Genomic Features and Prognostic Biomarkers of Chinese Resectable Lung Adenocarcinoma Patients with a Micropapillary Component

doi:10.21203/rs.3.rs-3445545/v1

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Genomic Features and Prognostic Biomarkers of Chinese Resectable Lung Adenocarcinoma Patients with a Micropapillary Component

https://doi.org/10.21203/rs.3.rs-3445545/v1

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Background

Lung adenocarcinoma (LADC) with a micropapillary component (MPC) (LMPC) is an aggressive histologic subtype of lung cancer, with unique pathological features and poor prognosis. Previous studies have characterized the driver mutations in LMPC, however, its comprehensive molecular profile and prognosis-related biomarkers in the Chinese population remain elusive.

Methods

We retrospectively studied 54 stage I-III LMPC patients who underwent complete resection and the LMPC tumor samples were characterized using broad-panel next-generation sequencing (NGS) of 425 cancer-related genes. The association among clinicopathologic factors, genomic characteristics, and post-operation recurrence risk were then explored.

Results

When compared with a reference cohort of 113 LADC patients, LMPC exhibited a unique genetic profile, with more diverse targetable mutations, an increased number of oncogenic pathways altered (NPA), and more oncogenic pathway-related alterations. The mutation frequencies of ERBB4 (11.1% vs. 1.8%, P = 0.015), BRAF (9.3% vs. 1.8%, P = 0.037), PIK3CA (14.8% vs. 4.4%, P = 0.029), RPTOR (P = 0.033), and NOTCH2 (P = 0.033) were significantly higher in LMPC. Moreover, LMPC patients harbored significantly more alterations in three oncogenic pathways (i.e., PI3K, WNT, and TGF-β) and a significantly increased NPA(P < 0.001). By analyzing the correlations between genetic features and median disease-free survival (mDFS) in stage II-III LMPC patients, SMARCA4 mutations (13.9 months vs. Not reached (NR), P = 0.013), as well as alterations in the SWI/SNF (16.3 months vs.NR, P = 0.003) and NRF2 (17.0 monthsvs.NR, P = 0.046) pathways, were significantly associated with higher postoperative recurrence risk. Furthermore, tumor mutation burden (TMB) was significantly correlated with postoperative DFS, with low TMB patients associating with prolonged mDFS than high TMB patients (NR vs.16.8 months, P = 0.021).

Conclusion

Our study elucidated the unique genetic features and the associated prognosis in Chinese resectable LMPC patients, and we found several molecular factors, especially TMB, can serve as potential prognostic biomarkers in stage II-III resectable LMPC. This study helps better understand the underlying mechanism and direct treatment decisions of this aggressive cancer subtype.

lung adenocarcinoma

micropapillary component

disease-free survival

genomic features

prognostic biomarkers

Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small-cell lung cancer (NSCLC) accounting for more than 80% of all lung cancer diagnoses [1, 2]. Lung adenocarcinoma (LADC) is the most prevalent histologic type of NSCLC [3], and according to the LADC classification system proposed by the International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) in 2011, LADC can be further classified into multiple histologic patterns, including lepidic, acinar, papillary, solid, and micropapillary [4]. Multiple studies have reported that the presence of a micropapillary component (MPC) in LADC was associated with a poor prognosis, and even a minor MPC in adenocarcinoma could contribute to a higher risk of disease recurrence [5–10].

Some previous studies have characterized the oncogenic mutations in LADC with an MPC component (LMPC), and they found that LMPC tended to harbor a diverse range of driver mutations [11]. In particular, Pyo and Kim conducted a meta-analysis and showed that the estimated rates of EGFR, KRAS, and ALK mutations in LMPC were 62.0%, 11.8%, and 10.2%, respectively [12]. Similarly, according to a study performed on 121 LMPC patients, the most common molecular alterations were EGFR mutations (76.9%), followed by ALK translocations (3.3%), KRAS mutations (2.5%), HER2 mutations (1.7%), and RET fusions (1.7%) [13]. Nevertheless, the molecular mechanisms underlying the poor prognosis of LMPC, when compared with other LADC subtypes, remain unclear, especially in Chinese LMPC patients. In addition, the association between the distinct molecular feature and clinical outcomes has not been fully investigated. Although surgical resection is the treatment of choice for early-stage LMPC, around 30–50% of patients suffered from disease recurrence within five years after the treatment [14]. Therefore, it is of clinical importance to identify molecular biomarkers that could estimate the post-surgical prognosis in LMPC.

