Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tumors. Therefore, in this study, we utilised a CT deep learning (DL) model to distinguish GNs with lobulation and spiculation signs from solid lung adenocarcinomas (LADCs), to improve the diagnostic accuracy of preoperative diagnosis. METHODS: 420 patients with pathologically confirmed GNs and LADCs from three medical institutions were retrospectively enrolled. The regions of interest in non-enhanced CT (NECT) and venous contrast-enhanced CT (VECT) were identified and labeled, and self-supervised labels were constructed. Cases from institution 1 were randomly divided into a training set (TS) and an internal validation set (IVS), and cases from institutions 2 and 3 were treated as an external validation set (EVS). Training and validation were performed using self-supervised transfer learning, and the results were compared with the radiologists' diagnoses. RESULTS: The DL model achieved good performance in distinguishing GNs and LADCs, with area under curve (AUC) values of 0.917, 0.876, and 0.896 in the IVS and 0.889, 0.879, and 0.881 in the EVS for NECT, VECT, and non-enhanced with venous contrast-enhanced CT (NEVECT) images, respectively. The AUCs of radiologists 1, 2, 3, and 4 were, respectively, 0.739, 0.783, 0.883, and 0.901 in the (IVS) and 0.760, 0.760, 0.841, and 0.844 in the EVS. CONCLUSIONS: A CT DL model showed great value for preoperative differentiation of GNs with lobulation and spiculation signs from solid LADCs, and its predictive performance was higher than that of radiologists.

Clinically relevant immune subtypes based on alternative splicing landscape of immune-related genes for lung cancer advanced PPPM approach.

Background: Alternative splicing (AS) occurs in the process of gene post-transcriptional process, which is very important for the correct synthesis and function of protein. The change of AS pattern may lead to the change of expression level or function of lung cancer-related genes, and then affect the occurrence and development of lung cancers. The specific AS pattern might be used as a biomarker for early warning and prognostic assessment of a cancer in the framework of predictive, preventive, and personalized medicine (PPPM; 3PM). AS events of immune-related genes (IRGs) were closely associated with tumor progression and immunotherapy. We hypothesize that IRG-AS events are significantly different in lung adenocarcinomas (LUADs) vs. controls or in lung squamous cell carcinomas (LUSCs) vs. controls. IRG-AS alteration profiling was identified to construct IRG-differentially expressed AS (IRG-DEAS) signature models. Study on the selective AS events of specific IRGs in lung cancer patients might be of great significance for further exploring the pathogenesis of lung cancer, realizing early detection and effective monitoring of lung cancer, finding new therapeutic targets, overcoming drug resistance, and developing more effective therapeutic strategies, and better used for the prediction, diagnosis, prevention, and personalized medicine of lung cancer. Methods: The transcriptomic, clinical, and AS data of LUADs and LUSCs were downloaded from TCGA and its SpliceSeq databases. IRG-DEAS events were identified in LUAD and LUSC, followed by their functional characteristics, and overall survival (OS) analyses. OS-related IRG-DEAS prognostic models were constructed for LUAD and LUSC with Lasso regression, which were used to classify LUADs and LUSCs into low- and high-risk score groups. Furthermore, the immune cell distribution, immune-related scores, drug sensitivity, mutation status, and GSEA/GSVA status were analyzed between low- and high-risk score groups. Also, low- and high-immunity clusters and AS factor (SF)-OS-related-AS co-expression network and verification of cell function of CELF6 were analyzed in LUAD and LUSC. Results: Comprehensive analysis of transcriptomic, clinical, and AS data of LUADs and LUSCs identified IRG-AS events in LUAD (n = 1607) and LUSC (n = 1656), including OS-related IRG-AS events in LUAD (n = 127) and LUSC (n = 105). A total of 66 IRG-DEAS events in LUAD and 89 IRG-DEAS events in LUSC were identified compared to controls. The overlapping analysis between IRG-DEASs and OS-related IRG-AS events revealed 14 OS-related IRG-DEAS events for LUAD and 16 OS-related IRG-DEAS events for LUSC, which were used to identify and optimize a 12-OS-related-IRG-DEAS signature prognostic model for LUAD and an 11-OS-related-IRG-DEAS signature prognostic model for LUSC. These two prognostic models effectively divided LUAD or LUSC samples into low- and high-risk score groups that were closely associated with OS, clinical characteristics, and tumor immune microenvironment, with significant gene sets and pathways enriched in the two groups. Moreover, weighted gene co-expression network (WGCNA) and nonnegative matrix factorization method (NMF) analyses identified four OS-relevant subtypes of LUAD and six OS-relevant subtypes of LUSC, and ssGSEA identified five immunity-relevant subtypes of LUAD and five immunity-relevant subtypes of LUSC. Interestingly, splicing factors-OS-related-AS network revealed hub molecule CELF6 was significantly related to the malignant phenotype in lung cancer cells. Conclusions: This study established two reliable IRG-DEAS signature prognostic models and constructed interesting splicing factor-splicing event networks in LUAD and LUSC, which can be used to construct clinically relevant immune subtypes, patient stratification, prognostic prediction, and personalized medical services in the PPPM practice. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00366-4.

