Abstract
Purpose: Thrombophilia genes contribute to tumorigenesis and thrombotic events in lung cancer, yet current treatments do not incorporate gene-specific strategies for F2, F5, PROS1, and SERPINC1. We evaluated survival in lung cancer patients with thrombophilia mutations.
Materials and Methods: We queried TCGA-LUAD and TCGA-LUSC for primary lung cancers with F2, F5, PROS1, or SERPINC1 mutations. STAR RNA-seq expression was included in univariate and multivariate Cox models comparing patients with versus without thrombophilia mutations, adjusting for age, race, AJCC stage, primary site, treatment type, laterality, and treatment modalities. Hazard ratios with 95% confidence intervals were calculated.
Results: We identified 569 patients with thrombophilia mutations and 850 without. Across all mutations, higher pathologic stage and right-sided tumors were associated with worse survival.
F5 mutations were significantly associated with survival in middle-lobe (HR 1.49, p = 0.028), pleural (HR 1.33, p = 0.006), and upper-lobe (HR 1.20, p = 0.025) cancers. SERPINC1 and PROS1 mutations were associated with improved survival in upper-lobe cancers. Among upper-lobe cancers, African American patients with F5 mutations had worse survival by age at diagnosis (HR 1.01, p = 0.015) and race (HR 1.33, p = 0.024).
Conclusions: Thrombophilia mutations influence lung cancer survival and may help refine gene-targeted therapies.
Keywords: F5, PROS1, SERPINC1, lung cancer, thrombophilia
INTRODUCTION
Lung cancer is a highly invasive cancer that metastasizes rapidly, remaining the second-most common cancer overall in both men and women [1]. Currently, lung cancer is responsible for nearly a quarter of all cancer deaths in the United States and globally [2, 3]. Despite advancements in therapeutic efficacy, lung cancer continues to have a poor prognosis, with a 5-year relative survival rate of just 19% in the United States [4]. This dismal outcome stems largely from late-stage presentation: only about 20% of cases are detected at a localized stage (stage I), for which the 5-year survival is approximately 57% [4]. Low-dose CT (LDCT) screening remains the only modality proven to reduce lung cancer mortality—data from the National Lung Screening Trial demonstrated a 20% relative reduction in lung cancer–specific deaths with three annual LDCT screens versus chest radiography [5]. Current U.S. Preventive Services Task Force guidelines recommend annual LDCT screening for adults 50–80 years of age with a ≥20 pack-year smoking history who currently smoke or have quit within the past 15 years [6]. Screening is not used in low-risk populations and, therefore, prognostic and screening gene markers will be key in reducing mortality for these groups.
Broadly, lung cancer is divided by either small cell or non-small cell lung cancers. Small cell lung cancer (SCLC) represents approximately 15% of all lung cancer diagnoses, and is characterized by rapid growth, early metastasis, and strong association with paraneoplastic syndromes such as Ectopic Cushing Syndrome or Syndrome of Inappropriate Anti-Diuretic Hormone [7]. Non-small cell lung cancers (NSCLC) represent 85% of lung cancer diagnoses, and include subtypes such as adenocarcinoma, squamous cell carcinoma, large cell carcinomas, and carcinoid tumors. These tumors all differ in primary location in the lung, as well as association with patient smoking history and genetic markers.
Genetic markers can provide insight into lung cancer pathophysiology and etiology. Genes involved in coagulation, such as F2, F5, PROS1, and SERPINC1, are of increasing interest in lung cancer research. The F2 gene encodes prothrombin, the precursor to thrombin in the coagulation cascade. In relation to lung cancer, a study by Luo et al. found that the F2 gene was significantly overexpressed in lung adenocarcinoma tumors compared to neighboring normal tissue [8]. The study found that a positive correlation between F2 gene expression and increased migration of regulatory T-cells, neutrophils, and mast cells, which are known mechanisms by which cancer cells create an immunosuppressive microenvironment. Another study by Wang et al. found that thrombin binds to and cleaves EGFR, activating the EGFR/AKT/mTOR signaling pathway and potentially promoting cell proliferation, migration, and chemotherapy resistance [9]. Thrombin activity has also been implicated in tumor growth, angiogenesis, and metastasis through its effects on protease-activated receptors and platelet activation [10]. Ultimately, these studies suggest that aberrant F2 gene mutation and subsequently, thrombin activity are implicated in tumor growth, angiogenesis, and metastasis through its effects on protease-activated receptors and platelet activation.
The F5 gene encodes coagulation Factor V, which serves as a cofactor in the prothrombinase complex. A condition resulting from mutation in this gene, Factor V Leiden, leads to resistance to activated Protein C and predisposes carriers to venous thromboembolism. Cancer-associated thrombosis is a major complication in oncology, as cancer is considered a hypercoagulable physiologic state, and may have an impact on patient’s prognosis [11]. Furthermore, a study by Tinholt et al. found a positive correlation between F5 gene expression and cellular infiltration in breast cancer [12]. Although not directly related to lung cancer, this finding could suggest a relationship between F5 overexpression and the creation of lung cancer microenvironments. Therefore, dysregulation in this gene may influence tumor progression and metastatic potential.