In this study, we aimed to explore the molecular characteristics and potential prognostic biomarkers in Chinese resectable LMPC patients. To this end, we conducted a comprehensive retrospective analysis on the clinicopathological features and oncogenic mutation profiles of 54 Chinese LMPC patients who received surgical resection, and their tumors contained at least 5% MPC. An external cohort of 113 Chinese LADC patients from a previous publication [15] was used for comparison. Our study focused on comparing crucial genetic features and aberrant signaling pathways between LADC patients with and without MPC, and we analyzed the prognostic effects of these molecular features in stage II-III LMPC patients.

Patients and Samples

From February 2017 to December 2019, a total of 54 patients underwent surgical resection and were diagnosed with LMPC at the Department of Thoracic Surgery, Fujian Medical University Union Hospital. This study was approved by the Institutional Review Board of Union Hospital affiliated with Fujian Medical University (ethical number: 2019JYKY017), and all patients provided written informed consent. Tumor tissue samples from the 54 patients were collected and prepared into formalin-fixed paraffin-embedded (FFPE) specimens. FFPE slides were further reviewed by two certified pathologists to define histologic subtypes of LADC according to the IASLC/ATS/ERS multidisciplinary classification system. LMPC was defined as LADC with an MPC of at least 5%. According to a previous study [15], LMPC was divided into MPC-low (5%≤MPC < 20%) and MPC-high (MPC ≥ 20%) groups based on the proportion of MPC contents. All FFPE samples were sent to a centralized testing center of Nanjing Geneseeq Technology Inc. (Nanjing, China) for targeted next-generation sequencing (NGS) of 425 cancer-relevant genes.

DNA Extraction and Library Construction

Genomic DNA was extracted from FFPE sections with a QIAamp DNA FFPE Tissue kit (Qiagen). Genomic DNA was extracted from white blood cells (WBCs) using the DNeasy Blood & Tissue Kit (Qiagen) and used as the normal control to remove germline variations. DNA was measured by Qubit 3.0 using the dsDNA HS Assay Kit (Life Technologies), and the quality was evaluated by a Nanodrop 2000 (Thermo Fisher).

Approximately 0.5-1 µg of fragmented genomic DNA from each sample was used for library preparation. Library preparation and targeted capture enrichment were performed following previously described methods with modifications [16]. Acustomized xGen lockdown probe panel (containing 425 predefined cancer-related genes) was used for selective enrichment, and the captured libraries were amplified, purified, and quantified.

Sequencing and Bioinformatics Analysis

Target enriched libraries were sequenced on the HiSeq4000 platform (Illumina) with 2×150 bp pair-end reads. Sequencing data were demultiplexed by bcl2fastq (v2.19), analyzed by Trimmomatic to remove low-quality (quality < 15) or N bases. Then the data were aligned to the hg19 reference human genome with the Burrows-Wheeler Aligner (bwa-mem) and further processed using the Picard suite (available at: https://broadinstitute.github.io/picard/) and the Genome Analysis Toolkit (GATK). SNPs and indels were called by VarScan2 and Haplotype Caller/Unified Genotyper in GATK. The mutant allele frequency (MAF) cutoff for single-nucleotide variants and indels was 1%. Common variants were removed using dbSNP and the 1000 Genome project. Germline mutations were filtered out by comparing to patient’s WBCs controls.

