A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma.

BACKGROUND: Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. This study aims to investigate the potential correlation between ferroptosis and the prognosis of lung adenocarcinoma (LUAD). METHODS: RNA-seq data were collected from the LUAD dataset of The Cancer Genome Atlas (TCGA) database. Based on ferroptosis-related genes, differentially expressed genes (DEGs) between LUAD and paracancerous specimens were identified. The univariate Cox regression analysis was performed to screen key genes associated with the prognosis of LUAD. LUAD patients were divided into the training set and validation set. Then, we screened out key genes and built a prognostic prediction model involving 5 genes using the least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation and the multivariate Cox regression analysis. After dividing LUAD patients based on the median level of risk score as cut-off value, the generated prognostic prediction model was validated in the validation set. Moreover, we analyzed the somatic mutations, and estimated the scores of immune infiltration in the high-risk and low-risk groups. Functional enrichment analysis of DEGs was performed as well. RESULTS: High-risk scores indicated the worse prognosis of LUAD. The maximum area under curve (AUC) of the training set and the validation set in this study was 0.7 and 0.69, respectively. Moreover, we integrated the age, gender, and tumor stage to construct the composite nomogram. The charts indicated that the AUC of LUAD cases with the survival time of 1, 3 and 5 years was 0.698, 0.71 and 0.73, respectively. In addition, the mutation frequency of LUAD patients in the high-risk group was significantly higher than that in the low-risk group. Simultaneously, DEGs were mainly enriched in ferroptosis-related pathways by analyzing the functional results. CONCLUSIONS: This study constructs a novel LUAD prognosis prediction model involving 5 ferroptosis-related genes, which can be used as a promising tool for decision-making of clinical therapeutic strategies of LUAD.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD).

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients. METHODS: Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature. RESULTS: A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041-39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779-3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis. CONCLUSION: Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Dynamic analysis of circulating tumor DNA to predict prognosis and monitor therapeutic response in metastatic relapsed cervical cancer.

Limited and inefficient treatment options exist for metastatic relapsed cervical cancer (MRCC), and there are currently no reliable indicators to guide therapeutic selection. We performed deep sequencing analyses targeting 322 cancer-related genes in plasma cell-free DNA and matched white blood cells in 173 serial blood samples from 82 locally advanced CC (LACC) or MRCC patients and when possible during treatment. We identified five notable nonsynonymous mutant genes (PIK3CA, BRAF, GNA11, FBXW7 and CDH1) in the MRCC samples as the metastatic relapse significantly mutated (MSG) genes and found that MRCC patients with any detectable MSG mutations had significantly shorter progression-free survival (PFS) (P = .005) and overall survival (OS) (P = .007) times than those without detectable MSG mutations. Additionally, analyses of matched prechemotherapy and postchemotherapy plasma revealed that a reduction in the number of MSG mutations after chemotherapy was significantly associated with partial remission (PR) and stable disease (SD) (P = .007). Among the patients included in the longitudinal tracking ctDNA analysis, an increase in MSG mutations was observed earlier in response to disease progression than radiological imaging. Our results outline the mutation profiles of MRCC. We show how longitudinal monitoring with ctDNA in liquid biopsy samples provides both predictive and prognostic information during treatment.

Longitudinal whole-genome sequencing reveals the evolution of MPAL.

PURPOSE: Mixed phenotype acute leukemia (MPAL) is a rare subtype of acute leukemia and its progressive genomic basis over time remains unclear. We aimed to investigate the longitudinal genomic evolution of MPAL from diagnosis to relapse. METHODS: We performed whole genome sequencing (WGS) on bone marrow (BM) samples obtained at the four stages of this disease in a male patient with Philadelphia chromosome positive (Ph+) MPAL, including primary, complete cytogenetic remission (CCR), complete molecular remission (CMR), and relapse stage during the 3 year follow-up period. RESULTS: 156 single-nucleotide variants (SNVs) and indels were detected, which exhibited distinctive evolutionary behaviors. Seventeen mutations disappeared quickly upon DCTER treatment and never came back. Seven mutations, although disappeared initially, reoccurred with the withdrawal of TKI treatment. Notably, ten mutations emerged in spite of the active DCTER chemotherapy. Moreover, copy number loss played critical roles in monitoring MPAL progression, displaying 7, 0, 0, and 383 losses at the stages of primary, CCR, CMR, and relapse respectively. CONCLUSION: This longitudinal genomic investigation of the Ph+ MPAL patient established one MPAL evolution model in which the primary tumor acquired additional variations leading to tumor relapse. Moreover, the event of copy number loss remained a valuable hallmark in the progression of MPAL.

Recursive Paleohexaploidization Shaped the Durian Genome.

The durian (Durio zibethinus) genome has recently become available, and analysis of this genome reveals two paleopolyploidization events previously inferred as shared with cotton (Gossypium spp.). Here, we reanalyzed the durian genome in comparison with other well-characterized genomes. We found that durian and cotton were actually affected by different polyploidization events: hexaploidization in durian ∼19-21 million years ago (mya) and decaploidization in cotton ∼13-14 mya. Previous interpretations of shared polyploidization events may have resulted from the elevated evolutionary rates in cotton genes due to the decaploidization and insufficient consideration of the complexity of plant genomes. The decaploidization elevated evolutionary rates of cotton genes by ∼64% compared to durian and explained a previous ∼4-fold over dating of the event. In contrast, the hexaploidization in durian did not prominently elevate gene evolutionary rates, likely due to its long generation time. Moreover, divergent evolutionary rates probably explain 98.4% of reconstructed phylogenetic trees of homologous genes being incongruent with expected topology. The findings provide further insight into the roles played by polypoidization in the evolution of genomes and genes, and they suggest revisiting existing reconstructed phylogenetic trees.

An Overlooked Paleotetraploidization in Cucurbitaceae.

Cucurbitaceae plants are of considerable biological and economic importance, and genomes of cucumber, watermelon, and melon have been sequenced. However, a comparative genomics exploration of their genome structures and evolution has not been available. Here, we aimed at performing a hierarchical inference of genomic homology resulted from recursive paleopolyploidizations. Unexpectedly, we found that, shortly after a core-eudicot-common hexaploidy, a cucurbit-common tetraploidization (CCT) occurred, overlooked by previous reports. Moreover, we characterized gene loss (and retention) after these respective events, which were significantly unbalanced between inferred subgenomes, and between plants after their split. The inference of a dominant subgenome and a sensitive one suggested an allotetraploid nature of the CCT. Besides, we found divergent evolutionary rates among cucurbits, and after doing rate correction, we dated the CCT to be 90-102 Ma, likely common to all Cucurbitaceae plants, showing its important role in the establishment of the plant family.