6 times; chrY: 4 times |
C1orf222: 13 times; GPR25: 4 times; SDCCAG8: 3 times; GALM: 10 times; FRG2C: 6 times; PLSCR4: 6 times; THSD7A: 4 times; NACAD: 4 times; LPL: 12 times; HR: 4 times; UEVLD: 6 times; ZNF202: 10 times; PRICKLE1: 6 times; GALNT6: 4 times; IFI27L1: 4 times; SNORD115-9: 4 times; MYO1E: 6 times; CRTC3: 4 times; CDC27: 4 times; R3HDM4: 10 times; MAST3: 6 times; PPFIA3: 22 times; SPACA6P: 4 times; NR0B1: 2 times; PABPC1P5: 2 times |
C,T: 19 times; G,A: 21 times; A,T: 6 times; T,C: 7 times; C,G: 10 times; A,G: 13 times |
0.48–0.53: 14 times; others: 69 times |
CAP, cough after pulmonary resection; SNP, single nucleotide polymorphism; VAF, variant allele frequency.
In the non-coughing population samples, the frequency of allele type A,G is relatively high, while in the coughing population, the allele types are more varied (Table 6).
Table 6
| Chromosome and its frequency | Variant effect predictor gene (and appearance frequency) |
Variant effect predictor gene (and appearance frequency) |
Allele type | VAF two types of allele frequency |
|---|---|---|---|---|
| chr1: 37 times; chr2: 21 times; chr3: 25 times; chr4: 9 times; chr6: 18 times; chr7: 21 times; chr9: 21 times; chr10: 8 times; chr11: 14 times; chr12: 10 times; chr14: 21 times; chr15: 14 times; chr16: 2 times; chr17: 14 times; chr18: 14 times; chr19: 14 times; chr20: 14 times; chr21: 7 times; chr22: 6 times; chrY: 4 times |
PRAMEF2: 4 times; CD247: 4 times; TNN: 3 times; SCN9A: 3 times; SNED1: 3 times; ITPR1: 4 times; FAM208A: 3 times; MUC4: 6 times; GPR125: 5 times; HLA-DQA1: 2 times; GLP1R: 6 times; PRIM2: 4 times; TRGC2: 3 times; RELN: 3 times; SVOPL: 3 times; TRBV7-3: 10 times; RP11-104G3.2: 3 times; TBC1D2: 6 times; GABBR2: 10Times; MAP4K2: 6 times; IGHMBP2: 3 times; TAS2R43: 3 times; ANKRD33: 4 times; KRT6C: 3 times; ZFHX2: 6 times; GALC: 6 times; GPR65: 3 times; OR4N4: 4 times; C15orf26: 3 times; MYO1C: 4 times |
NCOR1: 6 times; SPIRE1: 5 times; PSMG2: 5 times; SERPINB10: 3 times; GNA11: 3 times; GDF15: 3 times; ZNF529: 5 times; ZNF567: 3 times; ZBP1: 2 times; TEKT4P2: 4 times; KRTAP10-5: 3 times; SLC9B1P4: 2 times; LINC01663: 2 times; SLC9B1P1: 2 times; CRABP2: 3 times; AC027612.4: 3 times; ANKRD36B: 3 times; ANKRD36C: 3 times; VGLL4: 3 times; SDHAP2: 4 times; CYP21A1P: 2 times; OR11H2: 2 times; OR11H13P: 3 times; DMXL2: 3 times; WASH3P: 4 times; SEPT12: 2 times; QRICH2: 2 times; RRBP1: 2 times; SNRPB2: 2 times; MC3R: 5 times |
C,T: 45 times; G,A: 37 times; T,C: 34 times; A,G: 31 times; C,G: 13 times; A,T: 1 time; G,T: 1 time |
0.48_0.53: 21 times; other: 135 times |
CAP, cough after pulmonary resection; SNP, single nucleotide polymorphism; VAF, variant allele frequency.
