The impact of CDCA5 expression on the immune microenvironment and its potential utility as a biomarker for PD-L1/PD-1 inhibitors in lung adenocarcinoma.

BACKGROUND: Studies have highlighted the important role of cell division cycle associated 5 (CDCA5) in tumor-associated immune dysfunction. We studied immune dysfunction based on CDCA5 expression in lung adenocarcinoma and investigated its potential as a biomarker for patients undergoing anti-programmed death protein-1/ programmed death ligand-1 (PD-1/PD-L1) inhibitor therapy. METHODS: We used the CIBERSORTx algorithm to investigate the immune cell distribution based on CDCA5 and explored its potential as a biomarker for PD-1/PD-L1 therapy using Tumor Immune Dysfunction and Exclusion in three lung adenocarcinoma datasets. Thus, we validated the role of CDCA5 as a biomarker in patients treated with PD-1/PD-L1 inhibitors. We also investigated the pathways through which CDCA5 regulates PD-L1 expression in a cell line. RESULTS: The high CDCA5 expression group showed elevated interferon gamma signature, CD274 expression, CD8+ T cell levels, tumor mutation burden, and microsatellite instability. Higher CDCA5 expression was associated with poorer prognosis in patients not treated with PD-1/PD-L1 inhibitors. However, in patients treated with PD-1/PD-L1 inhibitors, higher CDCA5 expression correlated with better response rates and prognosis. CDCA5 expression positively correlated with inhibitory immune checkpoint molecules. CDCA5 regulated the expression of PD-L1 through the ANXA/AKT pathway, and combined suppression of CDCA5 and PD-L1 synergistically inhibited cell proliferation. CONCLUSIONS: CDCA5 served as a promising biomarker for patients undergoing PD-L1/PD-1 inhibitor treatment, and co-inhibition of CDCA5 and PD-L1 could serve as an effective therapeutic strategy.

Role of chemokines CXCL9, CXCL10, CXCL11, and CXCR3 in the serum and minor salivary gland tissues of patients with Sjögren's syndrome.

This study aimed to investigate the serum and expression levels of C-X-C motif chemokine ligand 9 (CXCL9), CXCL10, CXCL11, and CXC receptor 3 (CXCR3) in minor salivary glands (MSGs) of patients with primary Sjögren's syndrome (pSS), and to explore their correlations with clinical parameters. Serum samples from 49 patients diagnosed with pSS, 33 patients with rheumatoid arthritis (RA), and 30 healthy controls (HCs) were collected for measurements of CXCL9, CXCL10, CXCL11, and CXCR3. Additionally, CXCL levels in the MSG tissues were measured in 41 patients who underwent MSG biopsy. Correlations between CXCL and CXCL/CXCR levels in serum/MSG tissues and clinical factors/salivary scintigraphy parameters were analyzed. Serum CXCL11 and CXCR3 showed statistically significant differences among patients with pSS and RA and HCs (serum CXCL11, pSS:RA:HC = 235.6 ± 500.1 pg/mL:90.0 ± 200.3 pg/mL:45.9 ± 53.6 pg/mL; p = 0.041, serum CXCR3, pSS:RA:HC = 3.27 ± 1.32 ng/mL:3.29 ± 1.17 ng/mL:2.00 ± 1.12 ng/mL; p < 0.001). Serum CXCL10 showed a statistically significant difference between pSS (64.5 ± 54.2 pg/mL) and HCs (18.6 ± 18.1 pg/mL, p < 0.001), while serum CXCL9 did not exhibit a significant difference among the groups. Correlation analysis of clinical factors revealed that serum CXCL10 and CXCL11 levels positively correlated with erythrocyte sedimentation rate (r = 0.524, p < 0.001 and r = 0.707, p < 0.001, respectively), total protein (r = 0.375, p = 0.008 and r = 0.535, p < 0.001, respectively), globulin (r = 0.539, p < 0.001 and r = 0.639, p < 0.001, respectively), and European Alliance of Associations for Rheumatology SS Disease Activity Index (r = 0.305, p = 0.033 and r = 0.321, p = 0.025). Additionally, serum CXCL10 negatively correlated with the Schirmer test score (r = - 0.354, p = 0.05), while serum CXCL11 positively correlated with the biopsy focus score (r = 0.612, p = 0.02). In the MSG tissue, the percentage of infiltrating CXCL9-positive cells was highest (75.5%), followed by CXCL10 (29.1%) and CXCL11 (27.9%). In the correlation analysis, CXCL11-expressing cells were inversely related to the mean washout percentage on salivary gland scintigraphy (r = - 0.448, p = 0.007). Our study highlights distinct serum and tissue chemokine patterns in pSS, emphasizing CXCL9's potential for early diagnosis. This suggests that CXCL10 and CXCL11 are indicators of disease progression, warranting further investigation into their roles in autoimmune disorders beyond pSS.

