SPP1 inhibition improves the cisplatin chemo-sensitivity of cervical cancer cell lines

A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets

Traumatic brain injury (TBI) heterogeneity remains a critical barrier to translating therapies. Identifying final common pathways/molecular signatures that integrate this heterogeneity informs biomarker and therapeutic-target development. We present the first large-scale murine single-cell atlas of the transcriptomic response to TBI (334,376 cells) across clinically relevant models, sex, brain region, and time as a foundational step in molecularly deconstructing TBI heterogeneity. Results were unique to cell populations, injury models, sex, brain regions, and time, highlighting the importance of cell-level resolution. We identify cell-specific targets and previously unrecognized roles for microglial and ependymal subtypes. Ependymal-4 was a hub of neuroinflammatory signaling. A distinct microglial lineage shared features with disease-associated microglia at 24 h, with persistent gene-expression changes in microglia-4 even 6 months after contusional TBI, contrasting all other cell types that mostly returned to naive levels. Regional and sexual dimorphism were noted. CEREBRI, our searchable atlas (https://shiny.crc.pitt.edu/cerebri/), identifies previously unrecognized cell subtypes/molecular targets and is a leverageable platform for future efforts in TBI and other diseases with overlapping pathophysiology.

Identification of key pathways and mRNAs in interstitial cystitis/bladder pain syndrome treatment with quercetin through bioinformatics analysis of mRNA-sequence data

BACKGROUND

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic condition with painful bladder. At present, the pathogenesis of IC/BPS is still unknown. Quercetin (QCT) is a kind of natural flavonoid with wide sources and multiple biological activities. The purpose of this study was to explore the effects of QCT on mRNA expression and related regulatory signal pathways in IC model rats.

METHODS

LL-37 was used to induce the IC/BPS model rats. 20 mg/kg QCT was injected intraperitoneally into IC/BPS rats. ELISA, HE, Masson and TB staining were used to evaluate the level of inflammation and pathology. The concentration of QCT in rats was detected by HPLC. The mRNA sequencing was used to detect the differentially expressed (DE) mRNA in each group. The over-expression experiment of Lpl was carried out in IC/BPS model rats.

RESULTS

QCT treatment significantly decreased the level of MPO, IL-1β, IL-6 and TNF-α induced by LL-37 in rats, and alleviated bladder injury and mast cell degranulation. There were significant differences in mRNA sequencing data between groups, and the hub gene Lpl were screened by Cytohubba. The expression of Lpl was downregulated in IC/BPS rats. QCT intervention promoted Lpl expression. Overexpression of Lpl reduced the bladder injury induced by LL-37, increased GAG level and decreased the expression of MPO, IL-1β, IL-6 and TNF-α.

CONCLUSION

In this study, we provided the DE mRNA in IC/BPS rats treated with QCT, the signaling pathways for DE enrichment, screened out the hub genes, and revealed that Lpl overexpression alleviated IC/BPS model rats.

Single-cell RNA sequencing of cervical exfoliated cells reveals potential biomarkers and cellular pathogenesis in cervical carcinogenesis

Cervical cancer (CC) is a common gynecological malignancy. Despite the current screening methods have been proved effectively and significantly decreased CC morbidity and mortality, deficiencies still exist. Single-cell RNA sequencing (scRNA-seq) approach can identify the complex and rare cell populations at single-cell resolution. By scRNA-seq, the heterogeneity of tumor microenvironment across cervical carcinogenesis has been mapped and described. Whether these alterations could be detected and applied to CC screening is unclear. Herein, we performed scRNA-seq of 56,173 cervical exfoliated cells from 15 samples, including normal cervix, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL), and malignancy. The present study delineated the alteration of immune and epithelial cells derived during the cervical lesion progression. A subset of lipid-associated macrophage was identified as a tumor-promoting element and could serve as a biomarker for predicting the progression of LSIL into HSIL, which was then verified by immunofluorescence. Furthermore, cell-cell communication analysis indicated the SPP1-CD44 axis might exhibit a protumor interaction between epithelial cell and macrophage. In this study, we investigated the cervical multicellular ecosystem in cervical carcinogenesis and identified potential biomarkers for early detection.