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer.

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

The detection of PD-L1 expression on liquid-based cytology in pleural effusion of lung adenocarcinoma and its prognostic evaluation: Between paired liquid-based cytology and cell block samples.

BACKGROUND: Programmed death-ligand 1 (PD-L1) expression levels measured by immunohistochemistry have been proven to predict the outcome of immunotherapy in lung adenocarcinoma (LUAD). However, data on PD-L1 expression on liquid-based cytology (LBC) in malignant pleural effusion (MPE) is scarce. METHODS: This study cohort included 60 cases with MPE suffering from LUAD. PD-L1 SP263 assay was used for immunocytochemistry (ICC) on LBC and matched cell block (CB) to validate ICC protocols on LBC slides. Clinical outcomes were analyzed based on immunotherapy and PD-L1 tumor proportion scores (TPS) on LBC slides and CBs. RESULTS: PD-L1 expression with TPS ≥1% was lower in LBCs than in CBs (33 of 60 [55.0%] vs. 35 of 60 [58.3%]; p = .687). Even with the TPS ≥50% threshold, PD-L1 expression was lower in LBCs (10 of 60 [16.7%] vs. 15 of 60 [25%]; p = .125). Epidermal growth factor receptor (EGFR) exon 20 mutation, tumor cell proportion, and pleural fluid neutrophil-to-lymphocyte ratio were related to PD-L1 expression on CBs (p = .013, p = 0.022, and p = .011), respectively. Patients with subsequent immune checkpoint inhibitor therapy remained a better prognostic in subgroups of PD-L1 positive expression on LBC slides (TPS ≥1%, p = .041). CONCLUSIONS: LBC specimens had comparable performance to CBs in PD-L1 assessment and predicting treatment response to PD-L1-defined therapy.

Proteomic analysis reveals LRPAP1 as a key player in the micropapillary pattern metastasis of lung adenocarcinoma.

Objectives: Lung adenocarcinomas have different prognoses depending on their histological growth patterns. Micropapillary growth within lung adenocarcinoma, particularly metastasis, is related to dismal prognostic outcome. Metastasis accounts for a major factor leading to mortality among lung cancer patients. Understanding the mechanisms underlying early stage metastasis can help develop novel treatments for improving patient survival. Methods: Here, quantitative mass spectrometry was conducted for comparing protein expression profiles among various histological subtypes, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma (including acinar and micropapillary [MIP] types). To determine the mechanism of MIP-associated metastasis, we identified a protein that was highly expressed in MIP. The expression of the selected highly expressed MIP protein was verified via immunohistochemical (IHC) analysis and its function was validated by an in vitro migration assay. Results: Proteomic data revealed that low-density lipoprotein receptor-related protein-associated protein 1 (LRPAP1) was highly expressed in MIP group, which was confirmed by IHC. The co-expressed proteins in this study, PSMD1 and HSP90AB1, have been reported to be highly expressed in different cancers and play an essential role in metastasis. We observed that LRPAP1 promoted lung cancer progression, including metastasis, invasion and proliferation in vitro and in vivo. Conclusion: LRPAP1 is necessary for MIP-associated metastasis and is the candidate novel anti-metastasis therapeutic target.