SNP mutation sites more frequently observed in the postoperative cough group include: rs10003883, rs10516411, rs1058587, rs10818668, rs10876294, rs10985765 (6/9), rs10798335, rs1143937 (7/9), rs1062235, rs11231869, rs1129214 (8/9), etc.; SNP mutation sites enriched in the postoperative non-coughing population include: rs10417260, rs10500835, rs1061409, rs11123198 (5/7), rs10276748 (6/7), etc.
TBC1D2 and SEPT12 genes exhibit INDEL and SNP mutations in NSCLC patients with CAP
We detected 60 gene mutations in INDEL mutation-positive samples and 15 in SNP mutation positive samples from 20 patients, and analyzed that the association between gene mutation with CAP by the Chi-square test which led to the result that: Notably, both SNP and INDEL mutations in the TBC1D2 and SEPT12 genes were detected in mutation-positive samples. The presence of TBC1D2 INDEL and SNP mutations was significantly associated with CAP (P<0.05) (Table 7).
Table 7
| Variables | CAP (n=9) | Non-CAP (n=11) | P value | χ2 |
|---|---|---|---|---|
| TBC1D2 gene with INDEL patterns | 0.03 | 4.557 | ||
| Yes | 8 | 2 | ||
| No | 1 | 9 | ||
| TBC1D2 gene with SNP patterns | 0.03 | 4.557 | ||
| Yes | 8 | 2 | ||
| No | 1 | 9 |
CAP, cough after pulmonary resection; INDEL, insertion/deletion; SNP, single nucleotide polymorphism.
Overall, these results suggest that the condition of preoperative cough and variations in the TBC1D2 gene was significantly associated with postoperative cough. Although most variables showed no significant differences, the consistent association between preoperative cough and TBC1D2 mutations highlights a potentially valuable diagnostic indicator for postoperative CAP.
Discussion
Persistent cough is a common postoperative complication after lung resection. Studies have shown that CAP can affect the quality of life of patients after surgery, thereby hindering postoperative recovery (9). Some risk factors have been proven to be related to the occurrence of CAP. Wu et al. reported the causes of CAP in a meta-analysis; however, no data on WES were provided (10). Based on our previously published findings, age, female, preoperative cough, right lobe surgery, lobectomy, subcarinal lymph node dissection, mediastinal lymph node dissection, stapler closure of bronchial stump, tracheal surrounding lymph node dissection, and postoperative acid reflux are independent risk factors for CAP. Moreover, through WES testing in patients with NSCLC who developed CAP, we confirmed that genes such as TBC1D2 and SEPT12 are risk factors for the occurrence of CAP. These identified risk factors can be used to build a predictive model to identify high-risk patients. For high-risk patients, preventive measures against CAP should be taken during surgery, and tests such as WES should be carried out after surgery to actively deal with the occurrence of CAP.
The WES provides comprehensive insights into individual genetic backgrounds and may reveal underlying genetic factors contributing to postoperative cough in lung cancer, which helps to reveal the genetic factors affecting postoperative cough (7). Through WES, researchers can identify gene mutations related to postoperative cough, including those that may affect patient prognosis, tumor signaling pathways, and mechanisms, as well as the potential to become new therapeutic targets (3,11).
In our study analysis, we found that the TBC1D2 gene appeared simultaneously in SNP and INDEL mutation-positive samples. The TBC1D2 gene encodes TBC1 domain family member 2, a protein belonging to the family of GTPase-activating proteins (GAPs), which is involved in regulating intracellular Rab GTPase activity of intracellular Rab GTPases, thereby controlling various cellular processes, including endoplasmic reticulum transport, vesicle transport, and cell division (12). In lung cancer, the function and mechanism of TBC1D2 have not been fully elucidated, but studies suggest that it may play a role by affecting the metabolism and proliferation of tumor cells. Some studies have shown that the expression level of TBC1D2 in lung cancer tissue is related to tumor progression and patient prognosis (12,13). For example, reduced expression of TBC1D2 has been implicated in promoting tumor cell invasion and metastatic behavior in lung cancer, suggesting that it may act as a tumor suppressor. In addition, TBC1D2 may affect the survival and proliferation of lung cancer cells by regulating signaling pathways such as the PI3K/AKT or MAPK pathways. However, the specific mechanism of TBC1D2 in lung cancer needs further research to clarify (13,14). Future research may focus on how TBC1D2 affects the biological behavior of lung cancer cells through its GAP activity and whether it can serve as a new therapeutic target. Despite these associations, however, the biological function of these mutations in the pathophysiology of postoperative cough remains speculative. No functional experiments were conducted in this study, and the mechanistic links between TBC1D2/SEPT12 and CAP are not yet validated. Thus, while the associations are intriguing, further functional studies are required to establish causality. Additionally, gastroesophageal reflux is a well-recognized risk factor for postoperative cough. In our cohort, RDQ assessment identified reflux in 5/8 CAP patients versus 2/6 non-CAP patients, supporting its contributory role in CAP pathogenesis.
