Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides.

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

Oridonin represses lung cancer cell proliferation and migration by modulating AFAP1-AS1/IGF2BP1.

Oridonin belongs to a small molecule from the Chinese herb Rabdosia rubescens with potent anticancer activity. In spite of the lncRNA AFAP1-AS1 has been proven to exert promoting function in lung cancer, its relationship with oridonin in lung cancer is obscure. Therefore, our study planned to explore the potential of oridonin in lung cancer as well as unveil the regulatory mechanism of oridonin on AFAP1-AS1 in lung cancer cells. In the present study, oridonin inhibited lung cancer cell proliferation, migration, as well as invasion, as evidenced by MTT, wound healing, as well as transwell assays. Besides, we observed that oridonin could downregulate AFAP1-AS1 expression, and overexpressed AFAP1-AS1 could reverse the repressive effects of oridonin on lung cancer cell proliferation, migration, as well as invasion. More importantly, we found that AFAP1-AS1 could bind to IGF2BP1 through starBase prediction and RIP assay. The expression level of IGF2BP1 was also reduced by oridonin treatment but reversed after AFAP1-AS1 overexpression. Additionally, we proved that overexpressed IGF2BP1 could reverse the repressive impacts of oridonin on lung cancer cell proliferation, migration, as well as invasion. Further, in vivo experiments validated the repressive role of oridonin on tumor growth of lung cancer. Together, oridonin inhibits lung cancer cell proliferation as well as migration by modulating AFAP1-AS1/IGF2BP1, and AFAP1-AS1/IGF2BP1 possesses the potential to be a promising therapy targeting for lung cancer, especially in oridonin treatment.

LINC01133 contributes to the malignant phenotypes of non-small cell lung cancer by targeting miR-30b-5p/FOXA1 pathway.

This study aimed to explore the mechanism of action of LINC01133 in non-small cell lung cancer. LINC01133 expression in NSCLC patient tissues and cells was detected by qRT-PCR. After transfecting siRNA-LINC01133 in NSCLC cells, the proliferation and invasive migration ability of the cells were assessed via CCK-8 and Transwell assay, respectively. The sublocalization of LINC01133 in NSCLC cells was analyzed by bioinformatics prediction and nucleoplasm separation assay and RNA-FISH assay. Analysis of the binding relationship between LINC01133, FOXA1 and miR-30b-5p was all through bioinformatics website analysis, dual-luciferase reporter and RNA Pulldown assay. Functional rescue experiments confirmed the character of miR-30b-5p and FOXA1 in LINC01133 regulating the NSCLC cells biological behavior. LINC01133 high expressions were found in NSCLC tissues and cells. siRNA-LINC01133 treatment inhibited NSCLC cells malignant behavior. Mechanistically: LINC01133 promoted FOXA1 expression through adsorption binding of miR-30b-5p. Knocking down miR-30b-5p expression or up-regulating FOXA1 expression was able to reverse siRNA-LINC01133 inhibitory effect of tumor cell malignant behavior. LINC01133 promoted FOX1 expression by competitively binding miR-30b-5p, which attenuated the targeting inhibitory effect of miR-30b-5p on FOXA1 and ultimately promoted proliferation and invasive migration of NSCLC cells.

LINC00472 suppresses non-small cell lung cancer progression via regulating miR-23a-3p/CCL22 axis.

Long non-coding RNA (lncRNA) LINC00472 has a close connection with the development of tumors. The aim was to explore the role of LINC00472 on NSCLC cell biological function in vivo and its potential mechanisms. The mRNA levels of LncRNA 00472 and microRNA-23a-3p, were determined by RT-qPCR. Cell Counting Kit-8, cell scratches and western blot assays were used to analyze the proliferation, migration and level of apoptosis-associated proteins. Luciferase reporter assay validates the binding between LINC00472/CCL22 and miR-23a-3p. LINC00472 and CCL22 were lowly expressed in NSCLC tissues and cells, while miR-23a-3p expression was upregulated. LINC00472 overexpression significantly depressed NSCLC cell cellular behavior, whereas promoting cell death. MiR-23a-3p could reverse these above-mentioned biological behavior changes caused by LINC00472 overexpression. Additionally, LINC00472 increased CCL22 expression through sponging miR-23a-3p. Knocking down CCL22 antagonized the inhibitory effect of LINC00472 on NSCLC cell survival. LINC00472 may reduce the cellular growth, and accelerate death of NSCLC through increasing CCL22 expression by targeting miR-23a-3p.

