Cisplatin resistance-related multi-omics differences and the establishment of machine learning models

Objectives

Platinum-based chemotherapies are currently the first-line treatment of non-small cell lung cancer. This study will improve our understanding of the causes of resistance to cisplatin, especially in lung adenocarcinoma (LUAD) and provide a reference for therapeutic decisions in clinical practice.

Methods

Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA) and Zhongshan hospital affiliated to Fudan University (zs-cohort) were used to identify the multi-omics differences related to platinum chemotherapy. Cisplatin-resistant mRNA and miRNA models were constructed by Logistic regression, classification and regression tree and C4.5 decision tree classification algorithm with previous feature selection performed via least absolute shrinkage and selection operator (LASSO). qRT-PCR and western-blotting of A549 and H358 cells, as well as single-cell Seq data of tumor samples were applied to verify the tendency of certain genes.

Results

661 cell lines were divided into three groups according to the IC50 value of cisplatin, and the top 1/3 (220) with a small IC50 value were defined as the sensitive group while the last 1/3 (220) were enrolled in the insensitive group. TP53 was the most common mutation in the insensitive group, in contrast to TTN in the sensitive group. 1348 mRNA, 80 miRNA, and 15 metabolites were differentially expressed between 2 groups (P < 0.05). According to the LASSO penalized logistic modeling, 6 of the 1348 mRNAs, FOXA2, BATF3, SIX1, HOXA1, ZBTB38, IRF5, were selected as the associated features with cisplatin resistance and for the contribution of predictive mRNA model (all of adjusted P-values < 0.001). Three of 6 (BATF3, IRF5, ZBTB38) genes were finally verified in cell level and patients in zs-cohort.

Conclusions

Somatic mutations, mRNA expressions, miRNA expressions, metabolites and methylation were related to the resistance of cisplatin. The models we created could help in the prediction of the reaction and prognosis of patients given platinum-based chemotherapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03372-0.

Genomic And Tumor Microenvironment Differences Between Cell Cycle Progression Pathway Altered/Non-Altered Patients With Lung Adenocarcinoma

Background

Identified as a hallmark of cancer, the dysregulated cell cycle progression plays an important role in the promotion and progression of lung adenocarcinoma (LUAD). However, the genomic and microenvironment differences between cell cycle progression pathway altered/non-altered LUAD patients remain to be elucidated.

Materials and Methods

Data of this study were obtained from The Cancer Genome Atlas (TCGA), including simple nucleotide variation, copy number variation (CNV), RNA-seq gene expression, miRNA expression, survival, and clinical information. Besides, 34 LUAD samples from our institution were used as a validation cohort. Differentially expressed genes (DEGs), enrichment analysis, and immune cell infiltration were detected. At last, we built a LASSO-binary Logistic regression model to predict the cell-cycle-related gene mutation (CDKN2A, CCND1, CDK4, CCNE1, and RB1) in LUAD patients and further verified it in the samples from our institution.

Results

Based on the cell cycle progression pathway status, the LUAD patients were divided into the mutation (n=322) and wild (n=46) groups. Compared to the wild group, the mutation group had a higher mutational load and CNV. Among the 16684 protein-coding genes analyzed, 302 were upregulated, and 354 were downregulated in the mutation group. Enrichment analysis indicated that these DEGs were closely related to metabolism items. After performing immune cell infiltration analysis of 22 immune cells, we found the proportion of 5 immune cells such as monocytes (P&lt;0.01) and dendritic cells (P&lt;0.01) were higher in the wild group. Finally, a cell-cycle-related 15-signature model was built by LASSO-Logistic regression analysis, which could predict the cell cycle progression pathway-related gene mutation (CDKN2A, CCND1, CDK4, CCNE1, and RB1) in LUAD patients. The validation cohorts showed the sensitivity and specificity of this model were 0.667 and 0.929, respectively.

Conclusion

The genomic and microenvironment characteristics differed between the cell cycle progression pathway altered/non-altered patients with LUAD. Our findings may provide new insight into personalized treatment for LUAD patients.

