Molecular profiling identifies prognostic markers of stage IA lung adenocarcinoma

Multi-omics analysis unravels the underlying mechanisms of poor prognosis and differential therapeutic responses of solid predominant lung adenocarcinoma

Background

Solid predominant adenocarcinoma (SPA) has been reported to be a subtype with poor prognosis and unsatisfactory response to chemotherapy and targeted therapy in lung adenocarcinoma (LUAD). However, the underlying mechanisms remain largely unknown and the suitability of immunotherapy for SPA has not been investigated.

Methods

We conducted a multi-omics analysis of 1078 untreated LUAD patients with clinicopathologic, genomic, transcriptomic, and proteomic data from both public and internal cohorts to determine the underlying mechanisms of poor prognosis and differential therapeutic responses of SPA and to investigate the potential of immunotherapy for SPA. The suitability of immunotherapy for SPA was further confirmed in a cohort of LUAD patients who received neoadjuvant immunotherapy in our center.

Results

Along with its aggressive clinicopathologic behaviors, SPA had significantly higher tumor mutation burden (TMB) and number of pathways altered, lower TTF-1 and Napsin-A expression, higher proliferation score and a more immunoresistant microenvironment than non-solid predominant adenocarcinoma (Non-SPA), accounting for its worse prognosis. Additionally, SPA had significantly lower frequency of therapeutically targetable driver mutations and higher frequency of EGFR/TP53 co-mutation which was related to resistance to EGFR tyrosine kinase inhibitors, indicating a lower potential for targeted therapy. Meanwhile, SPA was enriched for molecular features associated with poor response to chemotherapy (higher chemoresistence signature score, lower chemotherapy response signature score, hypoxic microenvironment, and higher frequency of TP53 mutation). Instead, muti-omics profiling revealed that SPA had stronger immunogenicity and was enriched for positive biomarkers for immunotherapy (higher TMB and T cell receptor diversity; higher PD-L1 expression and more immune cell infiltration; higher frequency of gene mutations predicting efficacious immunotherapy, and elevated expression of immunotherapy-related gene signatures). Furthermore, in the cohort of LUAD patients who received neoadjuvant immunotherapy, SPA had higher pathological regression rates than Non-SPA and patients with major pathological response were enriched in SPA, confirming that SPA was more prone to respond to immunotherapy.

Conclusions

Compared with Non-SPA, SPA was enriched for molecular features associated with poor prognosis, unsatisfactory response to chemotherapy and targeted therapy, and good response to immunotherapy, indicating more suitability for immunotherapy while less suitability for chemotherapy and targeted therapy.

Identification of 5-Gene Signature Improves Lung Adenocarcinoma Prognostic Stratification Based on Differential Expression Invasion Genes of Molecular Subtypes

Background

The acquisition of invasive tumor cell behavior is considered to be the cornerstone of the metastasis cascade. Thus, genetic markers associated with invasiveness can be stratified according to patient prognosis. In this study, we aimed to identify an invasive genetic trait and study its biological relevance in lung adenocarcinoma.

Methods

250 TCGA patients with lung adenocarcinoma were used as the training set, and the remaining 250 TCGA patients, 500 ALL TCGA patients, 226 patients with GSE31210, 83 patients with GSE30219, and 127 patients with GSE50081 were used as the verification data sets. Subtype classification of all TCGA lung adenocarcinoma samples was based on invasion-associated genes using the R package ConsensusClusterPlus. Kaplan-Meier curves, LASSO (least absolute contraction and selection operator) method, and univariate and multivariate Cox analysis were used to develop a molecular model for predicting survival.

Results

As a consequence, two molecular subtypes for LUAD were first identified from all TCGA all data sets which were significant on survival time. C1 subtype with poor prognosis has higher clinical characteristics of malignancy, higher mutation frequency of KRAS and TP53, and a lower expression of immune regulatory molecules. 2463 differentially expressed invasion genes between C1 and C2 subtypes were obtained, including 580 upregulation genes and 1883 downregulation genes. Functional enrichment analysis found that upregulated genes were associated with the development of tumor pathways, while downregulated genes were more associated with immunity. Furthermore, 5-invasion gene signature was constructed based on 2463 genes, which was validated in four data sets. This signature divided patients into high-risk and low-risk groups, and the LUDA survival rate of the high-risk group is significantly lower than that of the low-risk group. Multivariate Cox analysis revealed that this gene signature was an independent prognostic factor for LUDA. Compared with other existing models, our model has a higher AUC.