Overexpression of SPP1 is a prognostic indicator of immune infiltration in lung adenocarcinoma

OBJECTIVE

The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD).

METHODS

In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated.

RESULTS

NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD.

CONCLUSIONS

SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

NUPR1 contributes to activate TFE3-dependent autophagy leading to cervical cancer proliferation

Cervical cancer is a malignant tumor that occurs in the cervix of women and endangers their lives. In this study, we aimed to assess the roles of NUPR1 and TFE3 in cervical cancer. The Cancer Genome Atlas (TCGA) database was used to assess the correlation between NUPR1 and TFE3 expression in cervical cancer. By silencing NUPR1 and TFE3, and through 3-MA treatment, we determined whether their silencing could lead to lysosomal dysfunction, thereby inhibiting autophagy and cervical cancer cell proliferation. Their roles were further analyzed using molecular biological methods. Silencing NUPR1 and TFE3 inhibited cell proliferation and decreased the expression levels of autophagy-related genes, p62 and LC3B. By tracing lysosomes within cells, NUPR1 and TFE3 knockdown were found to induce lysosomal dysfunction, thereby inhibiting autophagy. In vivo experimental studies have shown that knockdown of NUPR1 and TFE3 can inhibit tumor growth, while reducing the ki67, p62, and LC3B expression levels and promoting apoptosis. Furthermore, the expression levels of lamp1 and lamp2, and the phosphorylation of PI3K (p-PI3K) and Akt (p-Akt) were significantly reduced after NUPR1 and TFE3 knockdown. However, treatment with 3-MA and overexpression of TFE3 could partially reverse the effect of silencing NUPR1. Overall, silencing NUPR1 reduced autophagy by inhibiting TFE3 in cervical cancer. Our results supply new evidence for the use of NUPR1 as a therapeutic target in cervical cancer.

Relationship Between Expression of microRNA and Chemotherapy Resistance in Cervical Carcinoma

Cervical cancer (CC), although being a potentially avoidable disease, is the second most often diagnose gynecological cancer, with at minimum 530,000 new instant reported each year, and optimism for CC remains poor. Nearly half of individuals with locally advanced cervical cancer have a poor pathological response to standard therapy. As a result, research into the molecular pathogenesis of cervical cancer and associated therapeutic targets is a must. MicroRNAs (miRNAs) are possible biomarkers in cervical cancer; elevations or reductions in many distinct miRNAs discovered in individuals with this illness indicate that miRNA could contain a function to play in the illness's pathogenesis. Nevertheless, little is known about their significance in detecting individuals who do not respond to traditional therapy. As a consequence, the intention of this study is to look at the relationship among the synthesis of miRNAs (miR 217 and miR-140-3p), which can be utilized as molecular biomarkers to predict pathological responses in cervical cancer patients after radiation and chemotherapy. Various analytical techniques were used to analyze the data, including quantitative real-time PCR (qRT-PCR), growth and apoptosis analysis, western blot analysis, luciferase reporter gene analysis, immunohistochemistry, and statistical analysis. The results show that such miRNAs participate a crucial responsibility in CC cell proliferation inhibition. They might be a new therapeutic target for microRNA-mediated cell proliferation inhibition in cervical cancer.