The clinical prognostic factors of patients with stage IB lung adenocarcinoma

Background

Lung adenocarcinoma (ADC) at stage IB has its own prognostic characteristics. This study aimed to investigate the clinical factors that may affect the prognosis of patients with stage IB ADC.

Methods

The data of ADC cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2016) and patients in Zhongshan Hospital, Fudan University (Department of Thoracic Surgery, 2015–2016). Kaplan-Meier method was used to obtain the overall survival (OS). Factors that significantly related to the prognosis were evaluated by univariate and multivariate analysis (UVA, MVA) using the Cox model. A nomogram was developed and validated to predict the 3-year OSs of those patients.

Results

7,605 patients with stage IB ADC were included ultimately and were divided into two groups, a training cohort (n=5,324) and a test cohort (n=2,281). Besides, there was a validation cohort (n=272) for the verification of the nomogram model. Those with significantly older age, male, the white race, lower grades of tumor differentiation, larger tumor size (31–40 mm) without pleural layer (PL) invasion as well as receiving sublobectomy suffered from poorer survival (P<0.001), which were identified as independent factors for stage IB ADC (P<0.001), and according to which, a nomogram model was created.

Conclusions

Age, sex, race, histological grade, surgery to the primary site, and tumor size combined with PL invasion were independent risk factors for stage IB ADC, based on which a nomogram was constructed to predict the prognosis.

Two-dimensional quantum-sheet films with sub-1.2 nm channels for ultrahigh-rate electrochemical capacitance

Dense, thick, but fast-ion-conductive electrodes are critical yet challenging components of ultrafast electrochemical capacitors with high volumetric power/energy densities^1-4. Here we report an exfoliation-fragmentation-restacking strategy towards thickness-adjustable (1.5‒24.0 μm) dense electrode films of restacked two-dimensional 1T-MoS₂ quantum sheets. These films bear the unique architecture of an exceptionally high density of narrow (sub-1.2 nm) and ultrashort (~6.1 nm) hydrophobic nanochannels for confinement ion transport. Among them, 14-μm-thick films tested at 2,000 mV s^-1 can deliver not only a high areal capacitance of 0.63 F cm^-2 but also a volumetric capacitance of 437 F cm^-3 that is one order of magnitude higher than that of other electrodes. Density functional theory and ab initio molecular dynamics simulations suggest that both hydration and nanoscale channels play crucial roles in enabling ultrafast ion transport and enhanced charge storage. This work provides a versatile strategy for generating rapid ion transport channels in thick but dense films for energy storage and filtration applications.

Signatures of malignant cells and novel therapeutic targets revealed by single-cell sequencing in lung adenocarcinoma

Background

Single‐cell transcriptomics has been used to investigate various tumors to elucidate the molecular distinction of all cell type compositions of a complex mix.

Aims

This study aimed to investigate malignant‐cell‐specific genes to explore diagnostic and therapeutic biomarkers using single‐cell transcriptomic data of lung adenocarcinoma.

Materials & Methods

10X single‐cell RNA‐seq data of fourteen patients with lung adenocarcinoma were analyzed. Genes that expressed differentially and those with higher confidence to distinguish tumor cells from normal cells were picked out using the ROC curves. The LASSO regression method was used to select most markedly correlated genes to predict the malignancy of every single cell within a model. We also conducted further experiments to determine their roles in lung cancer in vitro.

Results

Twenty two thousand four hundred and ninety one tumor and 181 666 normal single cells were analyzed where 369 genes were found to be specifically expressed in single malignant cells. Seventy of them, encoding secreted or membrane‐bound proteins, showed involvement in cell‐to‐cell communications in tumor biology. KRT18 and the other six genes were identified as predictors to distinguish single malignant cells and were integrated to construct an accurate (96.1%) predicting model. Notably, IRX2, SPINK13, and CAPN8 outperformed the other four genes. Further experiments confirmed the upregulation of them in lung adenocarcinoma at both tissue and cell levels. Proliferative capacities of lung adenocarcinoma cells were attenuated by knocking‐down of either of them. However, targeting CAPN8, IRX2, or SPINK13 hardly exerted a cytotoxic effect on these cells.

Discussion

Apart from the current model, similar tools were still warranted using single‐cell RNA‐seq data of more types of tumors. The three genes identified as potential therapeutic targets in the present study still need to be validated in more in lung cancer.