Conclusion

In this study, two subtypes were identified. In addition, we developed a 5-gene signature prognostic risk model, which has a good AUC in the training set and independent validation set and is a model with independent clinical characteristics. Therefore, we recommend using this classifier as a molecular diagnostic test to assess the prognostic risk of patients with LUDA.

Prognostic alternative splicing signature reveals the landscape of immune infiltration in Pancreatic Cancer

Background: Pancreatic cancer (PC) is an aggressive cancer with worse survival in the world. Emerging evidence suggested that the imbalance of alternative splicing (AS) is a hallmark of cancer and indicated poor prognosis of patients. Genes-derived splicing events can produce neoepitopes for immunotherapy. However, the profound study of splicing profiling in PC is still elusive. We aimed to identification of novel prognostic signature across a comprehensive splicing landscape and reveal their relationship with tumor-infiltrating immune cells in pancreatic cancer microenvironment.

Methods: Based on integrated analysis of splicing profiling and clinical data, differentially splicing events were filtered out. Then, stepwise Cox regression analysis was applied to identify survival-related splicing events and construct prognostic signature. Functional enrichment analysis was performed to explore biology function. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were performed to validate the predictive effect of predictive signature. We also verified the clinical value of prognostic signature under the influence of different clinical parameters. For deeper analysis, we evaluated the correlation between prognostic signature and infiltrating immune cells by CIBERSORT.

Results: According to systematic analyzing, a final six splicing events were identified and validated the good prognostic capability in entire TCGA dataset, validation set 1 and validation set 2 by Kaplan-Meier curves (P < 0.0001). The area under the curve (AUC) of ROC curves were also confirmed the high predictive efficiency of the prognostic signature in these three cohorts (AUC = 0.857, 0.895 and 0.788). In order to validate whether prognostic signature highlights a correlation between AS and immune contexture, CIBERSORT was performed to analyze the proportion of tumor-infiltrating immune cells in PC. Based on prognostic signature, we identified survival-related immune cells including CD8 T cells (P = 0.0111), activated CD4 memory T cells (P = 0.0329) and resting mast cells (P = 0.0352).

Conclusion: In conclusion, our study contribute to provide a promising prognostic signature based on six splicing events and revealed prognosis-related immune cells which indeed represented novel tumor drivers and provide potential targets for personalized therapeutic.

Molecular differences across invasive lung adenocarcinoma morphological subgroups

Background

Lung adenocarcinomas (ADCs) show heterogeneous morphological patterns that are classified into five subgroups: lepidic predominant, papillary predominant, acinar predominant, micropapillary predominant and solid predominant. The morphological classification of ADCs has been reported to be associated with patient prognosis and adjuvant chemotherapy response. However, the molecular mechanisms underlying the morphology differences among different subgroups remain largely unknown.

Methods

Using the molecular profiling data from The Cancer Genome Atlas (TCGA) lung ADC (LUAD) cohort, we studied the molecular differences across invasive ADC morphological subgroups.

Results

We showed that the expression of proteins and mRNAs, but not the gene mutations copy number alterations (CNA), were significantly associated with lung ADC morphological subgroups. In addition, expression of the FOXM1 gene (which is negatively associated with patient survival) likely plays an important role in the morphological differences among different subgroups. Moreover, we found that protein abundance of PD-L1 were associated with the malignancy of subgroups. These results were validated in an independent cohort.

Conclusions

This study provides insights into the molecular differences among different lung ADC morphological subgroups, which could lead to potential subgroup-specific therapies.

Gene expression profiling by targeted RNA sequencing in pathological stage I lung adenocarcinoma with a solid component

OBJECTIVES

Solid predominant adenocarcinoma is considered an independent predictor of an unfavorable prognosis in patients with stage I lung adenocarcinoma (LUAD). Furthermore, solid minor components are related to poor prognosis in patients with stage I LUAD. Therefore, it is imperative to elucidate the molecular determinants of the malignant potential of solid components (SC). Several studies reported the gene expression profiling specific for lepidic predominant adenocarcinoma or solid predominant adenocarcinoma, however; there is no report identifying the differentially expressed genes (DEGs) between SC and acinar component (AC) within the same tumor tissue in pathological (p)-stage I LUAD patients.