The PROS1 gene encodes Protein S, a cofactor for activated Protein C which inhibits factors V and VIII in the coagulation cascade. Therefore, PROS1 contributes to natural anti-coagulant regulation. Interestingly, a study by Suleiman et al. found that Protein S was significantly overexpressed in lung cancer cells and may play an additional role in tumorigenesis [13]. The study found that Protein S binds to TAM receptors (Tyro3 and MerTK) and activates the Erk, PKB/Akt, p38, and FAK pathways, which are key players in cancer growth, survival, and migration. These studies suggest that a Protein S mutation can disturb the balance between coagulation and fibrinolysis, with potential implications in the generation of tumor-friendly microenvironment in the body, as well as immune system evasion in malignancy.
Likewise, SERPINC1, which encodes antithrombin III, serves a crucial inhibitory role in the coagulation cascade and inflammation. A study by Zhang et al. found a correlation between high SERPINC1 expression and worse overall survival in lung cancer patients [14]. The study found that in vitro, the SERPINC1 gene was involved in the activation of the PI3K/AKT pathway, which resulted in increased cancer growth, microenvironment formation, immunosuppression, and metastasis.
Mutations in F2, F5, PROS1, and SERPINC1 are all clinically linked to thrombotic disorders, including prothrombin G20210A mutation, Factor V Leiden, Protein S deficiency, and antithrombin deficiency, respectively. However, more importantly, these prothrombotic states may contribute to hypercoagulability observed in malignancies, suggesting a dual role in thrombosis and tumor progression. The goal of our research is to assess significant factors in lung cancer outcomes relating to location, age, race, AJCC cancer staging, and treatment modalities among other factors in patients with mutated F2, F5, PROS1, and SERPINC1 genes.
RESULTS
Overall, coagulation-related gene expression demonstrated greater independent prognostic relevance in the comparison cohort than in the mutation cohort. In adjusted analyses, PROS1 and SERPINC1 were associated with improved overall survival in the comparison cohort, whereas F2 and F5 were associated with worse overall survival. In the mutation cohort, none of the evaluated gene counts remained statistically significant after adjustment, although F2 and F5 showed borderline associations with worsened survival. Across models, advanced disease stage and select anatomic tumor sites, particularly pleura, upper lobe of lung location, and middle lobe of lung location, were consistently associated with worse survival.
Univariate Cox proportional hazards analysis
In univariate Cox proportional hazards analyses, the association between coagulation-related gene expression and overall survival differed by cohort. In the comparison cohort, higher F2 gene counts were associated with worse overall survival (HR 1.15, 95% CI 1.09 to 1.21, p < 0.001), as were higher F5 gene counts (HR 1.07, 95% CI 1.03 to 1.11, p < 0.001). In contrast, PROS1 and SERPINC1 were not significantly associated with overall survival in the comparison cohort (Table 1). In the mutation cohort, higher F5 gene counts were associated with worse overall survival (HR 1.05, 95% CI 1.02 to 1.09, p = 0.003), while F2 demonstrated a borderline association that did not meet statistical significance (HR 1.06, 95% CI 1.00 to 1.13, p = 0.053). PROS1 and SERPINC1 were not significantly associated with survival in the mutation cohort (Table 2).
Table 1. Univariate Cox proportional hazards analysis of gene mutations in the comparison group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| PROS1 | 1.02 | [0.97, 1.08] | 0.4 |
| SERPINC1 | 0.92 | [0.83, 1.03] | 0.14 |
| F2 | 1.15 | [1.09, 1.21] | 1.60E-07 |
| F5 | 1.07 | [1.03, 1.11] | 0.0004954 |
Survival analysis of gene expression in comparison group (Univariable).
Table 2. Univariate Cox proportional hazards analysis of gene mutations in the mutation group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| PROS1 | 0.99 | [0.94, 1.05] | 0.7 |
| SERPINC1 | 0.97 | [0.88, 1.06] | 0.5 |
| F2 | 1.06 | [1.00, 1.13] | 0.053 |
| F5 | 1.05 | [1.02, 1.09] | 0.003 |
Survival analysis of gene expression in patients with respective gene mutation (Univariable).
Multivariate Cox proportional hazards analysis
PROS1
In the multivariable model evaluating PROS1, higher gene counts were independently associated with improved overall survival in the comparison cohort (HR 0.94, 95% CI 0.88 to 0.99, p = 0.025) (Table 3). This association was not observed in the mutation cohort, where PROS1 gene counts were not significantly associated with survival after adjustment (HR 0.99, 95% CI 0.94 to 1.05, p = 0.7) (Table 4).
Table 3. Multivariate Cox proportional hazards analysis of survival factors in the PROS1 comparison group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 1.00, 1.01 | 0.3 |
| Gender | |||
| Female | — | — | |
| Male | 1.09 | 0.94, 1.27 | 0.2 |
| Race_new | |||
| White | — | — | |
| Black or african american | 1.06 | 0.78, 1.45 | 0.7 |
| Other | 0.84 | 0.65, 1.10 | 0.2 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.45 | 1.20, 1.77 | <0.001 |
| Stage III | 1.97 | 1.61, 2.40 | <0.001 |
| Stage IV | 1.51 | 1.14, 2.01 | 0.004 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 1.05 | 0.67, 1.65 | 0.8 |
| Middle lobe, lung | 1.46 | 0.96, 2.20 | 0.076 |
| Pleura, NOS | 1.73 | 1.36, 2.19 | <0.001 |
| Upper lobe, lung | 1.28 | 1.06, 1.54 | 0.009 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.41 | 0.76, 2.62 | 0.3 |
| Immunotherapy (Including Vaccines) | 2.26 | 0.83, 6.16 | 0.11 |
| Pleurodesis, NOS | 1.09 | 0.79, 1.51 | 0.6 |
| Radiation | 1.13 | 0.95, 1.35 | 0.2 |
| Targeted Therapy | 1.1 | 0.91, 1.33 | 0.3 |
| Laterality | |||
| Left | — | — | |
| Right | 1.18 | 1.02, 1.38 | 0.026 |
| Counts_PROS1 | 0.94 | 0.88, 0.99 | 0.025 |
Survival analysis of PROS1 in comparison group (Multivariable).