Changes in the expression of cell interaction-related pathways during brain metastasis in lung adenocarcinoma: Gene expression and immunohistochemical analysis.

BACKGROUND: Brain metastasis (BM) is a prevalent prognostic event in the development of lung adenocarcinoma (LUAD) with a poor prognosis. Alterations in gene or protein expression during various phases of BM remain unclear. METHODS: We performed gene expression and pathway analyses using a metastasis-related gene panel on 12 lung tissues from patients with confirmed BM, 12 lung tissues from patients without BM, and 12 matched brain tissues from patients with confirmed BM during follow-up after LUAD surgery. The results of the gene expression analysis were validated by immunohistochemistry. RESULTS: Cell interaction-related pathways (such as focal adhesion, extracellular matrix-receptor interaction, and proteoglycans in cancer) showed the greatest differences among the three groups. Expression of the cell interaction-related pathway was highest in the lung sample of BM group and lowest in the matched brain tissue. Using a machine learning model, a signature of 20 genes from cell interaction-related pathways accurately predicted BM (area under the curve score of 0.792 and an accuracy rate of 0.875). Immunohistochemical analysis showed higher expression of proteins associated with cell interaction-related genes and a mesenchymal phenotype in the lung sample of BM group than in those without BM or matched brain tissue. CONCLUSIONS: LUAD acquires the characteristics of the cell interaction-related pathway that leads to the development of BM, with a significant decrease in expression following brain colonization.

Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset.

BACKGROUND: Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between the miRNA expression profiles and BM occurrence in patients with LUAD remains unclear. METHODS: We conducted an analysis to identify miRNAs in tissue samples that exhibited different expression levels between patients with and without BM. Using a machine learning approach, we confirmed whether the miRNA profile could be a predictive tool for BM. We performed pathway analysis of miRNA target genes using a matched mRNA dataset. RESULTS: We selected 25 miRNAs that consistently exhibited differential expression between the two groups of 32 samples. The 25-miRNA profile demonstrated a strong predictive potential for BM in both Group 1 and Group 2 and the entire dataset (area under the curve [AUC] = 0.918, accuracy = 0.875 in Group 1; AUC = 0.867, accuracy = 0.781 in Group 2; and AUC = 0.908, accuracy = 0.875 in the entire group). Patients predicted to have BM, based on the 25-miRNA profile, had lower survival rates. Target gene analysis of miRNAs suggested that BM could be induced through the ErbB signaling pathway, proteoglycans in cancer, and the focal adhesion pathway. Furthermore, patients predicted to have BM based on the 25-miRNA profile exhibited higher expression of the epithelial-mesenchymal transition signature, TWIST, and vimentin than those not predicted to have BM. Specifically, there was a correlation between EGFR mRNA levels and BM. CONCLUSIONS: This 25-miRNA profile may serve as a biomarker for predicting BM in patients with LUAD.

Prediction of Responsiveness to PD-L1/PD-1 Inhibitors Using miRNA Profiles Associated With PD-L1 Expression in Lung Adenocarcinoma and Squamous Cell Carcinoma.