Knockdown of HE4 suppresses tumor growth and invasiveness in lung adenocarcinoma through regulation of EGFR signaling.

It has been shown that the high expression of human epididymis protein 4 (HE4) in most lung cancers is related to the poor prognosis of patients, but the mechanism of pathological transformation of HE4 in lung cancer is still unclear. The current study is expected to clarify the function and mechanism of HE4 in the occurrence and metastasis of lung adenocarcinoma (LUAD). Immunoblotting evaluated HE4 expression in lung cancer cell lines and biopsies, and through analysis of The Cancer Genome Atlas (TCGA) dataset. Frequent HE4 overexpression was demonstrated in LUAD, but not in lung squamous cell carcinoma (LUSC), indicating that HE4 can serve as a biomarker to distinguish between LUAD and LUSC. HE4 knockdown significantly inhibited cell growth, colony formation, wound healing, and invasion, and blocked the G1-phase of the cell cycle in LUAD cell lines through inactivation of the EGFR signaling downstream including PI3K/AKT/mTOR and RAF/MAPK pathways. The first-line EGFR inhibitor gefitinib and HE4 shRNA had no synergistic inhibitory effect on the growth of lung adenocarcinoma cells, while the third-line EGFR inhibitor osimertinib showed additive anti-proliferative effects. Moreover, we provided evidence that HE4 regulated EGFR expression by transcription regulation and protein interaction in LUAD. Our findings suggest that HE4 positively modulates the EGFR signaling pathway to promote growth and invasiveness in LUAD and highlight that targeting HE4 could be a novel strategy for LUAD treatment.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for lung cancer.

BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR). METHODS: Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant. FINDINGS: In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33. INTERPRETATION: We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.

BACKGROUND: Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets. METHODS: We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups. RESULTS: Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations. CONCLUSIONS: This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.

Tobacco-induced hyperglycemia promotes lung cancer progression via cancer cell-macrophage interaction through paracrine IGF2/IR/NPM1-driven PD-L1 expression.

Tobacco smoking (TS) is implicated in lung cancer (LC) progression through the development of metabolic syndrome. However, direct evidence linking metabolic syndrome to TS-mediated LC progression remains to be established. Our findings demonstrate that 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and benzo[a]pyrene (NNK and BaP; NB), components of tobacco smoke, induce metabolic syndrome characteristics, particularly hyperglycemia, promoting lung cancer progression in male C57BL/6 J mice. NB enhances glucose uptake in tumor-associated macrophages by increasing the expression and surface localization of glucose transporter (GLUT) 1 and 3, thereby leading to transcriptional upregulation of insulin-like growth factor 2 (IGF2), which subsequently activates insulin receptor (IR) in LC cells in a paracrine manner, promoting its nuclear import. Nuclear IR binds to nucleophosmin (NPM1), resulting in IR/NPM1-mediated activation of the CD274 promoter and expression of programmed death ligand-1 (PD-L1). Restricting glycolysis, depleting macrophages, or blocking PD-L1 inhibits NB-mediated LC progression. Analysis of patient tissues and public databases reveals elevated levels of IGF2 and GLUT1 in tumor-associated macrophages, as well as tumoral PD-L1 and phosphorylated insulin-like growth factor 1 receptor/insulin receptor (pIGF-1R/IR) expression, suggesting potential poor prognostic biomarkers for LC patients. Our data indicate that paracrine IGF2/IR/NPM1/PD-L1 signaling, facilitated by NB-induced dysregulation of glucose levels and metabolic reprogramming of macrophages, contributes to TS-mediated LC progression.

HTR2B as a novel biomarker of chronic obstructive pulmonary disease with lung squamous cell carcinoma.