Gene fusions were identified by FACTERA and copy number variations (CNVs) were analyzed with ADTEx. The log2 ratio cut-off for copy number gain was defined as 2.0 for tissue samples. A log2 ratio cut-off of 0.6 was used for copy number loss. Allele-specific CNVs were analyzed by FACETS with a 0.2 drift cut-off for unstable joint segments. Tumor mutation burden (TMB) was defined as the number of nonsynonymous mutations per sample as previously described [17].

Statistical Analysis

Quantitative data are presented as the median (range) or the number of patients (percentage). Comparisons of proportions between groups were carried out using Fisher’s exact test. Survival analysis was performed using Kaplan-Meier curves, the P value was determined with the log-rank test, and hazard ratios (HRs) were calculated by the Cox proportional hazards model. Univariate and multivariate analyses were performed to study the association between different variables and DFS. A two-sided P value lower than 0.05 was considered a significant value for all tests unless otherwise indicated. All analyses were performed with R 3.6.0.

Patient Characteristics

The clinicopathological features of the 54 Chinese resectable LMPC patients were summarized in Table 1, and each patient had paired treatment-naïve tumor tissue and WBC control samples. There were 20(37.0%) females and 34(63.0%) males, with a median age of 60 years. The same number of stage I and stage II-III patients were included in the study, and 25 (46.3%) cases had a smoking history. A total of 29 (54%) and 25 (46%) patients were classified as MPC-low (5%≤MPC < 20%) and MPC-high (MPC ≥ 20%), respectively, according to the percentage of MPC in the tumor. Lymph node metastases were observed in 18 (33.3%) patients, and only 6 (11.1%) cases of lymphovascular invasion and 8 (14.8%) cases of pleural invasion were detected. After surgical resection, 24 (44.4%) patients received adjuvant chemotherapy and/or adjuvant EGFR tyrosine kinase inhibitors (TKIs) treatment.

Table 1

Clinicopathologic characteristics of LMPC patients enrolled in this study.
Characteristics	No. (%)
Age
<60	26 (48%)
≥60	28 (52%)
Gender
Male	34 (63%)
Female	20 (37%)
Smoking status
Never	29 (54%)
Ever	25 (46%)
TNM stage
Ⅰ	27 (50%)
Ⅱ-Ⅲ	27 (50%)
MPC content
MPC-low	29 (54%)
MPC-high	25 (46%)
EGFR status
WT	19 (35%)
Mutant	35 (65%)
Lymph node metastasis
No	36 (67%)
Yes	18 (33%)
Pleural invasion
No	46 (85%)
Yes	8 (15%)
Intravascular tumor thrombus
No	48 (89%)
Yes	6 (11%)
Adjuvant therapy
No	30 (56%)
Yes	24 (44%)

LMPC, lung adenocarcinoma with micropapillary component; No., number; WT, wild type.

Driver Gene Characteristics of LMPC

As shown in Fig. 1, the most commonly mutated genes in LMPC were EGFR (76%), TP53 (57.4%), KRAS (14.8%), ALK (14.8%), and PIK3CA (14.8%). Driver mutations, including EGFR, ALK, KRAS, ERBB2, BRAF, and HRAS, were detected in more than 90% of the patients (Fig. 1 and Figure S1A). EGFR driver mutations occurred in 35(64.8%) patients, with EGFR19Del, EGFR p.L858R, EGFR 20ins, and EGFR rare sensitive mutations (e.g., p.S768I, p.L861Q, and p.G719S) detected in 20(57.1%), 10(28.6%), 2(5.7%), and 3(8.6%) cases, respectively (Figure S1B). Among these EGFR-positive patients, 5(14.5%) harbored compound EGFR mutations (Fig. 1 and Figure S1B). ALK gene fusions were detected in 4 (7.4%) patients, including 2 cases harboring single. ALK fusion (i.e., EML4-ALK and CHMP3-ALK, respectively) and the other 2 cases carrying compound ALK fusions (i.e., EML4-ALK plus ALK-SUCLG1 fusions and EML4-ALK plus DAOA-ALK fusions, respectively). Eight patients (14.8%) harbored KRAS mutations, three of whom carried KRAS p.G12C (Fig. 1 and Figure S1C). In addition, we identified two patients (3.7%) having ERBB2 20ins (p.Y772_A775dup) and one patient carrying ERBB2 p.S310F. Combined driver mutations were detected in 5(9.3%) patients, all of whom were EGFR driver mutations combined with other driver genes, including EGFR19Del + ALK fusion, EGFR19Del + BRAF p.V600M, EGFR19Del + KRAS p.A146T, EGFR p.L858R + ERBB2 p.S310F, and EGFR p.S768I + HRAS p.G13S (Figure S1A).