Overexpression of VEGFA mediated by HIF-1 is associated with higher rate of spread through air spaces in resected lung adenocarcinomas.

BACKGROUND: Spread through air spaces (STAS), a newly identified pattern of invasion in lung adenocarcinomas (LACs), is an unfavorable prognostic factor for patients with LAC, but the molecular characteristics and mechanisms underlying STAS have not been adequately explored. METHODS: In total, 650 pathologically confirmed invasive LAC patients who underwent curative resection between December 2019 and April 2020 were reviewed. Disease-free survival (DFS) and overall survival (OS) were analyzed using the log-rank test and the Cox proportional hazards model. A comparative deep sequencing analysis was conducted to explore the molecular characteristics underlying STAS. Vascular endothelial growth factor A (VEGFA) expression was evaluated by immunoblotting and immunohistochemical analysis using fresh tumor tissue and tissue microarray. RESULTS: STAS was more prevalent in patients with a smoking history (p < 0.001), high pathological TNM stage (p < 0.001), lymphovascular invasion (p < 0.001), visceral pleural invasion (p < 0.001) and micropapillary/solid histological subtypes (p < 0.001). STAS-negative patients had better DFS (p < 0.001) and OS (p = 0.003) compared to STAS-positive patients with invasive LACs, especially in the lymph node-negative population (p < 0.001). After RNA-sequencing analysis, hypoxia-inducible factor-1 (HIF-1) signaling was enriched and appeared to be strongly correlated with STAS, and more STAS-positive individuals were detected in the higher VEGFA-expressing group (p = 0.042). CONCLUSIONS: We demonstrated that STAS was an independent prognostic marker of poor clinical outcome, especially in lymph node-negative patients, and that higher VEGFA expression mediated by HIF-1 signaling was associated with an increased STAS rate.

Downregulated CDH3 is correlated with a better prognosis for LUAD and decreases proliferation and migration of lung cancer cells.

BACKGROUND: CDH3 is a glycoprotein with a single-span transmembrane domain that mediates cell-to-cell adhesion. Abnormal expression of CDH3 is associated with a poor prognosis in patients with breast, thyroid, colorectal carcinomas and glioblastoma. Soluble CDH3 in pleural effusions can be used as a marker for real-time monitoring of resistance to first- and second-generation EGFR-TKIs. The CDH3 mechanism underlying lung adenocarcinomas (LUADs) has not been established. OBJECTIVE: This study analyzed the correlation between CDH3 expression and lung cancer prognosis and the effect of down-regulation CDH3 expression on the proliferation and migration of lung cancer cells. METHODS: CDH3 expression was studied using the Oncomine, TIMER, PanglaoDB, and GEPIA databases. The effect of CDH3 on clinical prognosis was assessed with GEPIA, the PrognoScan database, and Kaplan-Meier plotter. The relationship between CDH3 to immune infiltrating cells was explored using TIMER and TISIDB. The function of CDH3 in lung cancer cell lines was determined by CCK-8 and wound healing assays in vitro. Furthermore, RNA sequencing was used to identify key signaling pathways and differentially-expressed genes. RESULTS: LUAD tissues had higher CDH3 expression compared with normal tissues and were associated with worse overall survival in patients with LUAD. CDH3 expression had positive associations with infiltration of CD4 + T cells, Tregs and exhausted T cells, but negative associations with infiltration of B cells in patients with LUAD. CCK-8 and wound healing assays revealed that downregulation of CDH3 inhibited the proliferation and migration of cells. KEGG analysis revealed that the TGF-beta signaling pathways were demonstrated to be enriched pathways for genes negatively regulated by knockdown of CDH3. CONCLUSION: CDH3 expression affects proliferation and migration of lung cancer cells and might serve as a potential prognostic marker in LUAD patients.

CD44v6 downregulation as a prognostic factor for distant recurrence in resected stage I lung adenocarcinomas.

