Genomic characteristics in Chinese non-small cell lung cancer patients and its value in prediction of postoperative prognosis

Prognostic factors of patients with human epidermal growth factor receptor 2-positive breast cancer following neoadjuvant therapy: Development and validation of a predictive nomogram

OBJECTIVE

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer exhibits an aggressive phenotype and poor prognosis. The application of neoadjuvant therapy (NAT) in patients with breast cancer can significantly reduce the risks of disease recurrence and improve survival. By integrating different clinicopathological factors, nomograms are valuable tools for prognosis prediction. This study aimed to assess the prognostic value of clinicopathological factors in patients with HER2-positive breast cancer and construct a nomogram for outcome prediction.

METHODS

We retrospectively analyzed the clinicopathological data from 374 patients with breast cancer admitted to the Fourth Hospital of Hebei Medical University between January 2009 and December 2017, who were diagnosed with invasive breast cancer through preoperative core needle biopsy pathology, underwent surgical resection after NAT, and were HER2-positive. Patients were randomly divided into a training and validation set at a ratio of 7:3. Univariate and multivariate survival analyses were performed using Kaplan-Meier and Cox proportional hazards regression models. Results of the multivariate analysis were used to create nomograms predicting 3-, 5-, and 8-year overall survival (OS) rates. Calibration curves were plotted to test concordance between the predicted and actual risks. Harrell C-index and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discriminability of the nomogram prediction model.

RESULTS

All included patients were women, with a mean age of 50 ± 10.4 years (range: 26-72 years). In the training set, both univariate and multivariate analyses identified residual cancer burden (RCB) class, tumor-infiltrating lymphocytes(TILs), and clinical stage as independent prognostic factors for OS, and these factors were combined to construct a nomogram. The calibration curves demonstrated good concordance between the predicted and actual risks, and the C-index of the nomogram was 0.882 (95 % CI 0.863-0.901). The 3-, 5-, and 8-year areas under the ROC curve (AUCs) were 0.909, 0.893, and 0.918, respectively, indicating good accuracy of the nomogram. The calibration curves also demonstrated good concordance in the validation set, with a C-index of 0.850 (95 % CI 0.804-0.896) and 3-, 5-, and 8-year AUCs of 0.909, 0.815, and 0.834, respectively, which also indicated good accuracy.

CONCLUSION

The nomogram prediction model accurately predicted the prognostic status of post-NAT patients with breast cancer and was more accurate than clinical stage and RCB class. Therefore, it can serve as a reliable guide for selecting clinical treatment measures for breast cancer.

Prognosis of immunotherapy for non-small cell lung cancer with CDKN2A loss of function

Background

Immunotherapy has been widely used to treat non-small cell lung cancer (NSCLC) but is only effective in 20% of patients. Cyclin-dependent kinase inhibitor 2A (CDKN2A) is an important tumor suppressor gene, and its loss of function (LOF) is quite common in NSCLC. Pre-clinical studies suggest CDKN2A LOF promotes immune evasion; however, the results in relation to NSCLC are controversial, and debate continues as to the effect of CDKN2A LOF on immunotherapy.

Methods

In this study, we collected the data of 49 CDKN2A LOF and 173 CDKN2A wild-type NSCLC consecutive patients treated by any line of immunotherapy. Through immunohistochemical (IHC) and immunofluorescent (IF) staining, we analyzed the CDKN2A predominant transcription protein p16INK4A in the CDKN2A LOF and CDKN2A wild-type NSCLC patients. Using Kaplan-Meier curves, we also examined the relationship between CDKN2A LOF and immunotherapy.

Results

The IHC and IF staining results showed that most CDKN2A LOF patients were p16INK4A negative, while most CDKN2A wild-type patients were p16INK4A positive. In the LOF group, five patients had partial responses, 35 had stable disease, and nine had progressive disease after the first evaluation of immunotherapy. The LOF group had a median progression-free survival (PFS) time of 4.67 months, while the wild-type group had a median PFS time of 8.63 months [hazard ratio (HR): 0.54; 95% confidence interval (CI): 0.38-0.77; P<0.001]. The LOF group had a median overall survival (OS) time of 9.07 months, while the wild-type group had a median OS time of 21.37 months (HR: 0.42; 95% CI: 0.29-0.61; P<0.001).

Conclusions

Our study revealed that CDKN2A LOF NSCLC patients treated with immune checkpoint inhibitor (ICI) mono-therapy or combined therapy had a worse prognosis than those with CDKN2A wild-type NSCLC. However, our study also suggested that ICI could work quite effectively in selective CDKN2A LOF patients.