Chronic obstructive pulmonary disease (COPD) is often associated with lung squamous cell carcinoma (LUSC), which has the same etiology (smoking, inflammation, oxidative stress, microenvironmental changes, and genetics). Smoking, inflammation, and airway remodeling are the most important and classical mechanisms of COPD comorbidity in LUSC patients. Cancer can occur during repeated airway damage and repair (airway remodeling). Changes in the inflammatory and immune microenvironments, which can cause malignant transformation of some cells, are currently being revealed in both LUSC and COPD patients. We obtained the GSE76925 dataset from the Gene Expression Omnibus database. Screening for possible COPD biomarkers was performed using the LASSO regression model and a random forest classifier. The compositional patterns of the immune cell fraction in COPD patients were determined using CIBERSORT. HTR2B expression was analyzed using validation datasets (GSE47460, GSE106986, and GSE1650). HTR2B expression in COPD cell models was determined via real-time quantitative PCR. Epithelial-mesenchymal transition (EMT) marker expression levels were determined after knocking down or overexpressing HTR2B. HTR2B function and mechanism in LUSC were analyzed with the Kaplan‒Meier plotter database. HTR2B expression was inhibited to detect changes in LUSC cell proliferation. A total of 1082 differentially expressed genes (DEGs) were identified in the GSE76925 dataset (371 genes were significantly upregulated, and 711 genes were significantly downregulated). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were mainly enriched in the p53 signaling and ß-alanine metabolism pathways. Gene Ontology enrichment analysis indicated that the DEGs were largely related to transcription initiation from the RNA polymerase I promoter and to the regulation of mononuclear cell proliferation. The LASSO regression model and random forest classifier results revealed that HTR2B, DPYS, FRY, and CD19 were key COPD genes. Immune cell infiltration analysis indicated that these genes were closely associated with immune cells. Analysis of the validation sets suggested that HTR2B was upregulated in COPD patients. HTR2B was significantly upregulated in COPD cell models, and its upregulation was associated with increased EMT marker expression. Compared with that in bronchial epithelial cells, HTR2B expression was upregulated in LUSC cells, and inhibiting HTR2B expression led to the inhibition of LUSC cell proliferation. In conclusions, HTR2B might be a new biomarker and therapeutic target in COPD patients with LUSC.

Pan-cancer analysis predict that FAT1 is a therapeutic target and immunotherapy biomarker for multiple cancer types including non-small cell lung cancer.

FAT1, a substantial transmembrane protein, plays a pivotal role in cellular adhesion and cell signaling. Numerous studies have documented frequent alterations in FAT1 across various cancer types, with its aberrant expression being linked to unfavorable survival rates and tumor progression. In the present investigation, we employed bioinformatic analyses, as well as in vitro and in vivo experiments to elucidate the functional significance of FAT1 in pan-cancer, with a primary focus on lung cancer. Our findings unveiled FAT1 overexpression in diverse cancer types, including lung cancer, concomitant with its association with an unfavorable prognosis. Furthermore, FAT1 is intricately involved in immune-related pathways and demonstrates a strong correlation with the expression of immune checkpoint genes. The suppression of FAT1 in lung cancer cells results in reduced cell proliferation, migration, and invasion. These collective findings suggest that FAT1 has potential utility both as a biomarker and as a therapeutic target for lung cancer.

Heterogeneity in PD-L1 expression between primary and metastatic lymph nodes: a predictor of EGFR-TKI therapy response in non-small cell lung cancer.

BACKGROUND: There is inconclusive evidence to suggest that the expression of programmed cell death ligand 1 (PD-L1) is a putative predictor of response to EGFR-TKI therapy in advanced EGFR-mutant non-small cell lung cancer (NSCLC). We evaluated the heterogeneity in PD-L1 expression in the primary lung site and metastatic lymph nodes to analyze the association between PD-L1 expression and response for patients treated with EGFR-TKI. METHODS: This study reviewed 184 advanced NSCLC patients with EGFR mutations who received first-generation EGFR-TKI as first-line treatment from 2020 to 2021 at Shanghai Chest Hospital. The patients were divided into the primary lung site group (n = 100) and the metastatic lymph nodes group (n = 84) according to the biopsy site. The patients in each group were divided into TPS < 1%, TPS 1-49%, and TPS ≥ 50% groups according to PD-L1 expression. RESULTS: The median PFS was 7 (95% CI: 5.7-8.3) months, and the median OS was 26 (95% CI: 23.5-28.5) months for all patients. No correlation existed between PFS or OS and PD-L1 expression. The median PFS in the primary lung site group was 11 months (95% CI: 9.6-12.4) in the TPS < 1% group, 8 months (95% CI: 6.6-9.4) in TPS 1-49% group, and 4 months (95% CI: 3.2-4.8) in TPS ≥ 50% group, with statistically significant differences (p = 0.000). The median OS of the TPS < 1% group and TPS ≥ 50% group showed a statistically significant difference (p = 0.008) in the primary lung site group. In contrast, PD-L1 expression in the lymph nodes of EGFR-mutant patients was unrelated to PFS or OS after EGFR-TKI therapy. CONCLUSION: PD-L1 expression from the primary lung site might predict clinical benefit from EGFR-TKI, whereas PD-L1 from metastatic lymph nodes did not. TRIAL REGISTRATION: This retrospective study was approved by the Ethics Committee of Shanghai Chest Hospital (ID: IS23060) and performed following the Helsinki Declaration of 1964 (revised 2008).