CD44 and CD44 variant isoforms have been reported as contributing factors to cancer progression. In this study, we aimed to assess whether CD44 and its variant isoforms were correlated with the prognostic factors for distant metastasis in stage I lung adenocarcinomas using tissue microarray and immunohistochemistry. In this single-center retrospective study, we analyzed the data of 490 patients with stage I lung adenocarcinoma resected between 1999 and 2016. We constructed tissue microarrays and performed immunohistochemistry for CD44s, CD44v6, and CD44v9. The risk of disease recurrence and its associations with clinicopathological risk factors were assessed. CD44v6 expression was significantly associated with recurrence. Patients with CD44v6-negative tumors had a significantly increased risk of developing distant recurrence than patients with CD44v6-positive tumors (5-year cumulative incidence of recurrence (CIR), 10.7% vs. 4.6%; P = 0.009). However, CD44v6-negative tumors were not associated with an increased risk of locoregional recurrence compared to CD44v6-positive tumors (5-year CIR, 6.0% vs. 4.0%; P = 0.39). The overall survival (OS) of patients with CD44v6-negative tumors was significantly lower than that of patients with CD44v6-positive tumors (5-year OS: 87% vs. 94%, P = 0.016). CD44v6-negative tumors were also associated with invasive tumor size and lymphovascular invasion. Even in stage I disease, tumors with negative-CD44v6 expression had more distant recurrences than those with positive-CD44v6 expression and were associated with poor prognosis in resected stage I lung adenocarcinomas. Thus, CD44v6 downregulation may be a prognostic factor for distant metastasis in stage I lung adenocarcinomas.

The role of thyroid transcription factor-1 in differentiating lung adenocarcinomas from non-pulmonary adenocarcinoma effusions.

Effusions, characterized by abnormal fluid accumulations in body cavities, present difficulties in identifying the primary organs of metastatic tumors through cytopathologic investigation, particularly in cancer-related complications. This retrospective cross-sectional laboratory study aimed to investigate the role of thyroid transcription factor-1 (TTF-1) in distinguishing lung adenocarcinomas from non-pulmonary adenocarcinomas in effusions. The study was conducted at Almobarak Cytopathology Laboratory, a private cytopathology laboratory. H&E was used to confirm the histological diagnosis of 58 archived cell blocks. TTF-1 immunostaining patterns were then correlated with the histological diagnosis. Statistical analysis, including numerical and graphical data summaries, was conducted using the Chi-square test in SPSS 23. TTF-1 expression was observed in 20 (34.4%) cases, while 38 (65.5%) cases showed no TTF-1 reaction. Positive TTF-1 was found in pleural fluid in 61.1 % of lung adenocarcinomas, while negative TTF-1 was found in only 3.4%. TTF-1 was not detected in the majority of peritoneal fluid samples. There was a highly significant relationship between pleural fluid, TTF-1, and lung adenocarcinoma (p=0.000). The data provided further evidence that TTF-1 is a useful marker for distinguishing pulmonary adenocarcinomas from non-pulmonary adenocarcinoma tumors.

Whole exome sequencing and MicroRNA profiling of lung adenocarcinoma identified risk prediction features for tumors at stage I and its substages.

OBJECTIVES: About 20% of stage I lung adenocarcinoma (LUAD) patients suffer a relapse after surgical resection. While finer substages have been defined and refined in the AJCC staging system, clinical investigations on the tumor molecular landscape are lacking. MATERIALS AND METHODS: We performed whole exome sequencing, DNA copy number and microRNA profiling on paired tumor-normal samples from a cohort of 113 treatment-naïve stage I Taiwanese LUAD patients. We searched for molecular features associated with relapse-free survival (RFS) of stage I or its substages and validated the findings with an independent Caucasian LUAD cohort. RESULTS: We found sixteen nonsynonymous mutations harbored at EGFR, KRAS, TP53, CTNNB1 and six other genes associated with poor RFS in a dose-dependent manner via variant allele fraction (VAF). An index, maxVAF, was constructed to quantify the overall mutation load from genes other than EGFR. High maxVAF scores discriminated a small group of high-risk LUAD at stage I (median RFS: 4.5 versus 69.5 months; HR = 10.5, 95% CI = 4.22-26.12, P < 0.001). At the substage level, higher risk was found for patients with high maxVAF or high miR-31; IA (median RFS: 32.1 versus 122.8 months, P = 0.005) and IB (median RFS: 7.1 versus 26.2, P = 0.049). MicroRNAs, miR-182, miR-183 and miR-196a were found correlated with EGFR mutation and poor RFS in stage IB patients. CONCLUSION: Distinctive features of somatic gene mutation and microRNA expression of stage I LUAD are characterized to complement the survival prognosis by substaging. The findings open up more options for precision management of stage I LUAD patients.