Table 4. Multivariate Cox proportional hazards analysis of survival factors in the PROS1 mutation group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 0.99, 1.01 | >0.9 |
| Gender | |||
| Female | — | — | |
| Male | 1.01 | 0.88, 1.18 | 0.8 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.2 | 0.94, 1.53 | 0.2 |
| Other | 0.85 | 0.67, 1.07 | 0.2 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.89 | 1.59, 2.26 | <0.001 |
| Stage III | 2.12 | 1.76, 2.56 | <0.001 |
| Stage IV | 1.62 | 1.18, 2.22 | 0.003 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 0.72 | 0.49, 1.06 | 0.1 |
| Middle lobe, lung | 1.34 | 0.94, 1.90 | 0.11 |
| Upper lobe, lung | 1.18 | 1.01, 1.39 | 0.034 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.55 | 0.49, 4.91 | 0.5 |
| Immunotherapy (Including Vaccines) | 2.41 | 0.76, 7.59 | 0.13 |
| Pleurodesis, NOS | — | — | |
| Radiation | 1.04 | 0.88, 1.23 | 0.6 |
| Targeted Therapy | 0.98 | 0.81, 1.18 | 0.8 |
| Laterality | |||
| Left | — | — | |
| Right | 1.2 | 1.04, 1.39 | 0.014 |
| Counts | 0.99 | 0.94, 1.05 | 0.7 |
Survival analysis in PROS1 mutation group (Multivariable).
In the comparison cohort, worse overall survival was also associated with stage II disease (HR 1.45, 95% CI 1.20 to 1.77, p < 0.001), stage III disease (HR 1.97, 95% CI 1.61 to 2.40, p < 0.001), and stage IV disease (HR 1.51, 95% CI 1.14 to 2.01, p = 0.004). Among tumor site variables, pleura, NOS was associated with worse survival (HR 1.73, 95% CI 1.36 to 2.19, p < 0.001), as was upper-lobe lung location (HR 1.28, 95% CI 1.06 to 1.54, p = 0.009). Right-sided laterality was also associated with worse survival (HR 1.18, 95% CI 1.02 to 1.38, p = 0.026) (Table 3).
In the mutation cohort, PROS1 was not independently associated with survival, but stage and tumor location remained prognostic. Stage II (HR 1.89, 95% CI 1.59 to 2.26, p < 0.001), stage III (HR 2.12, 95% CI 1.76 to 2.56, p < 0.001), and stage IV disease (HR 1.62, 95% CI 1.18 to 2.22, p = 0.003) were associated with worse survival. Upper-lobe lung location was also associated with worse survival (HR 1.18, 95% CI 1.01 to 1.39, p = 0.034), as was right-sided laterality (HR 1.20, 95% CI 1.04 to 1.39, p = 0.014) (Table 4).
SERPINC1
In the multivariable model evaluating SERPINC1, higher gene counts were independently associated with improved overall survival in the comparison cohort (HR 0.81, 95% CI 0.71 to 0.93, p = 0.002) (Table 5). In the mutation cohort, SERPINC1 was not significantly associated with survival after adjustment (HR 0.99, 95% CI 0.94 to 1.05, p = 0.7) (Table 6).
Table 5. Multivariate Cox proportional hazards analysis of survival factors in the SERPINC1 comparison group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 1.00, 1.01 | 0.3 |
| Gender | |||
| Female | — | — | |
| Male | 1.1 | 0.95, 1.28 | 0.2 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.24 | 0.90, 1.70 | 0.2 |
| Other | 0.85 | 0.65, 1.10 | 0.2 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.43 | 1.18, 1.74 | <0.001 |
| Stage III | 1.85 | 1.51, 2.25 | <0.001 |
| Stage IV | 1.42 | 1.07, 1.88 | 0.016 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 1.03 | 0.66, 1.62 | 0.9 |
| Middle lobe, lung | 1.55 | 1.03, 2.35 | 0.036 |
| Pleura, NOS | 1.81 | 1.42, 2.30 | <0.001 |
| Upper lobe, lung | 1.32 | 1.10, 1.59 | 0.003 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.35 | 0.73, 2.50 | 0.3 |
| Immunotherapy (Including Vaccines) | 2.41 | 0.88, 6.59 | 0.086 |
| Pleurodesis, NOS | 1.09 | 0.79, 1.50 | 0.6 |
| Radiation | 1.15 | 0.97, 1.36 | 0.12 |
| Targeted Therapy | 1.11 | 0.92, 1.35 | 0.3 |
| Laterality | |||
| Left | — | — | |
| Right | 1.17 | 1.01, 1.36 | 0.038 |
| Counts_SERPINC1 | 0.81 | 0.71, 0.93 | 0.002 |
Survival analysis of SERPINC1 in comparison group (Multivariable).