Conclusion

Our model can aid the analyses of single‐cell sequencing data. CAPN8, IRX2, and SPINK13 may serve as novel targets of targeted and immune‐based therapies in lung adenocarcinoma.

LncRNA FAM83A-AS1 facilitates tumor proliferation and the migration via the HIF-1α/ glycolysis axis in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD), the major subtype of lung cancer, is among the leading cause of cancer-related death worldwide. Energy-related metabolic reprogramming metabolism is a hallmark of cancer shared by numerous cancer types, including LUAD. Nevertheless, the functional pathways and molecular mechanism by which FAM83A-AS1 acts in metabolic reprogramming in lung adenocarcinoma have not been fully elucidated.

Methods: We used transwell, wound-healing scratch assay, and metabolic assays to explore the effect of FAM83A-AS1 in LUAD cell lines. Western blotting, Co-IP assays, and ubiquitination assays were used to detect the effects of FAM83A-AS1 on HIF-1α expression, degradation, and its binding to VHL. Moreover, an in vivo subcutaneous tumor formation assay was used to detect the effect of FAM83A-AS1 on LUAD.

Results: Herein, we identified FAM83A-AS1 as a metabolism-related lncRNA, which was highly correlated with glycolysis, hypoxia, and OXPHOS pathways in LUAD patients using bioinformatics analysis. In addition, we uncovered that FAM83A-AS1 could promote the migration and invasion of LUAD cells, as well as influence the stemness of LUAD cells in vivo and vitro. Moreover, FAM83A-AS1 was shown to promote glycolysis in LUAD cell lines in vitro and in vivo, and was found to influence the expression of genes related to glucose metabolism. Besides, we revealed that FAM83A-AS1 could affect glycolysis by regulating HIF-1α degradation. Finally, we found that FAM83A-AS1 knockdown could inhibit tumor growth and suppress the expression of HIF-1α and glycolysis-related genes in vivo.

Conclusion: Our study demonstrates that FAM83A-AS1 contributes to LUAD proliferation and stemness via the HIF-1α/glycolysis axis, making it a potential biomarker and therapeutic target in LUAD patients.

Identification and analysis of a prognostic ferroptosis and iron-metabolism signature for esophageal squamous cell carcinoma

Background: The role of ferroptosis in esophageal squamous cell carcinoma (ESCC) is still unclear.

Methods: The association of iron metabolism and ferroptosis-related genes with the prognosis, copy number variation (CNV), TMB, and immune cell infiltration of ESCC was explored using data from the GEO and TCGA database and validated by immunofluorescence in 112 ESCC patients from our center. The potential anti-cancer drugs and compounds from the GDSC and the Connectivity Map database were also screened.

Results: A total of 117 iron metabolism and ferroptosis-related genes were identified. We found the expressions of PRNP, SLC3A2, SLC39A8, and SLC39A14 negatively related to the prognosis of ESCC patients, while ATP6V0A1 and LCN2 were opposite, which was validated in 112 ESCC samples from our center. And a prognostic signature was constructed based on their expressions and Cox regression coefficient (β). The low-score group exhibited a significantly worse OS. Besides, analysis of 179 ESCC samples from GSE53625 revealed that patients of poorly differentiation, more than 60 years, T4 stage, advanced N stage, advanced stage, and adjuvant therapy also exhibited a significantly shorter OS, based on which a nomogram to predict the OS was established. Moreover, the low-score group exhibited significantly higher CNV and TMB and more frequent mutations of TP53, MUC16, and NOTCH1. Higher proportion of Macrophages M2, and lower proportion of T cells follicular helper were observed in the low-score group. We discovered that AZD7762, Sunitinib, Cytarabine, Docetaxel, Vinblastine, and Elesclomol exhibited lower IC50 in the low-score group. And 20 potential compounds were identified from the CMap database.

Conclusions: Six iron metabolism and ferroptosis-related genes were associated with the prognosis, CNV, TMB, and immune cell infiltration of ESCC. Some potential anti-cancer drugs and compounds may be helpful for OS.