Evaluating the Clinical Characteristics and Prognosis of Advanced Non-Small Cell Lung Cancer with Exon 20 Insertions.

BACKGROUND: Epidermal growth factor receptor exon 20 insertion (EGFR ex20ins), an uncommon mutation in non-small cell lung cancer (NSCLC), can induce poor patient response to EGFR tyrosine kinase inhibitors (EGFR-TKI). However, the clinical features and prognosis of patients with EGFR ex20ins are not clearly understood. This study investigated the clinical characteristics and prognosis of advanced NSCLC patients with EGFR ex20ins. METHODS: Advanced NSCLC patients treated at Fujian Cancer Hospital were consecutively recruited from June 1, 2014 to December 20, 2021 and retrospectively examined. EGFR ex20ins was identified by polymerase chain reaction (PCR) or next-generation sequencing (NGS). The clinical characteristics, treatment methods, and patient outcomes were retrieved from the hospital database. The progression-free survival (PFS)  and overall survival (OS) were assessed by Kaplan-Meier analysis. RESULTS: Fourteen mutation subtypes of EGFR ex20ins were identified in the 24 enrolled patients, with EGFR ex20ins mutation more prevalent in non-smoking women. A763_Y764insFQEA and A767_V769dup (12.5% for both) were the most common mutation subtypes. Notably, no significant differences in PFS and OS were found between the first-line targeted therapy group [PFS: 257 days, 95% confidence interval (CI): 116-397 days; OS: not reached] and chemotherapy-based combination therapy group (PFS: 182 days, 95% CI: 156-207 days; OS: 998 days, 95% CI: 674-1321 days). TP53 mutation was the commonest concomitant mutation (62%), followed by EGFR amplification (25%). Chemotherapy combined with immunotherapy improved the prognosis of patients with high PD-L1 expression. CONCLUSION: For NSCLC patients with EGFR ex20ins, limited therapeutic benefits can be gleaned from either EGFR-TKIs or chemotherapy-based combination therapy.

EGFR-TKIs have limited efficacy in NSCLC patients with EGFR ex20ins. Combining chemotherapy with immunotherapy may represent a promising treatment approach for individuals with positive ex20ins and high PD-L1 expression.

The identification of hub genes associated with pure ground glass nodules using weighted gene co-expression network analysis.

BACKGROUND: Whether there are invasive components in pure ground glass nodules(pGGNs) in the lungs is still a huge challenge to forecast. The objective of our study is to investigate and identify the potential biomarker genes for pure ground glass nodule(pGGN) based on the method of bioinformatics analysis. METHODS: To investigate differentially expressed genes (DEGs), firstly the data obtained from the gene expression omnibus (GEO) database was used.Next Weighted gene co-expression network analysis (WGCNA) investigate the co-expression network of DEGs. The black key module was chosen as the key one in correlation with pGGN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were done. Then STRING was uesd to create a protein-protein interaction (PPI) network, and the chosen module genes were analyzed by Cytoscape software.In addition the polymerase chain reaction (PCR) was used to evaluate the value of these hub genes in pGGN patients' tumor tissues compared to controls. RESULTS: A total of 4475 DEGs were screened out from GSE193725, then 225 DEGs were identified in black key module, which were found to be enriched for various functions and pathways, such as extracellular exosome, vesicle, ribosome and so on. Among these DEGs, 6 overlapped hub genes with high degrees of stress method were selected. These hub genes include RPL4, RPL8, RPLP0, RPS16, RPS2 and CCT3.At last relative expression levels of CCT3 and RPL8 mRNA were both regulated in pGGN patients' tumor tissues compared to controls. CONCLUSIONS: To summarize, the determined DEGs, pathways, modules, and overlapped hub genes can throw light on the potential molecular mechanisms of pGGN.

Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression.