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma

BACKGROUND

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC).

METHODS

From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression.

RESULTS

Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue.

CONCLUSION

Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

Comprehensive molecular characterizations of stage I-III lung adenocarcinoma with tumor spread through air spaces

Purpose: The aim of this study is to investigate integrative genomic spectra of stage I-III lung adenocarcinoma with tumor spread through air spaces (STAS). Methods: We retrospectively identified 442 surgically resected lung adenocarcinoma patients of pathological stage I-III in Shanghai Chest Hospital from January 2018 to February 2021. Surgically resected tissues were used for next-generation sequencing (NGS) with a panel of 68 lung cancer-related genes to profile comprehensive molecular characterizations. Results: A total of 442 cases were analyzed, including 221 (50%) STAS-positive (SP) and 221 (50%) STAS-negative (SN) lung adenocarcinoma patients. In total, 440 cases (99.6%) were positive for the overall mutational spectrum, and the higher mutational genes were EGFR, TP53, KRAS, ALK, SMAD4, and ERBB2 (62%, 42%, 14%, 10%, 7%, and 7%, respectively). Compared with the SN population, there was significantly lower EGFR alteration in the single-nucleotide variant (SNV) mutation spectrum (52.5% vs 69.7%, p < 0.001) and significantly higher TP53 alteration in the SP population (49.8% vs 34.8%, p = 0.002). EGFR L858R missense mutation (19.5% vs 37.6%, p < 0.001) and ERBB2 exon 20 indel mutation (1.8% vs 5.9%, p = 0.045) were more frequent in the SN population. The detection rate of ALK fusion rearrangements in the SP population was significantly higher than that in the SN population (13.1% vs 2.3%, p < 0.001). In the analysis of signaling pathways, no significant difference was discovered between SP and SN patients. No difference in 1-year disease-free survival was observed between SP and SN patients in this study. Conclusion: Significant differences exist in stage I-III lung adenocarcinoma patients with STAS in molecular characterizations.

Prognostic role of multiple abnormal genes in non-small-cell lung cancer

BACKGROUND

Non-small-cell lung cancer (NSCLC) has the highest morbidity and mortality rates among all malignant tumor types. Although therapies targeting the mutated genes such as KRAS have been used in the clinic for many years, the prognosis remains poor. Therefore, it is necessary to further study the aberrant expression or mutation of non-target genes affecting the survival and prognosis.

AIM

To explore the impact of simultaneous abnormalities of multiple genes on the prognosis and survival of patients.

METHODS

We used R packages to analyze gene expression data and clinical data downloaded from The Cancer Genome Atlas (TCGA) database. We also collected samples from 85 NSCLC patients from the First People’s Hospital of Jingzhou City and retrospectively followed the patients. Multivariate Cox regression analysis and survival analysis were performed.

RESULTS

Analysis of gene expression data from TCGA revealed that the overexpression of the following single genes affected overall survival: TP53 (P = 0.79), PTEN (P = 0.94), RB1 (P = 0.49), CTNNB1 (P = 0.24), STK11 (P = 0.32), and PIK3CA (P = 0.013). However, the probability of multiple genes (TP53, PTEN, RB1, and STK11) affecting survival was 0.025. Retrospective analysis of clinical data revealed that sex (hazard ratio [HR] = 1.29; [95%CI: 0.64-2.62]), age (HR = 1.05; [95%CI: 1.02-1.07]), smoking status (HR = 2.26; [95%CI: 1.16-4.39]), tumor histology (HR = 0.58; [95%CI: 0.30-1.11]), cancer stage (HR = 16.63; [95%CI: 4.8-57.63]), epidermal growth factor receptor (EGFR) mutation (HR = 1.82; [95%CI: 1.05-3.16]), abundance (HR = 4.95; [95%CI: 0.78-31.36]), and treatment with tyrosine kinase inhibitors (TKIs) (HR = 0.58; [95%CI: 0.43-0.78]) affected patient survival. Co-occurring mutations of TP53, PTEN, RB1, and STK11 did not significantly affect the overall survival of patients receiving chemotherapy (P = 0.96) but significantly affected the overall survival of patients receiving TKIs (P = 0.045).

CONCLUSION

Co-occurring mutation or overexpression of different genes has different effects on the overall survival and prognosis of NSCLC patients. Combined with TKI treatment, the co-occurring mutation of some genes may have a synergistic effect on the survival and prognosis of NSCLC patients.