Integrative analysis of DNA methylomes reveals novel cell-free biomarkers in lung adenocarcinoma.

Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.

INHA acts as a novel and potential biomarker in lung adenocarcinoma and shapes the immune-suppressive tumor microenvironment.

BACKGROUND: INHA expression has been correlated with the development, growth, and progression of multiple cancer types. However, the biological role of INHA has not been investigated in patients with lung adenocarcinoma (LUAD). Here, we performed a comprehensive bioinformatics analysis of the LUAD dataset to determine the mechanisms underlying the regulation of tumorigenesis by INHA. MATERIALS AND METHODS: INHA expression and clinical information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Protein levels in LUAD cell lines and human lung epithelial cells were examined by western blotting. Next, the prognostic value of INHA in LUAD was assessed using Cox regression analysis, while the potential biological functions and the impact on the immune microenvironment of INHA were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Finally, the effect of INHA on LUAD cell proliferation and invasion was determined in vitro and in vivo. RESULTS: We found significantly high mRNA and protein expression levels of INHA in LUAD tissues and cell lines. Additionally, a higher expression of INHA was linked to a shorter overall survival (OS) and a worse pathological stage, while INHA expression was associated with immune cell infiltration and immune-related markers in the LUAD tumor microenvironment. LUAD with high INHA expression tends to be a cold tumor. Furthermore, GO and KEGG enrichment analysis indicated that INHA-related genes were enriched in the cell adhesion and immune signaling pathways of LUAD. INHA promoted LUAD cell proliferation and invasion, in vitro and in vivo, by inducing the EGFR pathway. CONCLUSION: Our findings revealed that INHA is overexpressed in LUAD and is linked to a poor prognosis. Our study demonstrates the potential of INHA as an immunotherapeutic and predictive biomarker in LUAD.

Correlation Between Quantitative Spectral CT Parameters and Ki-67 Expression in Lung Adenocarcinomas Manifesting as Ground-glass Nodules.

OBJECTIVE: We assessed the feasibility of spectral CT imaging for diagnosing lung adenocarcinomas manifesting as ground-glass nodules (GGNs) with varying Ki-67 expression. METHODS: Spectral CT parameters in 116 patients with lung adenocarcinomas manifesting as GGNs were analyzed. Cases were grouped into pre-invasive/minimally invasive adenocarcinoma (pre/MIA) and invasive adenocarcinoma (IA) groups. The Ki-67 labeling index (Ki-67 LI) was measured and compared between the two groups. Ki-67 LI was divided into three grades based on the number of positive-stained cells. Spectral CT parameters (diameter, water, and iodine concentrations of the lesion [WCL and ICL], the slope of the spectral Hounsfield unit curve [λHU], and CT values from 40 to 140 keV [at 10 keV intervals]) were compared among the three different grades. The correlation between quantitative spectral CT imaging parameters and Ki-67 LI was analyzed using Spearman correlation analysis. RESULTS: Ki-67 LI in the IA group was significantly higher than in the pre/MIA group (p < 0.01). Grade 2 had higher diameter, WCL, and monochromatic CT values, and grade 1 had higher ICL and λHU. The WCL and monochromatic CT values were highly and positively correlated with Ki-67 LI. CT40keV had the highest correlation with Ki-67 LI, the diameter was moderately correlated with Ki- 67 LI, and ICL and λHU were weakly correlated with Ki-67 LI. CONCLUSION: Spectral CT, a noninvasive diagnostic method, is valuable for predicting Ki-67 expression higher in IA, thus allowing preoperative evaluation of lung adenocarcinomas manifesting as GGNs.