Multi-omics analysis identifies distinct subtypes with clinical relevance in lung adenocarcinoma harboring KEAP1/NFE2L2

Backgrounds: Lung adenocarcinoma is one of the most common malignant tumors, in which KEAP1-NFE2L2 pathway is altered frequently. The biological features and intrinsic heterogeneities of KEAP1/NFE2L2-mutant lung adenocarcinoma remain unclear.

Methods: Multiplatform data from The Cancer Genome Atlas (TCGA) were acquired to identify two subtypes of lung adenocarcinoma harboring KEAP1/NFE2L2 mutations.

Bioinformatic analyses, including immune microenvironment, methylation level and mutational signature, were performed to characterize the intrinsic heterogeneities. Meanwhile, initial results were validated by using in silico assessment of common lung adenocarcinoma cell lines, which revealed consistent features of mutant subtypes. Furthermore, drug sensitivity screening was conducted based on public datasets.

Results: Two mutant subtypes (P1 and P2) of 89 patients were identified in TCGA. P2 patients had significantly higher levels of smoking and worse survival compared with P1 patients. The P2 subset was characterized by active immune microenvironment and more smoking-induced genomic alterations with respect to methylation and somatic mutations. Validations of the corresponding features in 20 mutant cell lines were achieved. Several compounds which were sensitive to mutant subtypes of lung adenocarcinoma were identified, such as inhibitors of PI3K/Akt and IGF1R signaling pathways.

Conclusions:KEAP1/NFE2L2-mutant lung adenocarcinoma showed potential heterogeneities. The intrinsic heterogeneities of KEAP1/NFE2L2 were associated with immune microenvironment and smoking-related genomic aberrations.

Pan-Driver-Negatives <i>versus</i> Epidermal Growth Factor Receptor Mutants for C-Stage IA Lung Adenocarcinoma with Ground-Glass Opacity

Purpose: We aimed to verify the prognosis of epidermal growth factor receptor (EGFR) mutation of clinical (c)-stage IA lung adenocarcinoma with the ground-glass opacity (GGO) component.

Methods: We evaluated 226 cases of surgically resected c-stage IA lung adenocarcinoma with GGO component. Endpoints were overall survival (OS) and recurrence-free survival (RFS). Kaplan–Meier analysis and the log-rank test were used to estimate the survival differences. Prognostic factors were assessed using the univariable and multivariable Cox proportional hazards model.

Results: Among the 226 cases, 177 cases harbored the EGFR-mutant adenocarcinoma with the GGO component. The mean duration of follow-up time was 54.4 ± 1.2 months. The 5-year OS and RFS did not differ significantly between the EGFR-mutant and wild-type groups (5-year OS 100% vs. 94.3%, hazard ratio [HR] 0.276, P = 0.168; 5-year RFS 94.7% vs. 95.7%, HR 0.873, P = 0.864). Multivariable Cox hazard model revealed that radiologically solid component size (P = 0.010) and pathological node-positive (P = 0.036) were significant predictors of an inferior RFS.

Conclusion: EGFR-mutant was not a prognostic factor of OS and RFS for c-stage IA lung adenocarcinoma with the GGO component. Radiologically solid component size and pathological lymph node status were independent prognostic factors of worse RFS.

Weighted Correlation Network Analysis of Cancer Stem Cell-Related Prognostic Biomarkers in Esophageal Squamous Cell Carcinoma

Background: The role of cancer stem cells in esophageal squamous cell carcinoma (ESCC) remains unclear. Methods: The mRNA stemness index (mRNAsi) of 179 ESCC patients (GSE53625) was calculated using a machine learning algorithm based on their mRNA expression. Stemness-related genes were identified by weighted correlation network analysis (WGCNA) and LASSO regression, whose associations with mutation status, immune cell infiltrations, and potential compounds were also analyzed. The role of these genes in proliferation and their expressions was assessed in ESCC cell lines and 112 samples from our center. Results: The ESCC samples had significantly higher mRNAsi than the normal tissues. Patients with high mRNAsi exhibited higher worse OS. Seven stemness-related genes were identified by WGCNA and LASSO regression, based on which a risk-predicted score model was constructed. Among them, CST1, CILP, PITX2, F2RL2, and RIOX1 were favorable for OS, which were adverse for DPP4 and ZFHX4 in the GSE53625 dataset. However, RIOX1 was unfavorable for OS in patients from our center. In vitro assays showed that CST1, CILP, PITX2, F2RL2, and RIOX1 were pro-proliferated, which were opposite for DDP4 and ZFHX4. In addition, SMARCA4, NOTCH3, DNAH5, and KALRN were more mutated in the low-score group. The low-score group had significantly more memory B cells, monocytes, activated NK cells, and Tregs and less macrophages M2, resting mast cells, and resting dendritic cells. Conclusions: Seven stemness-related genes are significantly related to the prognosis, gene mutations, and immune cell infiltration of ESCC. Some potential anticancer compounds may be favorable for OS.