Table 6. Multivariate Cox proportional hazards analysis of survival factors in the SERPINC1 mutation group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 0.99, 1.01 | >0.9 |
| Gender | |||
| Female | — | — | |
| Male | 1.01 | 0.88, 1.18 | 0.8 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.2 | 0.94, 1.53 | 0.2 |
| Other | 0.85 | 0.67, 1.07 | 0.2 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.89 | 1.59, 2.26 | <0.001 |
| Stage III | 2.12 | 1.76, 2.56 | <0.001 |
| Stage IV | 1.62 | 1.18, 2.22 | 0.003 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 0.72 | 0.49, 1.06 | 0.1 |
| Middle lobe, lung | 1.34 | 0.94, 1.90 | 0.11 |
| Upper lobe, lung | 1.18 | 1.01, 1.39 | 0.034 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.55 | 0.49, 4.91 | 0.5 |
| Immunotherapy (Including Vaccines) | 2.41 | 0.76, 7.59 | 0.13 |
| Pleurodesis, NOS | — | — | |
| Radiation | 1.04 | 0.88, 1.23 | 0.6 |
| Targeted Therapy | 0.98 | 0.81, 1.18 | 0.8 |
| Laterality | |||
| Left | — | — | |
| Right | 1.2 | 1.04, 1.39 | 0.014 |
| Counts | 0.99 | 0.94, 1.05 | 0.7 |
Survival analysis in SERPINC1 mutation group (Multivariable).
In the comparison cohort, stage remained strongly associated with survival. Stage II (HR 1.43, 95% CI 1.18 to 1.74, p < 0.001), stage III (HR 1.85, 95% CI 1.51 to 2.25, p < 0.001), and stage IV disease (HR 1.42, 95% CI 1.07 to 1.88, p = 0.016) were each associated with worse overall survival. Several specific tumor sites were also associated with inferior survival, including middle lobe lung location (HR 1.55, 95% CI 1.03 to 2.35, p = 0.036), pleura, NOS (HR 1.81, 95% CI 1.42 to 2.30, p < 0.001), and upper-lobe lung location (HR 1.32, 95% CI 1.10 to 1.59, p = 0.003). Right-sided laterality was also associated with worse survival (HR 1.17, 95% CI 1.01 to 1.36, p = 0.038) (Table 5).
In the mutation cohort, SERPINC1 did not retain independent prognostic significance. However, stage II (HR 1.89, 95% CI 1.59 to 2.26, p < 0.001), stage III (HR 2.12, 95% CI 1.76 to 2.56, p < 0.001), and stage IV disease (HR 1.62, 95% CI 1.18 to 2.22, p = 0.003) were associated with worse survival. Upper lobe lung location (HR 1.18, 95% CI 1.01 to 1.39, p = 0.034) and right-sided laterality (HR 1.20, 95% CI 1.04 to 1.39, p = 0.014) were also associated with worse survival (Table 6).
F2
In the multivariable model evaluating F2, higher gene counts were independently associated with worse overall survival in the comparison cohort (HR 1.16, 95% CI 1.10 to 1.23, p < 0.001) (Table 7). In the mutation cohort, F2 gene counts did not meet statistical significance after adjustment, although the association approached significance (HR 1.07, 95% CI 1.00 to 1.14, p = 0.051) (Table 8).
Table 7. Multivariate Cox proportional hazards analysis of survival factors in the F2 comparison group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1.01 | 1.00, 1.02 | 0.14 |
| Gender | |||
| Female | — | — | |
| Male | 1.12 | 0.96, 1.31 | 0.14 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.11 | 0.81, 1.50 | 0.5 |
| Other | 0.89 | 0.68, 1.16 | 0.4 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.4 | 1.15, 1.71 | <0.001 |
| Stage III | 1.85 | 1.51, 2.25 | <0.001 |
| Stage IV | 1.4 | 1.06, 1.86 | 0.02 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 1.13 | 0.72, 1.77 | 0.6 |
| Middle lobe, lung | 1.69 | 1.12, 2.56 | 0.013 |
| Pleura, NOS | 1.77 | 1.41, 2.23 | <0.001 |
| Upper lobe, lung | 1.3 | 1.08, 1.56 | 0.006 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.17 | 0.63, 2.18 | 0.6 |
| Immunotherapy (Including Vaccines) | 2.17 | 0.80, 5.91 | 0.13 |
| Pleurodesis, NOS | 1.05 | 0.76, 1.44 | 0.8 |
| Radiation | 1.09 | 0.91, 1.29 | 0.4 |
| Targeted Therapy | 1.05 | 0.86, 1.27 | 0.7 |
| Laterality | |||
| Left | — | — | |
| Right | 1.16 | 1.00, 1.35 | 0.047 |
| Counts_F2 | 1.16 | 1.10, 1.23 | <0.001 |
Survival analysis of F2 in comparison group (Multivariable).