Systemic analysis of the DNA replication regulator origin recognition complex in lung adenocarcinomas identifies prognostic and expression significance.

BACKGROUND: DNA replication alteration is a hallmark of patients with lung adenocarcinoma (LUAD) and is frequently observed in LUAD progression. Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5, and ORC6 form a replication-initiator complex to mediate DNA replication, which plays a key role in carcinogenesis, while their roles in LUAD remain poorly understood. METHODS: The mRNA and protein expression of ORCs was confirmed by the GEPIA, HPA, CPTAC, and TCGA databases. The protein-protein interaction network was analyzed by the GeneMANIA database. Functional enrichment was confirmed by the Metascape database. The effects of ORCs on immune infiltration were validated by the TIMER database. The prognostic significance of ORCs in LUAD was confirmed by the KM-plot and GENT2 databases. DNA alteration and protein structure were determined in the cBioProtal and PDB databases. Moreover, the protein expression and prognostic value of ORCs were confirmed in our LUAD data sets by immunohistochemistry (IHC) staining. RESULTS: ORC mRNA and protein were significantly increased in patients with LUAD compared with corresponding normal tissue samples. The results of IHC staining analysis were similar result to those of the above bioinformatics analysis. Furthermore, ORC1 and ORC6 had significant prognostic values for LUAD patients. Furthermore, the ORC cooperatively promoted LUAD development by driving DNA replication, cellular senescence, and metabolic processes. CONCLUSION: The ORC, especially ORC1/6, has important prognostic and expression significance for LUAD patients.

Distinct cellular immune profiles in lung adenocarcinoma manifesting as pure ground glass opacity versus solid nodules.

INTRODUCTION: Ground glass opacity featured lung adenocarcinomas (GGO-LUAD) display more indolent biological behavior than solid nodule featured lung adenocarcinomas (SN-LUAD) and have an excellent prognosis. However, the cellular immune characteristics of GGO-LUAD remain poorly understood. METHODS: Immunohistochemistry technique was performed to stain related immune markers (CD8, CD103, CD20, CD138, CD4, FOXP3, CD68, CD163, PD-1 and PD-L1) and TGF-ß from 15 patients with pure GGO-LUAD and 15 patients with SN-LUAD tissue sections (Paired cohort), and then, the related markers with significant differences were verified on 10 patients (Verified cohort) with both pure GGO-LUAD and SN-LUAD. For localization analysis of CD68 + tumor-associated macrophages (TAMs) and FOXP3 + Terg cells in tumor areas, pure GGO-LUAD and SN-LUAD were also stained for simultaneous detection of pan-CK, CD68 and FOXP3 by multiplex immunofluorescence. RESULTS: In the Paired cohort, compared with SN-LUAD, only the infiltration of TAMs and Treg cells was significantly lower in GGO-LUAD. The infiltration of the remaining immune cells including CD8 + T cells, CD4 + T cells, CD103 + T cells, CD20 + B cells and CD138 + Plasma cells in GGO-LUAD, although relatively low, was not significantly different. Meanwhile, the expression of TGF-ß was significantly higher in SN-LUAD. And the above results have also been confirmed in the Verified cohort. Moreover, there was no significantly difference in PD-L1 expression in GGO-LUAD compared to SN-LUAD both in the Paired cohort and Verified cohort. CONCLUSIONS: GGO-LUAD demonstrates an overall less active immune landscape as compared with SN-LUAD. TAMs and TGF-ß may play an important role in the progression of GGO-LUAD. More importantly, PD-L1 expression in GGO-LUAD is comparable to that in SN-LUAD, indicating that there may be other reasons for the insensitivity of GGO-LUAD to immunotherapy.

Genomic landscape of lung adenocarcinomas in different races.