Multi-Omics Analysis of Cancer Cell Lines with High/Low Ferroptosis Scores and Development of a Ferroptosis-Related Model for Multiple Cancer Types

Background: Ferroptosis is a newly identified regulated cell death characterized by iron-dependent lipid peroxidation and subsequent membrane oxidative damage, which has been implicated in multiple types of cancers. The multi-omics differences between cancer cell lines with high/low ferroptosis scores remain to be elucidated.

Methods and Materials: We used RNA-seq gene expression, gene mutation, miRNA expression, metabolites, copy number variation, and drug sensitivity data of cancer cell lines from DEPMAP to detect multi-omics differences associated with ferroptosis. Based on the gene expression data of cancer cell lines, we performed LASSO-Logistic regression analysis to build a ferroptosis-related model. Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), esophageal cancer (ESCA), bladder cancer (BLCA), cervical cancer (CESC), and head and neck cancer (HNSC) patients from the TCGA database were used as validation cohorts to test the efficacy of this model.

Results: After stratifying the cancer cell lines into high score (HS) and low score (LS) groups according to the median of ferroptosis scores generated by gene set variation analysis, we found that IC50 of 66 agents such as oxaliplatin (p < 0.001) were significantly different, among which 65 were higher in the HS group. 851 genes such as KEAP1 and NRAS were differentially muted between the two groups. Differentially expressed genes, miRNAs and metabolites were also detected—multiple items such as IL17F (logFC = 6.58, p < 0.001) differed between the two groups. Unlike the TCGA data generated by bulk RNA-seq, the gene expression data in DEPMAP are from pure cancer cells, so it could better reflect the traits of tumors in cancer patients. Thus, we built a 15-signature model (AUC = 0.878) based on the gene expression data of cancer cell lines. The validation cohorts demonstrated a higher mutational rate of NFE2L2 and higher expression levels of 12 ferroptosis-related genes in HS groups.

Conclusion: This article systemically analyzed multi-omics differences between cancer cell lines with high/low ferroptosis scores and a ferroptosis-related model was developed for multiple cancer types. Our findings could improve our understanding of the role of ferroptosis in cancer and provide new insight into treatment for malignant tumors.

HIF-1α switches the functionality of TGF-β signaling via changing the partners of smads to drive glucose metabolic reprogramming in non-small cell lung cancer

BACKGROUND

Most cancer cells have fundamentally different metabolic characteristics, particularly much higher glycolysis rates than normal tissues, which support the increased demand for biosynthesis and promote tumor progression. We found that transforming growth factor (TGF)-β plays a dual function in regulating glycolysis and cell proliferation in non-small cell lung cancer.

METHODS

We used the PET/MRI imaging system to observe the glucose metabolism of subcutaneous tumors in nude mice. Energy metabolism of non-small cell lung cancer cell lines detected by the Seahorse XFe96 cell outflow analyzer. Co-immunoprecipitation assays were used to detect the binding of Smads and HIF-1α. Western blotting and qRT-PCR were used to detect the regulatory effects of TGF-β and HIF-1α on c-MYC, PKM1/2, and cell cycle-related genes.