RTK-RAS was the most frequently mutated signaling pathways in our cohort, due to the high frequency of EGFR mutations (64.8% of EGFR driver mutations and 11.1% of other EGFR mutations) and mutations of other RTK-RAS-related genes, such as ALK (14.8%), KRAS (14.8%), BRAF (9.3%), and ERBB2 (5.6%) (Fig. 1). The genetic alterations of PIK3CA (14.8%), RICTOR (5.6%), RPTOR (5.6%), STK11 (5.6%), TSC1 (5.6%), and TSC2 (3.7%) from the PI3K pathway were also commonly detected. In the NOTCH pathway, the mutation frequencies of FBXW7, NOTCH1, and NOTCH2 were 1.9%, 3.7%, and 5.6%, respectively. In terms of the NRF2 pathway, the mutation rate of KEAP1 and CUL3 was 5.6% and 3.7%, respectively. We also detected alterations in the SWI/SNF pathway, including mutations in SMARCA4 (7.4%), ARID1B (3.7%), and ARID2 (3.7%). Mutations from other signaling pathways, such as the SWI/SNF, cell cycle, WNT, and TGF-β pathways, were also detected (Fig. 1). Overall, we observed a relatively high frequency of oncogenic driver mutations and aberrant signaling pathways in Chinese resectable LMPC patients.

Comparison of Mutation Profiles between LMPC and LADC Patients

Given that LMPC and the reference cohort of 113 LADC patients had distinct clinical outcomes, we speculated that there might be some underlying molecular and genetic differences between the two patient populations. We, thereby, compared the mutational characteristics of our LMPC patients with those of 113 Chinese LADC patients, which were described in recent literature [15]. The mutation frequencies of EGFR, ALK, ERBB2, KRAS, and HRAS were comparable between LMPC and LADC, while ERBB4 (11.1% vs.1.8%, P = 0.015) and BRAF (9.3% vs.1.8%, P = 0.037) mutations were significantly more enriched in the LMPC group (Fig. 2A). Besides the RTK/RAS pathway, PIK3CA (14.8% vs.4.4%, P = 0.029) and RPTOR (0% vs. 5.6%, P = 0.033) mutations of the PI3K pathway and NOTCH2 (0% vs. 5.6%, P = 0.033) mutations of the NOTCH pathway were more frequently mutated in LMPC patients than LADC patients (Fig. 2B, 2C). In contrast, the mutation frequency of ARID1A (7.1% vs. 0%, P = 0.055) from the SWI/SNF pathway tended to be higher in LADC than LMPC, although the result was not statistically significant (Fig. 2D).