Table 8. Multivariate Cox proportional hazards analysis of survival factors in the F2 mutation group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 0.99, 1.01 | >0.9 |
| Gender | |||
| Female | — | — | |
| Male | 0.96 | 0.78, 1.18 | 0.7 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.06 | 0.79, 1.41 | 0.7 |
| Other | 1.39 | 0.98, 1.96 | 0.065 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.85 | 1.46, 2.35 | <0.001 |
| Stage III | 2.19 | 1.68, 2.84 | <0.001 |
| Stage IV | 1.6 | 1.02, 2.50 | 0.04 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 0.88 | 0.53, 1.45 | 0.6 |
| Middle lobe, lung | 1.33 | 0.81, 2.19 | 0.3 |
| Upper lobe, lung | 1.2 | 0.97, 1.49 | 0.092 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.11 | 0.26, 4.79 | 0.9 |
| Immunotherapy (Including Vaccines) | 1.5 | 0.47, 4.83 | 0.5 |
| Pleurodesis, NOS | — | — | |
| Radiation | 0.86 | 0.68, 1.09 | 0.2 |
| Targeted Therapy | 0.86 | 0.66, 1.12 | 0.3 |
| Laterality | |||
| Left | — | — | |
| Right | 1.24 | 1.01, 1.51 | 0.04 |
| Counts | 1.07 | 1.00, 1.14 | 0.051 |
Survival analysis in F2 mutation group (Multivariable).
In the comparison cohort, worse overall survival was associated with stage II disease (HR 1.40, 95% CI 1.15 to 1.71, p < 0.001), stage III disease (HR 1.85, 95% CI 1.51 to 2.25, p < 0.001), and stage IV disease (HR 1.40, 95% CI 1.06 to 1.86, p = 0.02). Several tumor sites were associated with worse survival, including middle lobe lung location (HR 1.69, 95% CI 1.12 to 2.56, p = 0.013), pleura, NOS (HR 1.77, 95% CI 1.41 to 2.23, p < 0.001), and upper-lobe lung location (HR 1.30, 95% CI 1.08 to 1.56, p = 0.006). Right-sided laterality was also associated with worse survival (HR 1.16, 95% CI 1.00 to 1.35, p = 0.047) (Table 7).
In the mutation cohort, F2 was not independently associated with survival after adjustment.
Stage remained the dominant prognostic feature, with stage II (HR 1.85, 95% CI 1.46 to 2.35, p < 0.001), stage III (HR 2.19, 95% CI 1.68 to 2.84, p < 0.001), and stage IV disease (HR 1.60, 95% CI 1.02 to 2.50, p = 0.04) associated with worse survival. Right-sided laterality was also associated with worse survival (HR 1.24, 95% CI 1.01 to 1.51, p = 0.04). Upper-lobe lung location demonstrated a trend toward worse survival but did not reach statistical significance (HR 1.20, 95% CI 0.97 to 1.49, p = 0.092) (Table 8).
F5
In the multivariable model evaluating F5, higher gene counts were independently associated with worse overall survival in the comparison cohort (HR 1.04, 95% CI 1.00 to 1.09, p = 0.032) (Table 9). In the mutation cohort, F5 gene counts were not significantly associated with survival after adjustment (HR 1.03, 95% CI 1.00 to 1.07, p = 0.072) (Table 10).
Table 9. Multivariate Cox proportional hazards analysis of survival factors in the F5 comparison group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1 | 1.00, 1.01 | 0.3 |
| Gender | |||
| Female | — | — | |
| Male | 1.11 | 0.95, 1.29 | 0.2 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.13 | 0.83, 1.54 | 0.4 |
| Other | 0.83 | 0.64, 1.07 | 0.2 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.43 | 1.17, 1.74 | <0.001 |
| Stage III | 1.85 | 1.51, 2.26 | <0.001 |
| Stage IV | 1.46 | 1.10, 1.93 | 0.009 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 1.06 | 0.68, 1.66 | 0.8 |
| Middle lobe, lung | 1.6 | 1.06, 2.43 | 0.027 |
| Pleura, NOS | 1.56 | 1.24, 1.96 | <0.001 |
| Upper lobe, lung | 1.29 | 1.07, 1.55 | 0.006 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.41 | 0.76, 2.62 | 0.3 |
| Immunotherapy (Including Vaccines) | 2.24 | 0.82, 6.11 | 0.11 |
| Pleurodesis, NOS | 1.11 | 0.80, 1.53 | 0.5 |
| Radiation | 1.15 | 0.96, 1.36 | 0.12 |
| Targeted Therapy | 1.1 | 0.91, 1.33 | 0.3 |
| Laterality | |||
| Left | — | — | |
| Right | 1.18 | 1.02, 1.37 | 0.03 |
| Counts_F5 | 1.04 | 1.00, 1.09 | 0.032 |
Survival analysis of F5 in comparison group (Multivariable).
Table 10. Multivariate Cox proportional hazards analysis of survival factors in the F5 mutation group.
| Characteristic | HR | 95% CI | p-value |
|---|---|---|---|
| Age_at_diagnosis | 1.01 | 1.00, 1.02 | 0.015 |
| Gender | |||
| Female | — | — | |
| Male | 1.03 | 0.90, 1.18 | 0.7 |
| Race_new | |||
| White | — | — | |
| Black or African American | 1.33 | 1.04, 1.71 | 0.024 |
| Other | 0.84 | 0.66, 1.06 | 0.14 |
| Stage | |||
| Stage I | — | — | |
| Stage II | 1.69 | 1.43, 1.99 | <0.001 |
| Stage III | 1.9 | 1.60, 2.26 | <0.001 |
| Stage IV | 1.67 | 1.31, 2.13 | <0.001 |
| Tissue_or_organ_of_origin | |||
| Lower lobe, lung | — | — | |
| Lung, NOS | 0.81 | 0.58, 1.14 | 0.2 |
| Middle lobe, lung | 1.49 | 1.04, 2.13 | 0.028 |
| Pleura, NOS | 1.33 | 1.08, 1.64 | 0.006 |
| Upper lobe, lung | 1.2 | 1.02, 1.41 | 0.025 |
| Treatment_type2 | |||
| Chemotherapy | — | — | |
| Ancillary Treatment | 1.46 | 0.83, 2.56 | 0.2 |
| Immunotherapy (Including Vaccines) | 2.02 | 0.75, 5.45 | 0.2 |
| Pleurodesis, NOS | 1.11 | 0.83, 1.48 | 0.5 |
| Radiation | 1.05 | 0.90, 1.22 | 0.6 |
| Targeted Therapy | 0.97 | 0.82, 1.15 | 0.7 |
| Laterality | |||
| Left | — | — | |
| Right | 1.13 | 0.99, 1.28 | 0.072 |
| Counts | 1.03 | 1.00, 1.07 | 0.072 |
Survival analysis in F5 mutation group (Multivariable).