BACKGROUND: Due to the unfavorable prognosis associated with lung adenocarcinoma (LUAD), the development of targeted therapies and immunotherapies is essential. Cuproptosis, an emerging form of regulated cell death, is implicated in mitochondrial metabolism and is induced by copper ions. This study aimed to explore the prognostic value of cuproptosis- and immune-related genes (CIRGs) in LUAD. METHODS: We used The Cancer Genome Atlas database to develop a prognostic prediction model for LUAD patients based on eight CIRGs. Using Cox regression analysis, we determined that the CIRG signature is a reliable, independent prognostic factor. We further identified PSMD11 as a critical CIRG and performed immunohistochemistry to study the protein expression levels of PSMD11 in LUAD tissues. We also investigated the impact of PSMD11 on the biological behavior of lung cancer cell lines. RESULTS: We found that patients with low PSMD11 expression levels displayed an improved prognosis compared with those with high PSMD11 expression levels. Overexpression of PSMD11 enhanced proliferation, migration, invasion, and tumor growth of lung carcinoma cell line A549, while PSMD11 knockdown diminished proliferation, migration, invasion, and tumor growth of lung carcinoma cell line PC9. Additionally, we discovered that PSMD11 expression was positively correlated with the infiltration of myeloid-derived suppressor cells and the increased expression of immunosuppressive molecules. CONCLUSION: These findings suggest that PSMD11 may serve as a valuable prognostic biomarker and therapeutic target for LUAD.

Silencing of ZNF610 suppresses cell proliferation and migration in lung adenocarcinoma.

Zinc finger proteins (ZNFs) play a significant role in the initiation and progression of tumors. Nevertheless, the specific contribution of ZNF610 to lung adenocarcinoma (LUAD) remains poorly understood. This study sought is to elucidate the role of ZNF610 in LUAD. Transcript data of LUAD were obtained from The Cancer Genome Atlas Program (TCGA) database and processed via R program. The expression of ZNF610 was assessed in various cell lines. To compare the proliferative capacity of cells with or without ZNF610 silencing, CCK8, cell colony formation assay, and Celigo label-free cell counting assay were employed. Furthermore, transwell migration and invasion assays were conducted to evaluate the migratory and invasive abilities of the cells. The expression levels of genes and proteins were assessed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot techniques. In different LUAD cells, the expression level of ZNF610 was found to be significantly higher in LUAD cells compared to MRC-5 and BASE-2B cells. Moreover, the silencing of ZNF610 resulted in a decrease in cell proliferation and migration abilities. Additionally, the apoptosis rate of cells increased upon silencing ZNF610. Notably, the proportion of cells in the G0/G1 phase increased, while the proportion of cells in the S phase decreased following ZNF610 silencing. Finally, ß-catenin and snail were identified as downstream targets of ZNF610 in cells. Our findings suggest that silencing ZNF610 could inhibit LUAD cell proliferation and migration, possibly through the downregulation of ß-catenin and snail.

[Correlation between common driver gene variations and clinicopathological typing in lung adenocarcinoma].

Objective: To correlate the common driver gene variations in primary lung adenocarcinoma with their clinical characteristics and histopathological subtypes. Methods: There were 4 995 cases of primary lung adenocarcinoma diagnosed at Weifang People's Hospital of Shandong Province from January 2015 to December 2021 which were retrospectively analyzed. Among them 1 983 cases were evaluated for their histopathological subtype; 3 012 were analyzed for the correlation of their histopathological subtypes and corresponding driver gene variations, including invasive non-mucinous adenocarcinoma (INMA) and invasive mucinous adenocarcinoma (IMA), and morphologically, poorly-differentiated, moderately-differentiated and well-differentiated adenocarcinomas. Next-generation sequencing was used to detect variations in EGFR, KRAS, ALK, RET, ROS1, MET, HER2, or BRAF driver genes. Results: There were 2 384 males and 2 611 females. EGFR and ALK variations were more commonly found in female patients aged 60 years or older, with EGFR mutation rate in clinical stage Ⅰ (25.80%) significantly higher than in other stages (P<0.05). KRAS mutations were more commonly detected in male smokers aged 60 years or older, HER2 mutations were more commonly in patients younger than 60 years, and RET mutations were more commonly in non-smokers (all P<0.05). No correlation was found between ROS1, MET, and BRAF gene variations and their clinical characteristics (P>0.05). For the histopathological subtypes, among the 1 899 cases of acinar adenocarcinoma, EGFR mutation rate was the highest (67.30%) compared to the other genes. Exon 21 L858R and exon 19 del were the main mutation sites in IMA and INMA, with a higher mutation rate at exon 20 T790M (11.63%) in micropapillary adenocarcinoma. In IMA, KRAS had the highest overall mutation rate (43.80%), with statistically significant difference in mutation rates of exon 2 G12D and exon 2 G12V in acinar adenocarcinoma, solid, and IMA (P<0.05). KRAS mutation at various sites were higher in poorly differentiated groups compared to moderately- and well-differentiated groups (P<0.05). HER2 mutations were more commonly observed in acinar adenocarcinoma, papillary, and micropapillary adenocarcinoma of INMA. BRAF mutation was higher in micropapillary adenocarcinoma compared with other types (P<0.05). Conclusions: Variations in EGFR, ALK, KRAS, HER2, and RET in primary lung adenocarcinoma are associated with patients' age, smoking history, and clinical stage, and driver gene mutations vary among different histopathological subtypes. EGFR mutations are predominant in INMA, while KRAS mutations are predominant in IMA.