Next, we compared the differences in oncogenic pathways between the LADC and LMPC groups, and we analyzed nine classical oncogenic pathways that were altered in at least five LMPC patients (Fig. 2E). Consistent with the gene-level mutational analysis, LMPC patients harbored more genetic alterations in various oncogenic pathways, including PI3K (42.6% vs.23.9%, P = 0.019), WNT (33.3% vs.16.8%, P = 0.027), and TGF-β (16.7% vs.6.2%, P = 0.047). In addition, the number of oncogenic pathways altered (NPA) in the LMPC group was significantly higher than that in the LADC group (P < 0.001) (Fig. 2F). Similarly, the NPA in the MPC-high group also tended to be higher than that in the MPC-low group (P = 0.081) (Fig. 2F). We then compared the TMB levels between LADC and LMPC and found no significant difference between the two groups (3.44 vs. 3.76, P = 0.333) (Fig. 2G). However, a further comparison of TMB levels between the MPC-low and MPC-high patients showed that the TMB levels in the MPC-high group were significantly increased (3.22 vs. 4.30, P = 0.012) (Fig. 2G). Moreover, TMB and NPA showed a positive correlation in LMPC patients (Spearman's correlation coefficient r = 0.567, P < 0.001) (Fig. 2H). Overall, LMPC patients, especially patients with high MPC, tended to carry more oncogenic alterations, signaling pathway aberrations, and mutational burdens.

The Association Between Clinicopathological Characteristics and Prognosis in LMPC Patients

As resectable LPMC patients suffered from poor prognosis, we then tried to explore the association between post-surgical disease-free survival (DFS) and various clinical characteristics. By univariate Cox regression analysis, clinicopathological factors such as age, sex, smoking history, MPC content, pleural invasion, lymphovascular invasion, and adjuvant therapy had no significant effect on patients’ prognosis, whereas tumor stage and lymph node metastasis status were significantly correlated with postoperative DFS in LMPC patients (Fig. 3A). In particular, the postoperative median DFS (mDFS) of stage I patients was significantly better than that of stage II and III patients (Not reached (NR) vs. NR vs. 18.2 months, P = 0.004, Hazard ratio (HR) = 6.14) (Fig. 3B and Figure S2A), while stage II and stage III patients had no significant difference in mDFS (NR vs. 18.2 months, P = 0.520) (Figure S2A). Indeed, none of the tested clinicopathological factors had a significant effect on mDFS when performing univariate Cox regression analysis in stage II-III LMPC patients (Table S1). Additionally, among the 54 LMPC cases, patients without lymph node metastasis demonstrated significantly better DFS than those with lymph node metastasis (NR vs. 19.5 months, P = 0.015, HR = 3.1) (Fig. 3C). Intriguingly, after stratifying patients based on their MPC contents, MPC-high patients showed a trend towards a shorter DFS than MPC-low patients, although the result was not statistically significant (Figure S2B, C). Therefore, LPMC patients who had more than stage I tumors and/or lymph node metastasis were likely to experience poor clinical outcomes after surgical resection.

Correlation Analysis of Gene Mutations, Signaling Pathways, TMB and Recurrence in Surgically Resected Stage II-III LMPC Patients

Considering that all of the investigated clinicopathological factors failed to stratify DFS in stage II-III LMPC patients (Table S1) and it is of clinical importance to estimate prognosis in patients with more advanced diseases, we decided to explore the prognostic effects of tumor mutations and aberrant signaling pathways in these patients. Genes or pathways that were altered in ≥ 3 patients were included, and their correlations with mDFS were analyzed. Among the 27 stage II-III LMPC patients, SMARCA4 mutations were significantly associated with poorer mDFS (13.9 months vs. NR, P = 0.013) (Fig. 4A, Table S2). Patients harboring KEAP1 mutations also tended to have a poorer mDFS, although this difference was not statistically significant (18.2 months vs. NR, P = 0.159) (Table S2). In addition, patients with aberrant SWI/SNF pathway showed a significantly shorter mDFS (16.3 months vs. NR, P = 0.003) (Fig. 4B, Table S2). Similarly, patients with NRF2 pathway-related mutations had significantly reduced the mDFS (17.0 months vs. NR, P = 0.046) (Fig. 4C, Table S2). Next, we analyzed the correlation between TMB and DFS in the 27 stage II-III LMPC patients.