BACKGROUND/AIM: MicroRNAs (miRNAs) regulate programmed cell death ligand 1 (PD-L1) and play a crucial role in tumor immune response. However, the relationship between miRNA expression patterns and PD-L1 remains unclear in both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). We investigated PD-L1-related miRNAs that can predict treatment response in patients treated with PD-L1/PD-1 inhibitors. PATIENTS AND METHODS: We selected miRNAs that were correlated with PD-L1 expression within the LUAD and LUSC datasets obtained from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). We validated whether the miRNA profile could be used to predict the prognosis of patients treated with PD-L1/PD-1 inhibitors. RESULTS: Based on four public datasets, we selected 66 and 23 miRNAs associated with PD-L1 expression in LUAD and LUSC, respectively. From the above miRNAs, we identified 5 miRNAs in LUSC and 1 miRNA in LUAD that could predict the response to PD-L1/PD-1 inhibitors in a validation set of patients treated with PD-L1/PD-1 inhibitors. In LUSC, the miRNA profile exhibited a high predictive capability for the response to PD-L1/PD-1 treatment [area under the curve (AUC)=0.963] and accurately predicted prognosis (p=0.031). In LUAD, the miRNA profile was relatively less predictive than in LUSC (AUC=0.691 and p=0.213). Additionally, we observed variations in the PD-L1-associated miRNA profiles, as well as in the associated pathways, between LUAD and LUSC. CONCLUSION: The PD-L1-associated miRNA profile may predict treatment response in LUSC patients treated with PD-L1/PD-1 inhibitors and help select the PD-L1/PD-1 inhibitor treatment group.

Characteristics of the immune microenvironment associated with RRM2 expression and its application to PD-L1/PD-1 inhibitors in lung adenocarcinoma.

Recent studies have indicated that RRM2 plays a crucial part in the tumor immune microenvironment. According to the expression of RRM2, we evaluated immune cell infiltration, immunotherapy biomarkers, and the expression of immune checkpoint molecules in four lung adenocarcinoma (LUAD) datasets. We employed the Tumor Immune Dysfunction and Exclusion (TIDE) and CIBERSORTx algorithms to examine the patterns of immune cell distribution and evaluate the responses to anti-programmed death protein-1/programmed death ligand-1 (PD-1/PD-L1) therapy in three publicly available LUAD datasets. These findings were corroborated using a validation group comprising patients who received treatment with PD-1/PD-L1 inhibitors. Additionally, we conducted experiments using LUAD cell lines to investigate how RRM2 affects the expression of PD-L1. In comparison to the low RRM2 group, the high RRM2 group exhibited a high interferon gamma signature, high T-cell-inflamed signature, high CD274 expression, high CD8+ T cell levels, low cancer-associated fibroblasts, and low M2 macrophages, according to TIDE analysis in the three LUAD datasets. Analysis of the three LUAD datasets using CIBERSORTx confirmed a positive correlation between RRM2 and CD8+ T cells, and this finding was validated by immunohistochemistry in a separate validation set. In the three LUAD datasets without PD-1/PD-L1 inhibitor treatment, higher RRM2 expression was associated with a poorer prognosis. However, in the LUAD dataset treated with PD-1/PD-L1 inhibitors, higher RRM2 expression was associated with better prognosis. In the three datasets, the high-RRM2 group exhibited higher expression of inhibitory immune checkpoint molecules. In a LUAD cell line study, we discovered that RRM2 regulates PD-L1 expression through the ANXA1/AKT pathway. The expression of RRM2 shows promise as a predictive biomarker for PD-1/PD-L1 inhibitors in LUAD patients, and it may represent a new target to overcome resistance to PD-L1/PD-1 therapies.

The comprehensive expression of BCL2 family genes determines the prognosis of diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a prevalent and aggressive non-Hodgkin's lymphoma, and 40% of patients succumb to death. Despite numerous clinical trials aimed at developing treatment strategies beyond the conventional R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) regimen, there have been no positive results thus far. Although the selective BCL2 inhibitor venetoclax has shown remarkable efficacy in chronic lymphocytic leukemia, its therapeutic effect in DLBCL was limited. We hypothesized that the limited therapeutic effect of venetoclax in DLBCL may be attributed to the complex expression and interactions of BCL2 family members, including BCL2. Therefore, we aimed to comprehensively analyze the expression patterns of BCL2 family members in DLBCL. We analyzed 157 patients with de novo DLBCL diagnosed at Asan Medical Center and Ajou University Hospital. The mRNA expression levels of BCL2 family members were quantified using the NanoString technology. BCL2 family members showed distinct heterogeneous expression patterns both intra- and inter-patient. Using unsupervised hierarchical cluster analysis, we were able to classify patients with similar BCL2 family expression pattern and select groups with clear prognostic features, C1 and C6. In the group with the best prognosis, C1, the expression of pro-apoptotic and pro-apoptotic BH3-only group gene expressions were increased, while anti-apoptotic group expression was significantly increased in both C1 and C6. Based on this, we generated the BCL2 signature score using the expression of pro-apoptotic genes BOK and BCL2L15, and anti-apoptotic gene BCL2. The BCL2 signature score 0 had the best prognosis, score 1/2 had intermediate prognosis, and score 3 had the worst prognosis (EFS, p = 0.0054; OS, p = 0.0011). Multivariate analysis, including COO and IPI, showed that increase in the BCL2 signature score was significantly associated with poor prognosis for EFS, independent of COO and IPI. The BCL2 signature score we proposed in this study provides information on BCL2 family deregulation based on the equilibrium of pro-versus anti-apoptotic BCL2 family, which can aid in the development of new treatment strategies for DLBCL in the future.