MATERIALS AND METHODS

LUAD tissue samples containing both SC and AC were obtained from 8 patients with p-stage I LUAD and each component was microdissected. Targeted RNA sequencing was performed by a high-throughput chip-based approach.

RESULTS

In total, 1272 DEGs were identified, including 677 upregulated genes and 595 downregulated genes in SC compared with AC. The most highly upregulated gene was TATA binding protein associated factor 7 (TAF7) and the most highly downregulated gene was homeobox B3 (HOXB3), which acts as a metastasis suppressor. A protein-protein interaction (PPI) network analysis of upregulated genes in SC identified ribosomal protein S27a (RPS27a) as a hub gene with the highest degree. First neighbors of RPS27a included PSMA6, which is a highly promising target for lung cancer. The subnetwork of PD-L1 had 10 first neighbors, including CMTM6, which enhances the ability of PD-L1-expressing tumor cells to inhibit T cells. The staining score for PD-L1 in SC was significantly higher than that in AC by immunohistochemistry (p = 0.001).

CONCLUSION

Our results revealed several new DEGs and key PPI network in SC compared to AC, contributing to understanding the biological features of SC and providing therapeutic targets for early-stage LUAD with SC in the future.

Profiling of prognostic alternative splicing in melanoma

Alternative splicing can lead to the coding of proteins that act as promoters of cancer, which is associated with the progression of cancer. However, to the best of our knowledge, no systematic survival analysis of alternative splicing in melanoma has previously been reported. The present study conducted an in-depth analysis of integrated alternative splicing events detected in 96 patients with melanoma using data obtained from The Cancer Genome Atlas. Prognostic models and an alternative splicing correlation network were built for patients with melanoma. A total of 41,446 mRNA splicing events were detected in 9,780 genes and 2,348 alternative splicing events were identified to be significantly associated with overall survival of patients with melanoma. Of all the events used in the prognostic model, the model with alternate terminator alternative splicing events exhibited the highest efficiency for evaluating the outcome of patients with melanoma, with an area under the curve of 0.902. The present study identified prognostic predictors for melanoma and revealed alternative splicing networks in melanoma that could indicate underlying mechanisms.

Spread through air spaces predicts a worse survival in patients with stage I adenocarcinomas >2 cm after radical lobectomy

Background

The aim of this study was to evaluate the significance of spread through air spaces (STAS) in early lung adenocarcinomas after radical lobectomy and lymphadenectomy.

Methods

A total of 242 patients with lung adenocarcinomas less than 4 cm (8th pStage I) were selected from the lung cancer patients surgically treated from January, 2009 to September, 2011. Pathological review focused on STAS as well as histological subtypes, blood vessel & neural invasion, pathological tumor size etc. Recurrence or disease-free survival (DFS) and overall survival (OS) were compared between patients as stratified by STAS and tumor size.

Results

STAS was observed in 33.47% (81/242) patients, which was significantly correlated with histological predominant subtype (χ²=25.903, P=0.093×10^-3) and differentiation grade (χ²=23.986, P=0.025×10^-3). Patients with STAS (+) showed a comparable PFS (P=0.268) and OS rates (P=0.100) in all stage I cases, but a significant lower PFS (P=0.029) and OS (P=0.013) in tumors within 2< tumors ≤4 cm. Multivariate analysis revealed STAS to be an independent worse prognostic factor in lung adenocarcinomas within 2< tumors ≤4 cm, both for PFS (P=0.004) and OS (P=0.002), while no significant difference was found in patients with tumors ≤2 cm (PFS, P=0.537; OS, P=0.448), after adjusting by other clinicopathological parameters as age, gender, smoking etc.

Conclusions

Presence of STAS was a significant worse predictor for pStage I patients with lung adenocarcinoma >2 cm who underwent radical lobectomy, while it is not significant in patients with tumor ≤2 cm. These findings may be helpful in assessing postoperative therapy stratified by tumor size and STAS status.