Background: Lung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood. Methods: We analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes. Results: Native Americans had significantly higher rates of insertions and deletions than other races (P<0.001). Among patients with lung adenocarcinomas, EGFR and KRAS were the highest discrepancy genes in the different racial groups (P<0.001). The EGFR exon 21 L858R point mutation was three times higher in Asians than in all other races (P<0.001). Asians, Whites, and Blacks had 4.7%, 3.1%, and 1.8% ALK rearrangement, respectively (P<0.001). White patients had the highest rates of reported KRAS G12C (15.51%) than other races (P<0.001). Whites (17.2%), Blacks (15.1%), and Other (15.7%) had higher rates of STK11 mutation than Asians (3.94%) (P<0.001). RET rearrangement and ERBB2 amplification were more common in Asian patients than in Other racial groups. Apart from point mutations, structural variations, and fusion genes, we identified a significant amount of copy number alterations in each race. Conclusions: The tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.

Afatinib 30 mg in the treatment of common and uncommon EGFR-mutated advanced lung adenocarcinomas: a retrospective, single-center, longitudinal study.

Background: Afatinib 30 mg has been proved to be with comparable efficacy but more tolerable than the dose of 40 mg for Asian patients with non-small cell lung cancer (NSCLC). This study aimed to investigate the clinical outcomes of afatinib at 30 mg/d in the treatment of advanced lung adenocarcinomas (LAD) with common and uncommon epidermal growth factor receptor (EGFR) mutations. Methods: EGFR-mutated advanced LAD patients receiving afatinib (30 mg/d) from January 2017 to November 2021 were retrospectively included. EGFR status was classified into three subtypes, namely common mutations including exon 19 deletions (19del) and exon 21 L858R (21L858R), uncommon mutations including G719X, L861Q, S768I, and complex mutations, and separately exon 20 insertions (20ins). Progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR) and adverse events (AEs) were analyzed during regular follow-up. Results: The overall median PFS of totally 58 included patients was 9.83 [95% confidence index (CI): 5.76-13.91] months. The number of patients with common, uncommon, and 20ins mutations was 32 (55.2%), 19 (32.8%) and 7 (12.1%), respectively. Baseline characteristics did not differ significantly among the three subtypes. The corresponding median PFS was 13.97 (12.06-15.89), 8.48 (0.32-16.64), and 3.78 (1.93-5.64) months, respectively (P=0.002). In the first-line setting, patients with common and uncommon mutations had a significantly longer PFS compared to those with 20ins [14.53 (13.53-15.53) vs. 10.39 (4.87-15.91) vs. 2.37 (0.00-5.11) months, P<0.001]. The first-line ORR showed significant differences among the three subtypes (60% vs. 80% vs. 0.0%, P=0.023). All-grade AEs occurred in 22 patients (37.9%). AEs ≥ grade 3 mainly included diarrhea (8.6%), and none of the patients discontinued treatment due to severe AEs. Conclusions: Afatinib at 30 mg/d is associated with a favorable efficacy and tolerability in the treatment of advanced LAD with common and major uncommon EGFR mutations except 20ins. Further large-scale prospective studies are warranted to confirm our findings.

Genetic determinants of lung cancer: Understanding the oncogenic potential of somatic missense mutations.

BACKGROUND: Treatment of lung cancer is getting more personalized nowadays and medical practitioners are moving away from conventional histology-driven empirical treatments, platinum-based chemotherapy, and other invasive surgical resections and have started adopting alternate therapies in which therapeutic targets are patient's molecular oncogenic drivers. AIM: The aim of the current study is to extract meaningful information from the online somatic mutation data (retrieved from cBioPortal) of 16 most significantly mutated oncogenes in non-small-cell lung cancer (NSCLC), namely EGFR, NRAS, KRAS, HER2 (ERBB2), RET, MET, ROS1, FGFR1, BRAF, AKT1, MEK1 (MAP2K1), PIK3CA, PTEN, DDR2, LKB1 (STK11) and ALK, for improving our understanding of the pathobiology of the lung cancer that can aid decision-making on critical clinical and therapeutic considerations. METHODS: Using an integrated approach comprising 4 steps, the oncogenic potential of 661 missense non-synonymous single nucleotide polymorphisms (nsSNPs) in 16 genes was ascertained using 2059 NSCLC (1575 lung adenocarcinomas, 484 lung squamous cell carcinomas) patients' online mutation data. The steps used comprise sequence/structure homology-based prediction, scoring of conservation of mutated residues and positions, prediction of resulting molecular and functional consequences using machine-learning and structure-guided approach. RESULTS: Out of a total of 661 nsSNPs analyzed, a set of 29 nsSNPs has been identified as conserved high confidence mutations in 10 of 16 genes relevant to the under study. Out of 29 conserved high confidence nsSNPs, 4 nsSNPs (EGFR N1094Y, BRAF M620I, DDR2 R307L, ALK P1350T) have been found to be putative novel rare genetic markers for NSCLC. CONCLUSIONS: The current study, the first of its kind, has provided a list of deleterious non-synonymous somatic mutations in a selected pool of oncogenes that can be considered as a promising target for future drug design and therapy for patients with lung adenocarcinomas and squamous cell carcinomas.