Immune profiles according to EGFR mutant subtypes and correlation with PD-1/PD-L1 inhibitor therapies in lung adenocarcinoma.

Background: We examined the distributions of 22 immune cell types and the responses to PD-1/PD-L1 inhibitors according to EGFR mutation profile, in three independent datasets of lung adenocarcinoma (LUAD). Methods: We used CIBERSORTx to analyze the distributions of immune cells, and tumor immune dysfunction and exclusion (TIDE) or tumor mutation burden (TMB) to analyze responses to anti-PD-1/PD-L1 therapy, in two public LUAD datasets. The results were verified with a validation set that included patients treated with PD-1/PD-L1 inhibitors. Results: Compared to EGFR mutants, EGFR wild-type carcinomas had higher numbers of CD8+ T cells, CD4 memory activated T cells and neutrophils, and lower numbers of resting dendritic cells and resting mast cells, in two of the datasets. In our subgroup analyses, CD8+ T cells and CD4 memory activated T cells were more numerous in EGFR rare variants than in wild-types, L858R mutants, and exon 19 deletion mutants. In our TIDE or TMB analyses, EGFR rare variants were predicted to respond better to PD-1/PD-L1 inhibitors than wild-types, L858R mutants, and exon 19 deletion mutants. In the validation set verified by immunohistochemical staining, levels of CD8+ T cells in the EGFR rare variant or wild-type groups were significantly higher than in the EGFR L858R and exon 19 deletion groups. In patients treated with PD-1/PD-L1 inhibitors, the survival rates of patients with EGFR wild-type and rare mutant carcinomas were higher than those with L858R and exon 19 deletion carcinomas. Conclusion: The EGFR rare mutation form of LUAD shows a higher immune activation state compared to wild-type, L858R, and exon 19 deletion variants, indicating it as a potential target for PD-1/PD-L1 inhibitor therapy.

Comparison of histological and molecular features of pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma.

Pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma are pediatric B cell lymphomas with similar clinical characteristics but distinct histological features. We investigated the differences between pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma by comparing their histological and molecular characteristics. A total of 5 pediatric-type follicular lymphoma and 11 pediatric nodal marginal zone lymphoma patients were included in the study. In the histological review, 5 of the 16 cases showed overlapping morphological features of pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma; hence, they were reclassified as "mixed type." In molecular analysis, using panel-based massively parallel sequencing, MAP2K1, TNFRSF14, and IRF8 mutations were found in 6, 3, and 2 of the 11 pediatric nodal marginal zone lymphoma patients, respectively, and IRF8 mutation was found in one of the five pediatric-type follicular lymphoma patients. There were no significant differences in genetic alterations established from the histologically reclassified diagnosis as well as the initial diagnosis. Pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma showed morphological overlap in some cases, and no difference between the two was found upon molecular analysis. These findings suggest the possibility that pediatric-type follicular lymphoma and pediatric nodal marginal zone lymphoma are single entity pediatric B-cell lymphoma with broad morphological spectrum.

Prognostic and predictive value of YTHDF1 and YTHDF2 and their correlation with tumor-infiltrating immune cells in non-small cell carcinoma.