In this study, the highest tertile of TMB was defined as TMB-high, reflects a TMB ≥ 6.44 mutations /Mb in these 27 stage II-III LMPC patients, and the intermediate and low tertiles of TMB was defined as TMB-low. Patients with TMB-low experienced significant DFS benefit compared with that TMB-high (NR vs. 16.8 months, P = 0.021, HR = 3.26) (Fig. 4D). Thereby, several genetic features can potentially serve as postoperative prognostic biomarkers in stage II-III LMPC patients.

Multivariate Cox Regression Analysis of DFS and Molecular Characteristics in Stage II-III LMPC Patients

Lastly, we conducted a multivariate Cox regression analysis using the molecular features that were significantly associated with DFS in stage II-III LMPC patients. Surprisingly, none of the selected molecular features were statistically significant in multivariate analysis, although the insignificance of the SWI/SNF pathway (P = 0.147) might be due to limited sample size (Table S3). This implied that the SWI/SNF pathway, the NRF2 pathway, and TMB were not independent prognostic factors in stage II-III LMPC and there might be some correlations among these features. To test this hypothesis, we performed correlation analyses between various molecular features. The mutation status of multiple genes, including TP53, LRP1B, SMARCA4, KEAP1, and PKHD1, were significantly associated with increased TMB (2.7 vs.4.3, P = 0.023; 3.2 vs. 8.6, P = 0.019; 3.2 vs. 16.6, P = 0.016; 3.2 vs. 49.4, P < 0.001; 3.2 vs. 37.1, P = 0.011) (Figure S3A, B).Additionally, patients with altered p53, NRF2, SWI/SNF, and TGF-β pathways had a significant or close-to-significant association with higher TMB(Figure S3C, D). Overall, the alterations of the SWI/SNF and NRF2 pathways were correlated with increased TMB, which may result in the insignificant result in the multivariate analysis.

LMPC, a histologic subtype of LADC, is usually associated with a poor prognosis. Given that the molecular characteristics and the associated prognosis for LMPC were under-investigated, especially in the Chinese population, we performed a systematical analysis to characterize molecular and clinical features in 54 Chinese resectable LMPC patients. LMPC tumors had a unique genetic profile, with more diverse targetable mutations, increased NPA, and more oncogenic pathway alterations, when compared with LADC tumors. In particular, the mutational frequencies of ERBB4, BRAF, PIK3CA, RPTOR, and NOTCH2 were significantly higher in LMPC than LADC, and LMPC patients were more likely to harbor genetic alterations in multiple oncogenic pathways, including PI3K, WNT, and TGF-β. Among stage II-III LMPC patients, molecular features including SMARCA4 mutations, the SWI/SNF pathway alterations, the NRF2 pathway alterations, and TMB were significantly associated with postoperative recurrent risk.

We found that mutations in driver genes, including EGFR, KRAS, ALK, ERBB2, and BRAF, occurred in 91% of LMPC tumors. Some previous studies on Asian LMPC patients showed that mutations in EGFR, ALK, and KRAS occurred in approximately 65–75%, 4–7%, and 3–6% of cases, respectively [12, 13, 18], which were higher than patients with other LADC subtypes. This was generally consistent with our results, but there were still some discrepancies. In this study, all exon regions of the driver genes in the predefined gene panel (425 cancer-related genes) were sequenced by NGS technology. Compared with previous RT-PCR hotspot sequencing technology that focused on a few driver mutations, NGS can comprehensively characterize common driver gene mutations, as well as rare gene mutations, in LMPC. For example, 5 patients with CHMP3-ALK fusion, SND1-BRAF fusion, and multiple driver gene mutations were identified in our LMPC cohort.

A similar analysis was conducted to better understand the differences in signaling pathways between LADC patients with and without an MPC. The LMPC group had a higher NPA than the reference Chinese LADC patients, with 3 oncogenic pathways (i.e., PI3K, WNT, and TGF-β) being frequently altered in LMPC. Caso et al. who performed NGS analysis on 604 LADC patients reported that NPA and TMB were associated with increasing subtype invasiveness and significantly higher frequencies of the micropapillary or solid subtypes [19]. In our study, the mutation frequencies of altered oncogenic pathways in LMPC patients were significantly higher than those in LADC patients, and a similar trend was observed when compared MPC-high with MPC-low tumors. Although there was no significant difference in TMB between the LMPC and LADC groups, the MPC-high group had significantly higher TMB levels than the MPC-low group (P = 0.012), which is consistent with previous reports showing that TMB tended to increase with elevated MPC percentage [15].