Genomic Alteration Spectrum of Non-Small Cell Lung Cancer Patients in East-China Characterized by Tumor Tissue DNA and Cell-Free DNA

Introduction

From an oncologic perspective, genetic detection is becoming a frontline clinical test, used to identify actionable alterations for targeted therapy, monitor molecular clonal tumor evolution, indicate disease progression and prognosis, and predict medication efficacy and resistance. From analysis of both tumor tissue and cell-free DNA from a large cohort of non-small cell lung cancer patients in East-China, we characterized the full spectrum of genomic alterations.

Methods

The study comprised 3000 unpaired samples including 1351 tumor tissue DNA (tDNA) and 1649 cell-free circulating tumor DNA (cfDNA) samples, from which 67 cancer-related genes were sequenced and the genetic alteration profiles were depicted. Integrative molecular analyses identified the frequently mutated genes, uncovered co-occurring somatic alterations, described the distribution of hotspot variants, analyzed the frequency of variant alleles, and notably distinguished actionable, novel variants.

Results

The most commonly affected genes were EGFR, TP53, KRAS, CDKN2A, and PIK3CA in both tDNA and cfDNA samples. EGFR and CTNNB1, PIK3CA and PTEN, ERBB2 and SMO were found to have frequent co-occurring alterations in tDNA samples, while EGFR and SMO, KRAS and PDGFRA, PIK3CA and KDR were in cfDNA samples. A large number of primary druggable variants were identified in tDNA samples, while numerous drug-resistance variants, rare actionable variants, and non-EGFR actionable variants were detected in cfDNA samples. Novel variants were enriched in KDR, KIT, TP53, ABL1, FGFR1 in tDNA samples while the majority of novel variants were distributed in PDGFRA, EGFR, KIT, ROS1, BRCA2 in cfDNA samples. Variant allele frequency in tDNA samples was significantly (P < 0.001) higher than that in cfDNA samples.

Conclusion

The results revealed considerable differences in the alteration characteristics between the two kinds of specimens. To date, this study represents the largest real-world investigation of its kind, derived from the largest number of patients in East-China. It reinforced and expanded the mechanism of molecular analysis of neoplastic genetic profiles.

Integrated analysis of patients with KEAP1/NFE2L2/CUL3 mutations in lung adenocarcinomas

Objectives

To explore the clinical features, molecular characteristics, and immune landscape of lung adenocarcinoma patients with KEAP1/NFE2L2/CUL3 mutations.

Methods

The multi‐omics data from the GDC‐TCGA LUAD project of The Cancer Genome Atlas (TCGA) database were downloaded from the Xena browser. The estimate of the immune infiltration was implemented by using the GSVA analysis and CIBERSORT. The status of KEAP1/NFE2L2/CUL3 mutation in 50 LUAD samples of our department was detected by using Sanger sequencing, following the relative expression level of differentially expressed genes (DEGs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) was validated by IHC and real‐time quantitative polymerase chain reaction (RT‐qPCR).

Results

The Kaplan–Meier and multivariable Cox regression analyses demonstrated that KEAP1/NFE2L2/CUL3 mutations had independent prognostic value for OS and PFS in LUAD patients. The differential analysis detected 207 upregulated genes (like GSR/UGT1A6) and 447 downregulated genes (such as PIGR). GO, KEGG, and GSEA analyses demonstrated that DEGs were enriched in glutamate metabolism and the immune response. The constructed ceRNA network shows the linkage of differential lncRNAs and mRNAs. Three hundred and nine somatic mutations were detected, alterations in immune infiltration DNA methylations and stemness scores were also founded between the two groups. Eight mutated LUAD patients were detected by Sanger DNA sequencing in 50 surgical patients. GSR and UGT1A6 were validated to express higher in the Mut group, whereas the expression of PIGR was restrained. Furthermore, the IHC staining conducted on paraffin‐embedded tissue emphasizes the consistency of our result.

Conclusion

This research implemented the comprehensive analysis of KEAP1/NFE2L2/CUL3 somatic mutations in the LUAD patients. Compared with the wild type of LUAD patients, the Mut group shows a large difference in clinical features, RNA sequence, DNA methylation, and immune infiltrations, indicating complex mechanism oncogenesis and also reveals potential therapeutic targets.