Background: YTH domain-containing family protein 1 (YTHDF1) or YTHDF2 play crucial roles in cancer immunotherapy. We examine the expression of YTHDF1, YTHDF2, CD8, CD4, and FOXP3 to identify their prognostic or predictive role for PD-1/PD-L1 inhibitor in non-small cell lung cancer (NSCLC). Methods: Immunohistochemical expression of YTHDF1, YTHDF2, CD8, CD4, and FOXP3 was investigated in 266 patients not receiving PD-1/PD-L1 inhibitors and in 59 patients receiving PD-1/PD-L1 inhibitors. Immunohistochemical results were verified using mRNA dataset obtained from The Cancer Genome Atlas (TCGA) database. Results: Immunohistochemical expression of YTHDF1 or YTHDF2 was negatively associated with CD8- and CD4-positive T cells; however, the same expression was positively associated with FOXP3-positive T cells. YTHDF1 or YTHDF2 mRNA expression was also negatively associated with CD8- and CD4-positive T cells. Gene set enrichment analysis revealed that low YTHDF1 was related to immune hot tumor gene sets. Expression of YTHDF1 or YTHDF2 was negatively associated with expression of most immune checkpoints. YTHDF1 and YTHDF2 were predictive markers of response to PD-1/PD-L1 inhibitors. YTHDF1 or YTHDF2 expression was associated with better prognosis. YTHDF1 has an immune hot profile in both cell types, whereas YTHDF2 is only seen in adenocarcinoma. Conclusion: Low YTHDF1 or YTHDF2 reflects an immune hot tumor signature and may serve as a predictor or prognostic marker.

Estrogen-responsive cancer-associated fibroblasts promote invasive property of gastric cancer in a paracrine manner via CD147 production.

Estrogen signaling has been extensively studied, especially in cancers that express estrogen receptor alpha (ERα). However, little is known regarding the effect of estrogen on cancer-associated fibroblasts (CAFs). Here, we explored the role of estrogen signaling of CAFs in gastric cancer (GC) progression. We investigated the phenotypic changes in CAFs upon 17ß-estradiol (E2) treatment using ERα-negative/positive CAFs, and the conditioned media (CM) collected from these were compared with regard to cancer cell proliferation, migration, and invasion. A paracrine factor was found using a cytokine array and was confirmed using qRT-PCR, western blotting, and enzyme-linked immunosorbent assays. ERα-CD147-matrix metalloproteinase (MMP) axis was confirmed by knockdown experiments using specific siRNAs. We found that a subset of CAFs expressed ERα. ERα-positive CAFs were responsive to E2, inducing ERα expression in a dose-dependent manner. Although E2 did not induce the proliferation of ERα-positive CAFs, the CM from E2-bound ERα-positive CAFs significantly promoted cancer cell migration and invasion. Cytokine array revealed that CD147 was induced in ERα-positive CAFs upon E2 treatment; this was mediated via ERα. Increased CD147 upregulated MMP2 and MMP9 in CAFs, and also influenced cancer cells in a paracrine manner to increase MMPs and CD147 in cancer cells. High CD147 expression in tumor tissue was associated with a worse prognosis in GC patients. Our data suggest that estrogen signaling activation in CAFs and the byproduct CD147 are among the critical mediators between the interplay of CAFs and cancer cells to facilitate cancer progression.

Correlations between salivary gland scintigraphy and histopathologic data of salivary glands in patients with primary Sjogren's syndrome.

OBJECTIVES: Our aim was to evaluate the association between salivary gland scintigraphy and the clinical parameters, including histological characteristics of salivary glands, in patients with primary Sjogren's syndrome (pSS). METHODS: Forty-one pSS patients were included in the study. The patients who had received salivary gland scintigraphy and minor salivary gland biopsy were retrospectively analyzed. Salivary gland scintigraphy was interpreted via semi-quantitative methods obtained by calculating the peak uptake and washout of each gland using regions of interest. All specimens were examined by pathologists for focus scores and leukocyte common antigen (LCA) to determine the degree of inflammatory infiltration. RESULTS: The mean age of pSS patients was 46.4 years, 82.9% were female, and the mean duration of symptoms was 2.5 years. The focus score was negatively correlated to the mean peak uptake (r = ‒0.396; p = 0.019), mean uptake (r = ‒0.388; p = 0.021), and mean percentage washout (r = ‒0.391; p = 0.02). In addition, the focus score and number of LCA positive cells per mm2 were correlated with the clinical parameters including erythrocyte sedimentation rate, globulin, rheumatoid factor, unstimulated whole saliva, and stimulated whole saliva flow. The number of LCA positive cells per mm2 was negatively correlated to leukocytes and hemoglobin. CONCLUSION: Although the diagnostic role of salivary gland biopsy is widely accepted and features in the classification criteria of Sjogren's syndrome, salivary gland scintigraphy may be an acceptable alternative method especially if a non-invasive test is required.