In the comparison cohort, stage II (HR 1.43, 95% CI 1.17 to 1.74, p < 0.001), stage III (HR 1.85, 95% CI 1.51 to 2.26, p < 0.001), and stage IV disease (HR 1.46, 95% CI 1.10 to 1.93, p = 0.009) were associated with worse overall survival. Middle-lobe lung location (HR 1.60, 95% CI 1.06 to 2.43, p = 0.027), pleura, NOS (HR 1.56, 95% CI 1.24 to 1.96, p < 0.001), and upper-lobe lung location (HR 1.29, 95% CI 1.07 to 1.55, p = 0.006) were also associated with worse survival. Right-sided laterality was similarly associated with worse survival (HR 1.18, 95% CI 1.02 to 1.37, p = 0.03) (Table 9).
In the mutation cohort, F5 gene counts did not retain statistical significance after multivariable adjustment. However, several clinical and tumor-related features were independently associated with worse survival. These included increasing age at diagnosis (HR 1.01, 95% CI 1.00 to 1.02, p = 0.015), Black or African American race (HR 1.33, 95% CI 1.04 to 1.71, p = 0.024), stage II disease (HR 1.69, 95% CI 1.43 to 1.99, p < 0.001), stage III disease (HR 1.90, 95% CI 1.60 to 2.26, p < 0.001), and stage IV disease (HR 1.67, 95% CI 1.31 to 2.13, p < 0.001). Tumor site was also prognostic, with middle lobe lung location (HR 1.49, 95% CI 1.04 to 2.13, p = 0.028), pleura, NOS (HR 1.33, 95% CI 1.08 to 1.64, p = 0.006), and upper lobe lung location (HR 1.20, 95% CI 1.02 to 1.41, p = 0.025) associated with worse overall survival. Right-sided laterality showed a borderline association but did not meet statistical significance (HR 1.13, 95% CI 0.99 to 1.28, p = 0.072) (Table 10).
DISCUSSION
This is the first study to our knowledge to assess overall survival factors in mutated F2, F5, PROS1, and SERPINC1 genes in lung cancer. F5, SERPINC1, and PROS1 were significant primarily in the upper lobe of the lung. This finding may be attributed to the anatomical differences between the upper lobe and lower lobe of the lungs. Medical literature has found a non-uniform oxygenation levels throughout the lungs, with the upper lobe having the highest level of oxygenation. The ventilation-perfusion (V/Q) ratio for the apex of the lung is approximately 3.0, which can be explained by a decreased ventilation and a severely decreased perfusion [15, 16]. As a result, the upper lobe of the lungs has higher exposure to oxygen and lower blood perfusion. This difference predisposes the upper lobe to increased oxidative stress and cellular damage [16]. Mutations in F5, SERPINC1, and PROS1 genes may contribute to further oxidative stress or the creation of hypoxic environments via thrombogenesis, ultimately leading to cellular damage and tumor genesis.
Given the role of these genes in modulating parts of the coagulation pathway and overall, coagulability, it may be plausible that the worse survival is accounted for by increased thrombotic events. Although this database does not account for these types of events, this should be considered, especially for loss of function mutations. Recent studies have shown venous thromboembolism to be a predictor of early mortality in non-small cell lung carcinoma patients [17]. Interestingly, younger lung cancer patients appear to be more at risk for thromboembolic events [18]. Future studies may want to explore these genes by age to further elucidate differences in survival.
Pathologic stage was consistently and strongly associated with worse survival in every gene.
Furthermore, different genetic mutations were more prevalent in tumors of different locations.
Tumors affecting the middle lobe, pleura, and upper lobe of the lung were more likely to express F5 gene mutations. Comparatively, tumors affecting the upper lobe were also more likely to express mutations in SERPINC1 and PROS1. Mutations in all genes studied, SERPINC1, F5, F2, PROS1, were more likely to yield a worse outcome when present in cancers of the right lung compared to the left lung.
Interestingly, unlike the other aforementioned genes involved in thrombotic disorders, F5 mutations appear to disproportionally affect survival based off the patients’ ethnicity. Of particular concern, from the multivariate hazards analysis, F5 is found to have a noticeably worse significant hazards ratio (HR 1.33, [1.04, 1.71] 95% CI) for African Americans within the mutation group in relation to the comparison group (HR 1.13, [0.83, 1.54] 95% CI). It is well researched that Factor V Leiden is most commonly found in patients of European Caucasian descent and less prevalent in African American patients, subsequently presenting as a lower risk gene mutation in the African American population for venous thromboembolism [19]. However, findings within our study illustrate the need for better understanding and investigation of the associated risks and mechanisms of F5 mutations within African American populations, especially with consideration of the gene’s interplay with lung cancers.