In this study, SMARCA4 mutations and changes in the SWI/SNF signaling pathway were significantly associated with poor outcomes in stage II-III LMPC patients. SMARCA4 mutations, which were reported to be the most frequent mutations in the SWI/SWF complex, were associated with poor prognosis in lung cancer, although SMARCA4-mutated lung cancer may be more sensitive to immunotherapy [20]. Two other studies showed that SMARCA4 mutations were related to significantly shorter overall survival and that the presence of SMARCA4 mutations may lead to poorer immunotherapy outcomes in NSCLC patients with KRAS co-mutation [21, 22]. Another SWI/SNF complex gene, ARID1A, has been reported to contribute to better immunotherapy outcomes [21, 23]. A similar trend was observed in our LMPC cohort, although the result was not statistically significant (P = 0.055). Therefore, SMARCA4 mutation could potentially serve as a prognostic and/or predictive biomarker in NSCLC. Given that immunotherapy efficacy may not be ideal in LMPC patients with SMARCA4 and KRAS co-mutations, it is worth exploring the clinical utility of testing SMARCA4, KRAS, and ARID1A mutations in LMPC patients to predict their eligibility for immunotherapy.

We found that genetic alterations in KEAP1, which is one of the key components of the NRF2 pathway, were correlated with poor prognosis in stage II-III LMPC patients. Mutations in the NRF2 pathway, an important regulator of redox balance and cell homeostasis, were common in NSCLC and were associated with increased tumor growth and aggressiveness [24]. Recent studies suggested that KEAP1/NRF2 alterations in NSCLC served as biomarkers of poor prognosis and contributed to resistance to various cancer treatments, such as chemotherapy, radiotherapy, immunotherapy, and TKI therapy [25]. The results from two multicenter randomized clinical trials showed that advanced NSCLC patients with KEAP1/NFE2L2 mutations had worse clinical outcomes than wild-type patients when treated with immunotherapy and chemotherapy [26]. Therefore, the poor prognosis of LMPC patients might be at least partially due to the presence of relatively high frequency of NRF2 pathway-related aberrations, and future research should investigate the efficacy of anti-NRF2 drugs in LMPC.

TMB may also help predict the postoperative prognosis of early-stage NSCLC patients, although its predictive value remains controversial. Previous studies showed that a high TMB was a biomarker of good prognosis in resectable early-stage LADC [27] and NSCLC [28], and patients in the TMB-high group had better DFS and overall survival. However, a study on Chinese LADC patients reported that a high TMB was associated with a shorter DFS, and high TMB was more likely to occur in older patients with a smoking history [29].Another study involving 90 patients with early-stage lung cancer reported that high TMB was a poor prognostic factor [30].In our study, low TMB was significantly associated with improved DFS in postoperative stage II-III LMPC patients, and there was a high correlation between NPA and TMB, which were consistent with previous observations that TMB and NPA were primarily enriched in the histologic subtypes of lung cancer with poor prognosis [19].

There were some limitations of this study. Firstly, because the incidence rate of the LMPC subtype is only about 5%, the number of LMPC patients included in this study was relatively small. The small sample size may limit the statistical analyses, impairing the power to detect the statistically significant difference in the mutation profiles between the MPC-low and MPC-high groups. Further research using larger patient cohorts are needed to fully characterize the LMPC genetic profile. Secondly, as most LADCs were composed of a mixture of multiple histologic subtypes, microdissection of the micropapillary components was not carried out in this study, and the molecular characteristics of the analyzed genes may be affected by the presence of other histologic subtypes. Lastly, this study reported some genetic alterations and pathway aberrations that were potentially associated with the prognosis of LMPC, which needs to be further confirmed in future studies.