Elevated expression of TLR2 and its correlation with disease activity and clinical manifestations in adult-onset Still's disease.

This study investigated the role of Toll-like receptor 1 (TLR1), TLR2, TLR4, TLR7, and TLR9 in patients with adult-onset Still's disease (AOSD). This study included 20 patients with AOSD and 15 healthy controls (HCs). TLR expression in the peripheral blood was quantified using flow cytometry; TLR expression pattern, in the skin lesions and lymph nodes (LNs) of patients with AOSD, was evaluated immunohistochemically. Significantly higher mean intensities of cells presenting TLR2 and TLR7 from whole blood were observed in patients with AOSD than in HCs. TLR2 expression in whole cells correlated with systemic scores, levels of lactate dehydrogenase and ferritin and serum levels of interleukin-1ß (IL-1ß), IL-6, and IL-18. The percentage of TLR2-positive inflammatory cells was higher in skin biopsy samples from patients with AOSD than those in HCs. TLR9-expressing positive inflammatory cell counts were higher in skin lesions from patients with AOSD than those in the HC, eczema, and psoriasis groups. The expression levels of TLR1, TLR4, TLR7, and TLR9 were higher in LNs of patients with AOSD than in those with T cell lymphoma and reactive lymphadenopathy. Circulating TLR2- and TLR7-positive cells may contribute to the pathogenesis of AOSD. Furthermore, immunohistochemical staining for TLRs in skin lesions and LNs may aid in differentiating AOSD from similar conditions.

Significance of Single-cell Level Dual Expression of BCL2 and MYC Determined With Multiplex Immunohistochemistry in Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a fatal heterogenous neoplasm. Recent clinical trials have failed partly due to nebulous criteria for defining high-risk patients. Patients with double-expresser lymphoma (DEL) have a poor prognosis and are resistant to conventional treatment. However, many diagnostic and clinical controversies still surround DEL partly due to the arbitrariness of criteria for the diagnosis of DEL. In this study, we suggest a refined method for diagnosing DEL by evaluating the concurrent expression of BCL2 and MYC at the single-cell level (dual-protein-expressing lymphoma [DUEL]). For the proof of concept, a multiplex immunofluorescence assay for CD20, BCL2, and MYC was performed and quantitatively analyzed using spectral image analysis in patients. The analysis results and clinical applicability were verified by using dual-color immunohistochemistry performed on 353 independent multicenter patients who had been uniformly treated with standard therapy. DUEL showed significantly worse overall survival (OS) and event-free survival (EFS) (P=0.00011 and 0.00035, respectively). DUEL status remained an independent adverse prognostic variable with respect to the International Prognostic Index risk and the cell of origin. Moreover, the advantage of determining DUEL status by dual-color immunohistochemistry was shown by more robust classification and more homogeneous high-risk subgroup patient identification in both training (n=271) (OS: P<0.0001; EFS: P<0.0001) and validation sets (n=82) (OS: P=0.0087; EFS: P<0.0001). This concept of DUEL is more consistent with carcinogenesis and has greater practical utility, hence it may provide a better basis for both basic and clinical research for the development of new therapeutics.

Intrinsic and Extrinsic Transcriptional Profiles That Affect the Clinical Response to PD-1 Inhibitors in Patients with Non-Small Cell Lung Cancer.