EGFR-Mutated Squamous Cell Lung Cancer and Its Association With Outcomes

Background

The therapeutic efficacy of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in advanced EGFR-mutant lung squamous cell carcinoma (SCC) patients remains uncertain. Furthermore, the factors underlying the responsiveness have not been fully investigated. We therefore investigated the link between genomic profiles and EGFR-TKI efficacy.

Material and Methods

We consecutively enrolled stage IV, EGFR-mutant, and EGFR-TKI–treated patients with SCC. Patients with EGFR wild-type lung SCC and EGFR-mutant lung adenocarcinoma were consecutively enrolled as controls, and next-generation sequencing (NGS) was performed.

Results

In total, 28 EGFR-mutant lung SCC, 41 EGFR-mutant lung adenocarcinoma, and 40 EGFR wild-type lung SCC patients were included. Among the patients with EGFR mutations, shorter progression-free survival (PFS) was observed in SCC compared to adenocarcinoma (4.6 vs. 11.0 months, P<0.001). Comparison of the genomic profiles revealed that EGFR-mutant SCC patients had similar mutation characteristics to EGFR-mutant adenocarcinoma patients, but differed from those with EGFR wild-type SCC. Further exploration of EGFR-mutant SCC revealed that mutations in CREBBP (P = 0.005), ZNF217 (P = 0.016), and the Wnt (P = 0.027) pathway were negatively associated with PFS. Mutations in GRM8 (P = 0.025) were associated with improved PFS.

Conclusions

EGFR-mutant lung SCC has a worse prognosis than EGFR-mutant adenocarcinoma. Mutations in other genes, such as CREBBP, ZNF217, GRM8, or Wnt that had implications on PFS raise the possibility of understanding mechanisms of resistance to EGFR-TKI in lung SCC, which will aid identification of potential beneficial subgroups of patients with EGFR-mutant SCCs receiving EGFR-TKIs.

Advances in Lung Cancer Driver Genes Associated With Brain Metastasis

Brain metastasis, one of the common complications of lung cancer, is an important cause of death in patients with advanced cancer, despite progress in treatment strategies. Lung cancers with positive driver genes have higher incidence and risk of brain metastases, suggesting that driver events associated with these genes might be biomarkers to detect and prevent disease progression. Common lung cancer driver genes mainly encode receptor tyrosine kinases (RTKs), which are important internal signal molecules that interact with external signals. RTKs and their downstream signal pathways are crucial for tumor cell survival, invasion, and colonization in the brain. In addition, new tumor driver genes, which also encode important molecules closely related to the RTK signaling pathway, have been found to be closely related to the brain metastases of lung cancer. In this article, we reviewed the relationship between lung cancer driver genes and brain metastasis, and summarized the mechanism of driver gene-associated pathways in brain metastasis. By understanding the molecular characteristics during brain metastasis, we can better stratify lung cancer patients and alert those at high risk of brain metastasis, which helps to promote individual therapy for lung cancer.

Comprehensive Molecular Characterizations of Chinese Patients With Different Subtypes of Lung Squamous Cell Carcinoma

Background

This study aims to profile integrative genomic spectra of Chinese patients with different subtypes of lung squamous cell carcinoma (LUSC) and explore potential molecular prognosis factors.

Methods

We retrospectively identified 204 surgically resected LUSC patients in Shanghai Chest Hospital who underwent capture-based targeted next-generation sequencing (NGS) with a panel of 68 lung cancer‐related genes from September 2017 to January 2019. NGS was used to profile comprehensive molecular characterizations.

Results

Of 204 cases, 114 (55.9%) were keratinizing squamous cell carcinoma (KSCC), 77 (37.7%) were non-keratinizing squamous cell carcinoma (NKSCC), 13 (6.4%) were basaloid squamous cell carcinoma (BSCC), respectively. All subtypes presented similarly high proportions of mutations, including TP53, CDKN2A, and NOTCH1. A comparable prevalence of FGFR1 amplifications was identified between KSCC and NKSCC (11.4 versus 26.9%, p = 0.007). Compared with NKSCC, IGF1R amplifications were more frequent in BSCC (0 versus 15.4%, p = 0.019). We found cases with TP53 alterations had less EGFR alterations in KSCC (P = 0.013, OR = 0.158). Compared with TCGA cohorts, our Chinese cohorts exhibited statistic differences in both somatic mutations and signaling pathways. We found that STK 11 alterations and TOP2A alterations were significantly associated with higher risk of recurrence in patients with LUSC.

Conclusions

Significant differences exist among three subtypes of LUSC in molecular characterizations.