RESULTS

We discovered that TGF-β could inhibit glycolysis under normoxia while significantly promoting tumor cells' glycolysis under hypoxia in vitro and in vivo. The binding of hypoxia-inducible factor (HIF)-1α to the MH2 domain of phosphorylated Smad3 switched TGF-β function to glycolysis by changing Smad partners under hypoxia. The Smad-p107-E2F4/5 complex that initially inhibited c-Myc expression was transformed into a Smad-HIF-1α complex that promoted the expression of c-Myc. The increased expression of c-Myc promoted alternative splicing of PKM to PKM2, resulting in the metabolic reprogramming of tumor cells. In addition, the TGF-β/Smad signal lost its effect on cell cycle regulatory protein p15/p21. Furthermore, high expression of c-Myc inhibited p15/p21 and promoted the proliferation of tumor cells under hypoxia.

CONCLUSIONS

Our results indicated that HIF-1α functions as a critical factor in the dual role of TGF-β in tumor cells, and may be used as a biomarker or therapeutic target for TGF-β mediated cancer progression.

Dissecting the single-cell transcriptome network in patients with esophageal squamous cell carcinoma receiving operative paclitaxel plus platinum chemotherapy

Esophageal squamous cell carcinoma (ESCC) accounts for 90% of all cases of esophageal cancers worldwide. Although neoadjuvant chemotherapy (NACT-ESCC) improves the survival of ESCC patients, the five-year survival rate of these patients is dismal. The tumor microenvironment (TME) and tumor heterogeneity decrease the efficacy of ESCC therapy. In our study, 113,581 cells obtained from five ESCC patients who underwent surgery alone (SA-ESCC) and five patients who underwent preoperative paclitaxel plus platinum chemotherapy (NACT-ESCC), were used for scRNA-seq analysis to explore molecular and cellular reprogramming patterns. The results showed samples from NACT-ESCC patients exhibited the characteristics of malignant cells and TME unlike samples from SA-ESCC patients. Cancer cells from NACT-ESCC samples were mainly at the ‘intermediate transient stage’. Stromal cell dynamics showed molecular and functional shifts that formed the immune-activation microenvironment. APOE, APOC1, and SPP1 were highly expressed in tumor-associated macrophages resulting in anti-inflammatory macrophage phenotypes. Levels of CD8+ T cells between SA-ESCC and NACT-ESCC tissues were significantly different. Immune checkpoints analysis revealed that LAG3 is a potential immunotherapeutic target for both NACT-ESCC and SA-ESCC patients. Cell–cell interactions analysis showed the complex cell-cell communication networks in the TME. In summary, our findings elucidate on the molecular and cellular reprogramming of NACT-ESCC and ESCC patients. These findings provide information on the potential diagnostic and therapeutic targets for ESCC patients.

Differences in genetics and microenvironment of lung adenocarcinoma patients with or without TP53 mutation

Background

Differences in genetics and microenvironment of LUAD patients with or without TP53 mutation were analyzed to illustrate the role of TP53 mutation within the carcinogenesis of LUAD, which will provide new concepts for the treatment of LUAD.

Methods

In this study, we used genetics and clinical info from the TCGA database, including somatic mutations data, RNA-seq, miRNA-seq, and clinical data. More than one bioinformatics tools were used to analyze the unique genomic pattern of TP53-related LUAD.

Results

According to TP53 gene mutation status, we divided the LUAD patients into two groups, including 265 in the mutant group (MU) and 295 in the wild-type group (WT). 787 significant somatic mutations were detected between the groups, including mutations in titin (TTN), type 2 ryanodine receptor (RYR2) and CUB and Sushi multiple domains 3(CSMD3), which were up-regulated in the MU. However, no significant survival difference was observed. At the RNA level, we obtained 923 significantly differentially expressed genes; in the MU, α-defensin 5(DEFA5), pregnancy-specific glycoprotein 5(PSG5) and neuropeptide Y(NPY) were the most up-regulated genes, glucose-6-phosphatase (G6PC), alpha-fetoprotein (AFP) and carry gametocidal (GC) were the most down-regulated genes. GSVA analysis revealed 30 significant pathways. Compared with the WT, the expression of 12 pathways in the mutant group was up-regulated, most of which pointed to cell division. There were significant differences in tumor immune infiltrating cells, such as Macrophages M1, T cells CD4 memory activated, Mast cells resting, and Dendritic cells resting. In terms of immune genes, a total of 35 immune-related genes were screened, of which VGF (VGF nerve growth factor inducible) and PGC (peroxisome proliferator-activated receptor gamma coactivator) were the most significant up-regulated and down-regulated genes, respectively. Research on the expression pattern of immunomodulators found that 9 immune checkpoint molecules and 6 immune costimulatory molecules were considerably wholly different between the two groups.