A Nomogram Combined Radiomics and Clinical Features as Imaging Biomarkers for Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma.

Objectives: To develop and validate a nomogram model based on radiomics features for preoperative prediction of visceral pleural invasion (VPI) in patients with lung adenocarcinoma. Methods: A total of 659 patients with surgically pathologically confirmed lung adenocarcinoma underwent CT examination. All cases were divided into a training cohort (n = 466) and a validation cohort (n = 193). CT features were analyzed by two chest radiologists. CT radiomics features were extracted from CT images. LASSO regression analysis was applied to determine the most useful radiomics features and construct radiomics score (radscore). A nomogram model was developed by combining the optimal clinical and CT features and the radscore. The model performance was evaluated using ROC analysis, calibration curve and decision curve analysis (DCA). Results: A total of 1316 radiomics features were extracted. A radiomics signature model with a selection of the six optimal features was developed to identify patients with or without VPI. There was a significant difference in the radscore between the two groups of patients. Five clinical features were retained and contributed as clinical feature models. The nomogram combining clinical features and radiomics features showed improved accuracy, specificity, positive predictive value, and AUC for predicting VPI, compared to the radiomics model alone (specificity: training cohort: 0.89, validation cohort: 0.88, accuracy: training cohort: 0.84, validation cohort: 0.83, AUC: training cohort: 0.89, validation cohort: 0.89). The calibration curve and decision curve analyses suggested that the nomogram with clinical features is beyond the traditional clinical and radiomics features. Conclusion: A nomogram model combining radiomics and clinical features is effective in non-invasively prediction of VPI in patients with lung adenocarcinoma.

Proteomic Quantification of Lysine Acetylation and Succinylation Profile Alterations in Lung Adenocarcinomas of Non-Smoking Females.

Background: Epidemiological surveys in recent years have shown that the incidence of female lung adenocarcinomas has multiplied in both smoking and non-smoking populations. The cause of lung adenocarcinomas is still not clear. Protein post-translational modification is one of the causes of the development of cancer cells. Methods: Lung adenocarcinoma and paracancerous tissue samples were collected from female patients with no history of smoking. The differences in protein acetylation and succinylation of cancerous tissues and paracancerous tissues were analysed by LC-MS/MS with a TMT labelling method. We distinguished the differentially modified proteins and annotated these proteins in terms of Go annotation, protein domains, protein complex analysis and KEGG pathway analysis. Results: 972 acetylation sites on 556 proteins were identified, among which 875 Kac sites on 507 proteins were quantified, 2373 succinylation sites on 1205 proteins were identified, and 2205 Ksu sites on 1131 proteins were quantified. The acetylation levels of proteins, which contribute to DNA binding and gene expression regulation, were up-regulated. The proteins for which the succinylation levels were up-regulated were mainly involved in mitochondria carboxylic acid metabolism. We also identified simultaneously up-regulated or down-regulated acetylated and succinylated proteins and depicted their interaction network. Conclusion: This study provides insight into lung adenocarcinomas acetylation and succinylation profile alterations in carcinoma pathogenesis and provides a potential therapeutic target for lung adenocarcinomas.