Notes

Detection associated with centre genetics linked along with insufficient sleep making use of co-expression analysis.
DFS in adenocarcinoma patients. These results could be driven by the small number of patients and require validation.
A small prognostic effect of KRAS mutation was identified for LCSS, and a trend towards worse LCSS, DFS and OS was noted for KRAS MUT + Gain. A potential predictive effect of concomitant KRAS mutation and copy number gain was observed for DFS in adenocarcinoma patients. These results could be driven by the small number of patients and require validation.
The current National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer (NSCLC) recommend that surgeons sample is not clear. We aimed to define a minimal number of examined lymph nodes for removal or sampling for optimized nodal staging recommendation, with a focus on T
N
M
patients.

A total of 55,101 consecutive patients were selected, including 52,099 patients with US Surveillance, Epidemiology, and End Results (SEER) data and 3,002 patients in a Chinese multicenter database from 11 thoracic referral centers, who underwent complete resection plus lymph node dissection or sampling for stage T
N
M
NSCLC. Propensity score-matching analysis was performed with R software, and a cut-off value was calculated using X-tile software. Survival was evaluated using the Kaplan-Meier method and Cox proportional hazard models.

Five-year survival rates with respect to total examined lymph nodes numbers (examined lymph nodes <10
examined lymph nodes ≥10) were 69% and 64% (group A), 66% and 63% (group B), 62% and 58% (group C), 81% and 75% (group D). There were significant differences between examined lymph nodes <10 and examined lymph nodes >10 in each group (P<0.001).

A minimum of 10 examined lymph nodes would significantly improve T
N
M
NSCLC prognosis and patients' survival rates if implemented as a minimum standard for lymphadenectomy. Therefore, we recommended a minimum of 10 examined lymph nodes for T
N
M
patients.
A minimum of 10 examined lymph nodes would significantly improve T1-3N0M0 NSCLC prognosis and patients' survival rates if implemented as a minimum standard for lymphadenectomy. Therefore, we recommended a minimum of 10 examined lymph nodes for T1-3N0M0 patients.
Lung adenocarcinoma (LUAD) with brain metastasis (BM) occurs frequently and has a poor prognosis. In this study, we aimed to assess the correlation between gene expression signatures and the development of BM after surgical resection of LUAD.

We analyzed the immune-related gene expression profiles of 72 LUADs with and without BM after surgery and verified them using NanoString method and immunohistochemistry (IHC). We matched the Tumor, Node, Metastasis (TNM) stage in the groups with and without BM to minimize the effect of TNM stage. Pathway enrichment studies were also performed.

In the NanoString results, we identified 11 upregulated immune-related gene signature that correlated specifically with BM in the discovery and validation sets [area under the curve (AUC) =0.750 and 0.787, respectively]. The discovery set achieved 94% sensitivity and 62% specificity and the validation set displayed 100% sensitivity and 50% specificity. Eight out of the 11 genes were verified by IHC and had profiles similar to the gene expression profile results (AUC =0.844 for the discovery set and AUC =0.795 for the validation set). Subgroup analysis revealed that 11 immune-related gene signature enabled prediction of BM at all TNM stages. There were no differences in the 11 immune-related gene expression signatures between the primary LUAD samples and the matched brain samples. Pathway enrichment analysis revealed that the cytokine-cytokine receptor interaction pathway was closely correlated with BM.

The 11 identified immune-related gene expression signatures may be potentially clinically useful predictors for BM and can provide patient-specific treatment options.
The 11 identified immune-related gene expression signatures may be potentially clinically useful predictors for BM and can provide patient-specific treatment options.
Despite advances in systemic therapy and improvements in survival for advanced epidermal growth factor receptor (
) mutant non-small cell lung cancer (NSCLC), brain metastasis (BM) remains a poor outcome. Previous studies on risk factors for BM occurrence included unselected patients and biomarker prediction of BM in these populations were not well studied. We aimed to identify the role of epithelial mesenchymal transition (EMT) marker and clinical factors predicting BM in.

mutant NSCLC patients.

Advanced
-mutant NSCLC patients in the King Chulalongkorn Memorial Hospital from January 2013 to December 2017 were included. Vimentin expression was assessed by immunohistochemistry. The correlation between vimentin expression and factors associated with BM occurrence was analyzed by univariate and multivariate analyses.

304 patients were enrolled. Of these, 149 patients (49%) developed BM. In multivariate analysis, the occurrence of BM was associated with age <60 years, metastatic disease at diagnosisrisk populations.
Immune checkpoint inhibitor (ICI)-based immunotherapy has improved the clinical outcome of non-small cell lung cancer (NSCLC). However, current indicators, such as programmed cell death-ligand 1 (PD-L1) expression in tumors or tumor mutational burden (TMB), are not considered ideal biomarkers for prognosis. Thus, there is an urgent requirement for a comprehensive risk scoring system.

In this study, we enrolled 464 NSCLC patients who received ICIs between March 2017 and January 2020 at four clinical centers. Mirdametinib mouse Univariate and multivariate (the logistic and the Cox regression) analyses were conducted to screen clinically relevant variables. Significant parameters (P<0.05) including absolute lymphocyte count (ALC, L), Eastern Cooperative Oncology Group Performance Status (ECOG PS, E) and lung/pleural metastasis (M) were selected for LEM score. Weighted values based on odds ratio and hazard ratio of multiple analyses were assigned to each parameter. LEM score was the sum of weighted values of each variable (Good, 0-1; Intermediate, 2-3; Poor, 4-6).
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