Using a machine learning method, we investigated the intrinsic and extrinsic transcriptional profiles that affect the clinical response to PD-1 inhibitors in 57 patients with non-small cell lung cancer (NSCLC). Among the top 100 genes associated with the responsiveness to PD-1 inhibitors, the proportion of intrinsic genes in lung adenocarcinoma (LUAD) (69%) was higher than in NSCLC overall (36%) and lung squamous cell carcinoma (LUSC) (33%). The intrinsic gene signature of LUAD (mean area under the ROC curve (AUC) = 0.957 and mean accuracy = 0.9) had higher predictive power than either the intrinsic gene signature of NSCLC or LUSC or the extrinsic gene signature of NSCLC, LUAD, or LUSC. The high intrinsic gene signature group had a high overall survival rate in LUAD (p = 0.034). When we performed a pathway enrichment analysis, the cell cycle and cellular senescence pathways were related to the upregulation of intrinsic genes in LUAD. The intrinsic signature of LUAD also showed a positive correlation with other immune checkpoint targets, including CD274, LAG3, and PDCD1LG2 (Spearman correlation coefficient > 0.25). PD-1 inhibitor-related intrinsic gene patterns differed significantly between LUAD and LUSC and may be a particularly useful biomarker in LUAD.

Genetic profiles of subcutaneous panniculitis-like T-cell lymphoma and clinicopathological impact of HAVCR2 mutations.

Recent studies identified germline mutations in HAVCR2 (encoding T-cell immunoglobulin mucin 3) as a genetic factor that predisposes to subcutaneous panniculitis-like T-cell lymphoma (SPTCL). However, the differences between HAVCR2-mutated (HAVCR2MUT) and HAVCR2 wild-type (HAVCR2WT) SPTCLs remain unclear. A nationwide cohort of 53 patients with SPTCL diagnosed at 8 Korean institutions was established. Whole-exome sequencing and RNA-sequencing were performed on 8 patients in the discovery set. In the validation set, targeted gene sequencing or direct sequencing of HAVCR2 was performed. Of 49 patients with available HAVCR2 status, 25 (51.0%) were HAVCR2Y82C. HAVCR2Y82C was associated with younger age (P = .001), development of hemophagocytic lymphohistiocytosis or hemophagocytic lymphohistiocytosis-like systemic illness (P < .001), and short relapse-free survival (RFS) (P = .023). Most mutated genes in SPTCLs were involved in immune responses, epigenetic modifications, and cell signaling. Mutations in UNC13D, PIAS3, and KMT2D were more frequent in HAVCR2WT SPTCLs. At the gene expression level, HAVCR2Y82C SPTCLs were enriched in genes involved in IL6-JAK-STAT3 signaling and in tumor necrosis factor-α signaling via NF-κB. CCR4 was significantly upregulated in HAVCR2WT SPTCLs both at the messenger RNA level and at the protein level. We established a risk stratification system for SPTCL by integrating clinical and histopathological features, including age and HAVCR2 mutation status. This risk stratification system was strongly associated with RFS (P = .031). In conclusion, the HAVCR2Y82C mutation was common in Korean patients with SPTCL and was associated with unique clinicopathological and genetic features. Combining clinicopathological parameters could aid in predicting prognosis for patients with SPTCL.

Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling.

Using a machine learning approach with a gene expression profile, we discovered a tumor nonimmune-microenvironment-related gene expression signature, including extracellular matrix (ECM) remodeling, epithelial-mesenchymal transition (EMT), and angiogenesis, that could predict brain metastasis (BM) after the surgical resection of 64 lung adenocarcinomas (LUAD). Gene expression profiling identified a tumor nonimmune-microenvironment-related 17-gene expression signature that significantly correlated with BM. Of the 17 genes, 11 were ECM-remodeling-related genes. The 17-gene expression signature showed high BM predictive power in four machine learning classifiers (areas under the receiver operating characteristic curve = 0.845 for naïve Bayes, 0.849 for support vector machine, 0.858 for random forest, and 0.839 for neural network). Subgroup analysis revealed that the BM predictive power of the 17-gene signature was higher in the early-stage LUAD than in the late-stage LUAD. Pathway enrichment analysis showed that the upregulated differentially expressed genes were mainly enriched in the ECM-receptor interaction pathway. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. The tumor nonimmune-microenvironment-related gene expression signatures found in this study are important biological markers that can predict BM and provide patient-specific treatment options.

An immune-related gene expression signature predicts brain metastasis in lung adenocarcinoma patients after surgery: gene expression profile and immunohistochemical analyses.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The 11 identified immune-related gene expression signatures may be potentially clinically useful predictors for BM and can provide patient-specific treatment options.