Moreover, the F5 gene, distinctive from the other genes, possesses a slightly worse hazards ratio (HR 1.01, [1.00, 1.02] 95% CI) for age of diagnosis that is statistically significant within the mutations group in contrast to the comparison group. In turn, the relation and severity of the negative impact of F5 mutations on lung cancer patients may be dependent upon the patient’s age at diagnosis, leading to potentially age-differentiated rates of lung cancer survival within patients affected by F5 mutations.
When considering all variables of interest, gene count is observed to be statistically significant within the comparison group of all genes of interest. On the other hand, this variable is found to be insignificant in all mutation groups of each gene. These trends are explained via the structure of the study. Since the study population is split between two groups based on the presence of a gene mutation, rather than specifically abnormally lower or higher expression of each thrombotic gene, it can be reasoned that gene count is insignificant within the mutation group due to the averaging of gain and loss-of-function mutations into a lesser extreme expression level. Within the comparison groups, however, the significance of gene count indicates the potential benefit of utilizing identified changes within these genes as a prognostic tool for lung cancers. Further investigation into specifically lower expression and loss-of-function mutations of these genes may be necessary, alongside their side effects.
Clinical implications
The results of this study suggest that African American patients with an F5 mutation may be at increased risk for worse outcomes in lung cancer. Prior studies have discovered unique mutations specific to these populations [20, 21]. However, no studies have looked at the F5 gene. F5 may serve as a future prognostic marker for this population and should be further studied. If future studies confirm this finding, loss of function mutations of the F5 gene may require more aggressive or personalized treatment, especially in African American populations.
Factor V Leiden is an inherited condition caused by a loss of function in the F5 gene. Currently, there are no disease specific guidelines for this population and there are no studies specifically studying this population’s risk of lung cancer. These patients could be at increased risk of worse outcomes and, therefore, should be considered for future studies. If future studies confirm this study’s findings, Factor V Leiden specific guidelines for lung cancer should be considered.
Limitations
This study comes with limitations which should be considered. First, it is retrospective in nature and, therefore, many of the patient variables could not be controlled for such as the type and timing of treatment. Additionally, the study utilized STAR RNA expression counts for each gene. These readings represent a snapshot in time of the patient’s expression and could differ significantly throughout the progression of the cancer. Our study assessed metastasis by AJCC pathologic M which does not indicate the specific site. Site is a major prognostic factor and, therefore, future studies should include metastatic site in their analysis. Lastly, mutations were not separated by type. Therefore, our data included loss of function and gain of function and future studies should separate the two.
MATERIALS AND METHODS
The Cancer Genome Atlas (TCGA) was queried for primary lung cancer patients from the TCGALUAD and TCGA-LUSC projects with mutations in either the PROS1, SERPINC1, F2, or F5 genes.
Additionally, clinical data of a comparison group of all patients from the TCGA-LUAD and TCGALUSC projects were queried. All patients with missing or incomplete data for these variables were excluded. A total of 569 patients met the inclusion and exclusion data for this study. STAR RNA gene expression quantification data of each gene were collected for the mutated and comparison group to be used in this analysis. We compared outcomes for each gene between two groups: patients with mutated PROS1, SERPINC1, F2, or F5 and patients without mutation of these genes. The primary outcomes were hazard ratios.
Patient age at diagnosis, race, AJCC pathologic stage, primary site, treatment type, and laterality data were pulled for the analysis. Treatment types included chemotherapy, ancillary treatment, immunotherapy (including vaccines), pleurodesis, radiation, and targeted therapy. All patients with missing or incomplete data for these variables were excluded. A total of 569 patients in the mutation group and 850 patients in the comparison group met the inclusion and exclusion criteria for this study.
Univariate and multivariate Cox Proportional Hazards Analyses were conducted to assess which variables were most associated with overall survival. Hazard ratios (HR) and 95% confidence intervals were calculated for the analysis.
CONCLUSIONS
Higher pathologic stage is significantly associated with worse survival in all groups. F5 mutations was protective in middle lobe, pleura, and upper lobe primary sites. PROS1 and SERPINC1 mutation were protective in upper lobe primary sites. African Americans with F5 mutations experienced worse survival. Mutations in F5, F2, SERPINC1, and PROS1 were all significantly associated with worse survival in right-sided lung cancer.
ACKNOWLEDGMENTS
The authors would like to thank the Augusta University Hematology and Oncology department for their support and input.
AUTHOR CONTRIBUTIONS
RB: Conceptualization, statistical analysis, writing, editing; AB: writing, editing; HB: writing, editing; RA: writing, editing; DZ: writing, editing; AJ: writing, editing; GR: editing, revision, project oversight and guidance, primary investigator. All authors reviewed and approved the final manuscript prior to submission for publication.
CONFLICTS OF INTEREST
Authors have no conflicts of interest to declare.
FUNDING
No funding was used for this paper.