In addition, another gene, SEPT12, has caught our attention. The SEPT12 gene encodes a member of the SEPT protein family, which plays an important role in cell division, cytoskeleton organization, and tumorigenesis (14,15). SEPT12 is involved in maintaining cell shape and movement by binding to microtubules and F-actin (16). Previous studies have shown that SEPT12 is upregulated in certain lung cancers and correlates with tumor grade and stage (17). These findings suggest that SEPT12 may contribute to tumor development and aggressiveness. Studies have shown that SEPT12 is upregulated in some types of lung cancer and is closely related to tumor grading, staging, and patient prognosis. SEPT12 may promote the development of lung cancer by affecting cell cycle progression, inhibiting apoptosis, and promoting cell proliferation and migration (18). In addition, the phosphorylation of SEPT12 leads to the absence of the sperm’s annulus or sperm ring, which in turn causes defects in sperm motility and may contribute to reduced male fertility (19). However, the specific mechanism of SEPT12 in lung cancer still needs further research. Future research may explore how SEPT12 interacts with other signaling pathways in lung cancer and whether it can be a potential therapeutic target. These insights underscore the need for further functional studies to clarify the role of TBC1D2 in CAP pathogenesis.
In summary, this study identified preoperative cough and the TBC1D2 and SEPT12 genes as risk factors for postoperative CAP through small-sample WES testing across multiple centers. This study also has certain limitations, such as the relatively homogeneous nature of our included population and the small number of participants. Furthermore, with the growing availability of big data, we can conduct comprehensive analyses by integrating multidimensional data, which will better assist in determining the occurrence of CAP. Furthermore, given the number of statistical comparisons and the lack of adjustment for multiple testing, there is a risk of false-positive findings (type I error), and the associations reported here should be viewed as preliminary. In the future, we will further validate relevant factors by expanding the population sample, and use machine learning to construct detection models to achieve accurate prediction and auxiliary diagnosis of postoperative cough. Given the limited sample size, our study is exploratory in nature, and the findings, which should be considered as hypothesis-generating rather than definitive. Larger, multi-center prospective studies are needed to confirm the associations observed here.
Conclusions
In this exploratory, segmentectomy-predominant cohort of NSCLC patients, we found that preoperative cough and somatic mutations in the TBC1D2 and SEPT12 genes were significantly associated with persistent postoperative cough (CAP). These results suggest that genetic profiling via WES could help identify individuals at higher risk of CAP. Given the limited sample size and lack of functional validation, our findings are hypothesis-generating and warrant confirmation in larger, multi-center prospective studies. Upon validation, these genetic signatures may contribute to the development of individualized risk stratification models and guide preventive strategies for postoperative CAP. Future work should integrate matched normal controls and mechanistic experiments to clarify the molecular mechanisms linking these mutations to postoperative cough.
Acknowledgments
We gratefully acknowledge the valuable assistance of Olivia Bennett and Dr. Qi-Wang, a native English-speaking medical editor, for professional English editing.
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1061/rc
Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1061/dss
Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1061/prf
Funding: The study was supported by
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1061/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Provincial Medical Ethics Committees (ethics Nos. KY-Q-2022-007-01, Guangdong Provincial People’s Hospital; LL-KY-2021851, Shenzhen People’s Hospital). Prior to participation, all patients were provided with detailed information about the study objectives and procedures, and written informed consent for use of clinical data and tissue samples for genetic analysis was obtained.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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