Conclusions

Taking the mutant group as a reference, LUAD patients in the mutant group had significant differences in somatic mutations, mRNA-seq, miRNA-seq, immune infiltration, and immunomodulators, indicating that TP53 mutation plays a crucial role in the occurrence and development of LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01671-8.

Clinicopathological and prognostic implications of ALK rearrangement in patients with completely surgically resected lung adenocarcinoma

Background

The prognostic significance of ALK rearrangement is still contradictory. Here, we aimed to investigate the clinical characteristics and outcomes of lung adenocarcinoma patients with ALK rearrangement, and analyze whether these patients benefited from targeted therapy.

Methods

This was a retrospective cohort study of 80 ALK‐rearranged lung adenocarcinoma patients who had undergone radical surgery and another 3031 ALK mutation‐negative patients were retrospectively reviewed for inclusion in this case‐controlled analyses. Overall survival (OS) was evaluated using the Kaplan‐–Meier method. Univariate analysis (UVA) and multivariate analysis (MVA) by the Cox proportional hazards regression identified risk factors that predicted OS.

Results

Compared to ALK‐negative patients, the ALK rearranged patients were younger, with more non‐smokers, more females, a larger primary tumor was demonstrated, and were a higher pathological stage. In particular, the risk of lymph node metastasis was higher. For patients with surgically‐resected tumors, the prognosis was better for ALK rearranged patients (HR = 0.503; 95% CI: 0.259–0.974, p = 0.041). In addition, for stage II–III patients, targeted therapy was an independent prognostic factor of better OS (HR = 0.159; 95% CI: 0.032–0.801, p = 0.026).

Conclusions

ALK rearranged lung adenocarcinoma patients who have undergone radical surgery have distinct clinical features. Patients with ALK rearrangement may have a favorable prognosis, and stage II–III patients may benefit from targeted treatment.

Tumor size as a predictor for prognosis of patients with surgical IIIA-N2 non-small cell lung cancer after surgery

Background

The 8^th edition of the American Joint Committee on Cancer staging system for lung cancer made major revisions to T staging, especially the size division of stage II/III patients. However, the value of tumor size in the postoperative prognosis of IIIA–N2 non-small cell lung cancer (NSCLC) is seldom mentioned, and survival data of such patients should be re-evaluated according to the 8^th edition staging system.

Methods

Patients with IIIA-N2 NSCLC after surgery were identified in the Surveillance, Epidemiology, and End Results database (n=4,128). All patients were stratified according to tumor size, 5-year overall survival (OS) was then compared. Cox regression analysis was used to determine the value of size to discriminate patients with prognostic differences and establish a predictive nomogram system. Patients with IIIA-N2 NSCLC from our own institute (n=583) were used to validate the results.

Results

The prognosis of patients with tumor sizes of 0–2, 2–4 and 4–5 cm differed greatly from each other in the training cohort, with 5-year OS rates of 53.7%, 43.9% and 36.9% respectively (P<0.001), in the validation cohort, the rates were 54.1%, 38.4% and 33.8% respectively. Tumor size >2 cm was considered an independent risk factor compared to the ≤2 cm group in the Cox regression analysis: 2–4 cm (HR =1.25, 1.12–1.39; P<0.001), 4–5 cm (HR =1.51, 1.32–1.39; P<0.001), the validation cohort showed the same trend. The concordance index of the training set was 0.634 (0.622–0.646), while that of the validation set was 0.716 (0.686–0.746). The calibration plot showed optimal consistency between the nomogram predicted survival and observed survival.

Conclusions

Tumors with different sizes showed significant postoperative survival differences among patients with IIIA-N2 NSCLC. Tumor size should be considered when making surgery decisions in such patients, with tumor size ≤2 cm showing considerably better prognosis.