The average copy number variation (CNVA) of chromosome fragments is a potential surrogate for tumor mutational burden in predicting responses to immunotherapy in non-small-cell lung cancer

A Predictive Network-Based Immune Checkpoint Blockade Immunotherapeutic Signature Optimizing Patient Selection and Treatment Strategies

Immune checkpoint blockade (ICB) therapy has brought significant advancements to the field of oncology. However, the diverse responses among patients highlight the need for more accurate predictive tools. In this study, insights are drawn from tumor-immunology pathways, and a novel network-based ICB immunotherapeutic signature, termed ICBnetIS, is constructed. The signature is derived from advanced biological network-based computational strategies involving co-expression networks and molecular interactions networks. The efficacy of ICBnetIS is established through its association with enhanced patient survival and a robust immune response characterized by diverse immune cell infiltration and active anti-tumor immune pathways. The validation process positions ICBnetIS as an effective tool in predicting responses to ICB therapy, analyzing ICB data from a broad collection of over 700 samples from multiple cancer types of more than 15 datasets. It achieves an aggregated prediction AUC of 0.784, which outperforms the other nine renowned immunotherapeutic signatures, indicating the superior predictive capability of ICBnetIS. To sum up, the findings suggest ICBnetIS as a potent tool in predicting ICB therapy responses, offering significant implications for patient selection and treatment optimization in oncology. The study highlights the role of ICBnetIS in advancing personalized treatment strategies, potentially transforming the clinical landscape of ICB therapy.

Integrated exome sequencing and microarray analyses detected genetic defects and underlying pathways of hepatocellular carcinoma

We performed whole exome sequencing (WES) and microarray analysis to detect somatic variants and copy number alterations (CNAs) for underlying mechanisms in a case series of hepatocellular carcinoma (HCC) with paired DNA samples from tumor and adjacent nontumor tissues. Clinicopathologic findings based on Edmondson-Steiner (E-S) grading, Barcelona-Clinic Liver Cancer (BCLC) stages, recurrence, and survival status and their associations with tumor mutation burden (TMB) and CNA burden (CNAB) were evaluated. WES from 36 cases detected variants in the TP53, AXIN1, CTNNB1, and SMARCA4 genes, amplifications of the AKT3, MYC, and TERT genes, and deletions of the CDH1, TP53, IRF2, RB1, RPL5, and PTEN genes. These genetic defects affecting the p53/cell cycle control, PI3K/Ras, and β-catenin pathways were observed in approximately 80% of cases. A germline variant in the ALDH2 gene was detected in 52% of the cases. Significantly higher CNAB in patients with poor prognosis by E-S grade III, BCLC stage C, and recurrence than patients with good prognosis by grade III, stage A, grade III and nonrecurrence was noted. Further analysis on a large case series to correlate genomic profiling with clinicopathologic classifications could provide evidence for diagnostic interpretation, prognostic prediction, and target intervention on involved genes and pathways.

Mutational and Transcriptional Characterization Establishes Prognostic Models for Resectable Lung Squamous Cell Carcinoma

Background

The prognosis of non-small cell lung cancer (NSCLC) patients has been comprehensively studied. However, the prognosis of resectable (stage I-IIIA) lung squamous cell carcinoma (LUSC) has not been thoroughly investigated at genomic and transcriptional levels.

Methods

Data of genomic alterations and transcriptional-level changes of 355 stage I-IIIA LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database, together with the clinicopathological information (training cohort). A validation cohort of 91 patients was retrospectively recruited. Data were analyzed and figures were plotted using the R software.

Results

Training cohort was established with 355 patients. TP53 (78%), TTN (68%), CSMD3 (39%), MUT16 (36%) and RYR2 (36%) were genes with the highest mutational frequency. BRINP3, COL11A1, GRIN2B, MUC5B, NLRP3 and TENM3 exhibited significant higher mutational frequency in stage III (P < 0.05). Patients with stage III also exhibited significantly higher tumor mutational burden (TMB) than those with stage I (P < 0.01). The mutational status of 10 genes were found to have significant stratification on patient prognosis. TMB at threshold of 25 percentile (TMB = 2.39 muts/Mb) also significantly stratified the patient prognosis (P = 0.0003). Univariate and multivariate analyses revealed TTN, ADGRB3, MYH7 and MYH15 mutational status and TMB as independent risk factors. Further analysis of transcriptional profile revealed many significantly up- and down-regulated genes, and multivariate analysis found the transcriptional levels of seven genes as independent risk factors. Significant factors from the multivariate analyses were used to establish a Nomogram model to quantify the risk in prognosis of individual LUSC patients. The model was validated with a cohort containing 91 patients, which showed good predicting efficacy and consistency.

Conclusion

The influencing factors of prognosis of stage I-III LUSC patients have been revealed. Risk factors including gender, T stage, cancer location, and the mutational and transcriptional status of several genes were used to establish a Nomogram model to assess the patient prognosis. Subsequent validation proved its effectiveness.

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear.

Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database.

Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk.

Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Association between plasma somatic copy number variations and response to immunotherapy in patients with programmed death-ligand 1-negative non-small cell lung cancer

Objective

To determine how patients with non-small cell lung cancer (NSCLC) with programmed death-ligand 1 (PD-L1)-negative and/or a low tumor mutation burden status benefit from immune checkpoint inhibitors (ICI).

Methods

We determined the plasma cell-free DNA profiles of 25 patients with PD-L1-negative advanced NSCLC before ICI therapy using low-coverage whole-genome sequencing.

Results

Elevated cell-free copy number variations (CNVs) were associated with progressive disease, with a cutoff CNV score of 0.10 evaluated with an area under the curve of 0.790 in PD-L1-negative NSCLC. CNV changes were also correlated with poor survival. Progression-free survival and overall survival were both significantly shorter in CNVhigh compared with CNVlow patients.

Conclusions

Cell-free CNV may be a useful peripheral blood biomarker for predicting the response to ICIs in patients with NSCLC.