In summary, our study systematically delineated the genetic profile in LMPC and characterized multiple molecular features that differentiate LMPC from other LADC. Additionally, we discovered several genetic features, including TMB as well as the genetic alterations in SMARCA4, KEAP1, the SWI/SWF pathway, and the NRF2 pathway, were associated with the postoperative prognosis in stage II-III LMPC patients. Our study provides a more systematic understanding of the molecular characteristics and the underlying mechanism of the poor prognosis of LMPC, which helps direct prognostic estimation and treatment decision in resectable LMPC.

Ethics approval and consent to participate

This study was approved by the Institutional Review Board of Union Hospital affiliated with Fujian Medical University (ethical number: 2019JYKY017), and all patients provided written informed consent.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

MW, JY and YX are the employees of Nanjing Geneseeq Technology Inc. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This work was supported by grants from Joint Funds for the Innovation of Science and Technology, Fujian Province (2021Y9057); Natural Science Foundation of Fujian Province (2021J01745)；Fujian provincial health technology project (2020CX01010103); Natural Science Foundation of Fujian Province (2020J01997).

Authors’ contributions

Conception and design: ZZ and JZ; administrative support: JL and MK; provision of study materials or patients: WL and LW; collection and assembly of data: JZ and MW; data analysis and interpretation: ZZ, JZ, MW, JY and YX; manuscript writing: all authors; final manuscript revision: JL and YX. All authors contributed to the article and approved the submitted version.

Acknowledgements

Not applicable.

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No competing interests reported.

FigureS1.tif
Figure S1.The spectrum of oncogenic driver mutations in LMPC patients. (A-C) The pie charts showed the distribution of main driver mutations (A), EGFRmutations (B), and KRAS mutations (C) in LMPC patients.
FigureS2.tif
Figure S2.The prognostic analysis for TNM stage and MPC content in the 54 LMPC patients. (A) The Kaplan-Meier curve of DFS stratified by TNM Staging. (B) The forest plot of hazard ratios (HRs) for DFS with various MPC cutoffs. (C) The Kaplan-Meier curve of DFS in MPC-high and MPC-low patients.
FigureS3.tif
Figure S3.The correlation analysis among individual gene mutations, signaling pathway alterations, and TMB. (A) The correlation matrix of gene mutations and TMB. (B) The relationship between TMB levels and mutational status of individual genes. (C) The correlation matrix of signaling pathways and TMB. (D) The relationship between TMB levels and the alteration of specific signaling pathways.
TableS1.docx
Table S1. The univariate Cox regression analysis of DFS with clinicopathologiccharacteristics in stage Ⅱ-Ⅲ LMPC patients.
TableS2.docx
Table S2. The univariate Cox regression analysis of DFS with individual gene or signaling pathway alteration in stage Ⅱ-Ⅲ LMPC patients.
TableS3.docx
Table S3. The univariate and multivariate Cox regression analysis of DFS with molecular characteristics in stage Ⅱ-Ⅲ LMPC patients.

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Genomic Features and Prognostic Biomarkers of Chinese Resectable Lung Adenocarcinoma Patients with a Micropapillary Component

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Abstract

Background

Methods

Results

Conclusion

Figures

INTRODUCTION

MATERIALSANDMETHODS

Patients and Samples

DNA Extraction and Library Construction

Sequencing and Bioinformatics Analysis

Statistical Analysis

RESULTS

Patient Characteristics

Driver Gene Characteristics of LMPC

Comparison of Mutation Profiles between LMPC and LADC Patients

The Association Between Clinicopathological Characteristics and Prognosis in LMPC Patients

Multivariate Cox Regression Analysis of DFS and Molecular Characteristics in Stage II-III LMPC Patients

DISCUSSION

Declarations

References

Additional Declarations

Supplementary Files

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