TET2-mutant undifferentiated pleomorphic sarcoma metastatic to lung and brain.

Sarcomas constitute approximately 1% of adult cancers and 8%-10% of paediatric cancers. Undifferentiated pleomorphic sarcoma (UPS) is a type of soft-tissue sarcoma (STS) characterised by dedifferentiated cancer cells. The most common sites of metastasis for UPS include the lungs, liver, bones and regional lymph nodes. Brain metastasis is rare, affecting only 1%-8% of STS patients. This report presents a unique case of a woman in her 80s with a TET2-mutant UPS metastatic to the lung and brain.

CDCA gene family promotes progression and prognosis in lung adenocarcinoma.

BACKGROUND: The cell division cycle-associated (CDCA) family participates in the cell cycle, and the dysregulation of its expression is associated with the development of several types of cancers. However, the roles of CDCAs in lung adenocarcinomas (LUAD) have not been investigated in systematic research. METHODS: Using data retrieved from The Cancer Genome Atlas (TCGA), the expression of CDCAs in LUAD and normal tissues was compared, and survival analysis was performed using the data. Also, the correlation between clinical characteristics and the expression of CDCAs was assessed. Using data from cBioPortal, we investigated genetic alterations in CDCAs and their prognostic implications. Immunohistochemical analyses were performed to validate our findings from TCGA data. Following this, we created a risk score model to develop a nomogram. We also performed gene set enrichment analyses (GSEA), gene ontology, and KEGG pathway analysis. We used Timer to analyze the correlation between immune cell infiltration, tumor purity, and expression data. RESULTS: Our results indicated that all CDCAs were expressed at high levels in LUAD; this could be associated with poor overall survival, as indicated in TCGA data. Univariate and multivariate Cox analyses revealed that CDCA4/5 could serve as independent risk factors. The results of immunohistochemical analyses confirmed our results. Based on the estimation of expression levels, clinical characteristics, alterations, and immune infiltration, the low-risk group of CDCA4/5 had a better prognosis than the high-risk group. Immune therapy is also a potential treatment option. CONCLUSION: In conclusion, our findings indicate that CDCAs play important roles in LUAD, and CDCA4/5 can serve as diagnostic and prognostic biomarkers and therapeutic targets in LUAD.

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling.

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

PURPL Promotes M2 Macrophage Polarization in Lung Cancer by Regulating RBM4/xCT Signaling.

Lung cancer is the most common malignancy worldwide. Long non-coding RNA (lncRNA) p53 upregulated regulator of P53 levels (PURPL) is abnormally in various cancers. However, the reports on its roles in lung cancer are limited. The purpose of present study is to investigate the potentials of lncRNA PURPL in lung cancer. PURPL and mRNA expression was determined using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). The location of PURPL was detected using RNA fluorescence in situ hybridization (FISH) assay. Protein expression was detected using western blot. Cellular functions were determined using flow cytometry. The interaction between PURPL and RNA-binding motif 4 (RBM4) was confirmed using RNA immunoprecipitation (RIP) assay. PURPL was overexpressed in lung cancer cells and patients. Overexpressed PURPL promoted M2 macrophage polarization and suppressed ferroptosis. Additionally, PURPL maintained the mRNA stability of cystine glutamate reverse transporter (xCT) via regulating RBM4. xCT knockdown antagonized the effects of overexpressed PURPL and inhibited M2 macrophage polarization via inducing macrophage ferroptosis. PURPL/RBM4/xCT axis promoted M2 macrophage polarization in lung cancer. Therefore, PURPL may be a potential target of lung cancer.