REFERENCES
- 1.Schabath MB, Cote ML. Cancer Progress and Priorities: Lung Cancer. Cancer Epidemiol Biomarkers Prev. 2019; 28:1563–79. 10.1158/1055-9965.EPI-19-0221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Thandra KC, Barsouk A, Saginala K, Aluru JS, Barsouk A. Epidemiology of lung cancer. Contemp Oncol (Pozn). 2021; 25:45–52. 10.5114/wo.2021.103829. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ridge CA, McErlean AM, Ginsberg MS. Epidemiology of lung cancer. Semin Intervent Radiol. 2013; 30:93–98. 10.1055/s-0033-1342949. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023; 73:17–48. 10.3322/caac.21763. [DOI] [PubMed] [Google Scholar]
- 5.Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD, and National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011; 365:395–409. 10.1056/NEJMoa1102873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Davis EM, Donahue KE, Doubeni CA, Kubik M, Landefeld CS, Li L, Ogedegbe G, et al. , and US Preventive Services Task Force. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021; 325:962–70. 10.1001/jama.2021.1117. [DOI] [PubMed] [Google Scholar]
- 7.Li Y, Li C, Qi X, Yu L, Lin L. Management of small cell lung cancer complicated with paraneoplastic Cushing’s syndrome: a systematic literature review. Front Endocrinol (Lausanne). 2023; 14:1177125. 10.3389/fendo.2023.1177125. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Luo C, Lei M, Zhang Y, Zhang Q, Li L, Lian J, Liu S, Wang L, Pi G, Zhang Y. Systematic construction and validation of an immune prognostic model for lung adenocarcinoma. J Cell Mol Med. 2020; 24:1233–44. 10.1111/jcmm.14719. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Wang T, Shen Z, Yang L, Zhang X, Yu M, Yu S, Zhao B. The coagulation and tumor system are directly linked through the proteolysis and activation of epidermal growth factor receptor by thrombin. Oncogene. 2025; 44:1153–66. 10.1038/s41388-025-03296-1. [DOI] [PubMed] [Google Scholar]
- 10.Falanga A, Marchetti M, Vignoli A. Coagulation and cancer: biological and clinical aspects. J Thromb Haemost. 2013; 11:223–33. 10.1111/jth.12075. [DOI] [PubMed] [Google Scholar]
- 11.Roberts BK, Collado G, Barnes BJ. Role of interferon regulatory factor 5 (IRF5) in tumor progression: Prognostic and therapeutic potential. Biochim Biophys Acta Rev Cancer. 2024; 1879:189061. 10.1016/j.bbcan.2023.189061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tinholt M, Stavik B, Tekpli X, Garred Ø, Borgen E, Kristensen V, Sahlberg KK, Sandset PM, Iversen N. Coagulation factor V is a marker of tumor-infiltrating immune cells in breast cancer. Oncoimmunology. 2020; 9:1824644. 10.1080/2162402X.2020.1824644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Suleiman L, Muataz Y, Négrier C, Boukerche H. Protein S-mediated signal transduction pathway regulates lung cancer cell proliferation, migration and angiogenesis. Hematol Oncol Stem Cell Ther. 2021. [Epub ahead of print]. 10.1016/j.hemonc.2021.11.002. [DOI] [PubMed] [Google Scholar]
- 14.Zhang J, Tang Z, Guo X, Wang Y, Zhou Y, Cai W. Synergistic effects of nab-PTX and anti-PD-1 antibody combination against lung cancer by regulating the Pi3K/AKT pathway through the Serpinc1 gene. Front Oncol. 2022; 12:933646. 10.3389/fonc.2022.933646. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Powers KA, Dhamoon AS. Physiology, Pulmonary Ventilation and Perfusion. In: StatPearls. Treasure Island (FL): StatPearls Publishing. 2026. [PubMed] [Google Scholar]
- 16.Rogers LK, Cismowski MJ. Oxidative Stress in the Lung - The Essential Paradox. Curr Opin Toxicol. 2018; 7:37–43. 10.1016/j.cotox.2017.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Su Y, Huo M, Hua L, Zhang Y, Yi J, Zhang S, Li J, Zhang Y. Association of Venous Thromboembolism and Early Mortality in Patients with Newly Diagnosed Metastatic Non-Small Cell Lung Cancer. Cancer Manag Res. 2021; 13:4031–40. 10.2147/CMAR.S301088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bagchi A, Khan MS, Saraswat A, Ansari A, Nai Q, Iyer V, Hamouda D, Khuder S, Verghese C. Increased Incidence of Thrombotic Complications With Non-small Cell Lung Cancer Necessitates Consideration of Prophylactic Anticoagulation in Young Individuals. Cureus. 2021; 13:e17769. 10.7759/cureus.17769. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Limdi NA, Beasley TM, Allison DB, Rivers CA, Acton RT. Racial differences in the prevalence of Factor V Leiden mutation among patients on chronic warfarin therapy. Blood Cells Mol Dis. 2006; 37:100–6. 10.1016/j.bcmd.2006.06.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Mamdani H, Schwartz AG. Genomic Characterization of NSCLC in African Americans: A Step Toward “Race-Aware” Precision Medicine. J Thorac Oncol. 2020; 15:1800–2. 10.1016/j.jtho.2020.10.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Araujo LH, Lammers PE, Matthews-Smith V, Eisenberg R, Gonzalez A, Schwartz AG, Timmers C, Shilo K, Zhao W, Natarajan TG, Zhang J, Yilmaz AS, Liu T, et al. Somatic Mutation Spectrum of Non-Small-Cell Lung Cancer in African Americans: A Pooled Analysis. J Thorac Oncol. 2015; 10:1430–36. 10.1097/JTO.0000000000000650. [DOI] [PMC free article] [PubMed] [Google Scholar]