Identification and verification of a 4-gene signature predicting the overall survival of cervical cancer

Cervical cancer (CC) is one of the most common gynecological malignancies, ranking fourth in both incidence and mortality in women worldwide. Early screening and treatment are of great significance in reducing the incidence and mortality of CC. Due to the complex molecular mechanisms of tumor progression, the predictive power of traditional clinical information is limited. In this study, an effective molecular model is established to assess prognosis of patients with CC and guide clinical treatment so as to improve their survival rate. Three high quality datasets (GSE138080, GSE52904, GSE67522) of expression profiling were obtained from gene expression omnibus (GEO) database. Another mRNA expression and clinicopathological data of CC were obtained from The Cancer Genome Atlas (TCGA) dataset. The bioinformatic analyses such as univariate analysis, multivariate Cox proportional-hazards model (Cox) analysis and lasso regression analysis were conducted to select survival-related differentially expressed genes (DEGs) and further establish a prognostic gene signature. Moreover, the performance of prognostic gene signature was evaluated based on Kaplan-Meier curve and receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA) and tumor immunity analysis were carried out to elucidate the molecular mechanisms and immune relevance. A 4-gene signature comprising procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 (PLOD2), spondin1 (SPON1), secreted phosphoprotein 1 (SPP1), ribonuclease H2 subunit A (RNASEH2A) was established to predict overall survival (OS) of CC. The ROC curve indicated good performance of the 4-gene signature in predicting OS of CC based on the TCGA dataset. The 4-gene signature classified the patients into high-risk and low-risk groups with distinct OS rates of CC. Univariate analysis and multivariate Cox regression analysis revealed that the 4-gene signature was an independent factor affecting the prognosis of patients with CC. Our study developed a 4-gene signature capable of predicting the OS of CC. The findings may be beneficial to individualized clinical treatment and timely follow-up for patients with CC.

SPP1 facilitates cell migration and invasion by targeting COL11A1 in lung adenocarcinoma

Background

Secreted phosphoprotein 1 (SPP1), an extracellular secreted glycol phosphoprotein, is closely related to tumor biologies, such as proliferation, migration, and invasion. However, the role and biological function of SPP1 in lung adenocarcinoma (LUAD) was still ambiguous.

Methods

SPP1 expression in LUAD tissues and its associations with clinical features and prognosis was investigated using meta-analysis, immunohistochemistry (IHC) staining methods, and quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the potential mechanism related to SPP1 was identified by using the Gene Set Enrichment Analysis (GSEA) method. A series of function assays were conducted to determine the biological role of SPP1 in LUAD cell migration and invasion in vitro and vivo. The co-expressed genes of SPP1 were obtained and verified by western blot assays. The influence of SPP1 on Collagen type XI alpha 1 (COL11A1) expression and epithelial-mesenchymal transition (EMT) markers was analyzed using western blot assays.

Results

The expression of SPP1 in LUAD tissues and cells was significantly higher than that in normal tissues and cells. And positively associations of SPP1 expression with TNM stage, lymph node metastasis, and invasion depth were observed. Patients with high SPP1 expression had unfavorable survival. The multivariable Cox regression analysis revealed that SPP1 expression was an independent prognostic factor of LUAD patients. Furthermore, downregulation of SPP1 could inhibit cell migration and invasion both in vitro and vivo, reduce the expression of epithelial marker (E-cadherin), and increase the expression of mesenchymal markers (N-cadherin and vimentin). Using bioinformatics and western blot assays, we confirmed that COL11A1 acted as the downstream of SPP1, and SPP1 knockdown could significantly downregulate the COL11A1 expression. Importantly, suppression of cell migration and invasion and the expression changes of EMT markers induced by SPP1 downregulation could be reversed by COL11A1 overexpression.

Conclusions

SPP1 facilitates cell migration and invasion by upregulating COL11A1 expression and that acts as a potential biomarker of metastasis and prognosis for LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02749-x.

Identification and Analysis of Immune-Related Gene Signature in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts.

METHODS

Differential analysis was employed to obtain the DEGs (Differentially Expressed Genes) of the TCGA-LIHC-TPM cohort. The lasso regression analysis was applied to build the prognosis model through using the TCGA cohort as the training group and the GSE14520 cohort as the testing group. Next, based on the prognosis model, we performed the following analyses: the survival analysis, the independent prognosis analysis, the clinical feature analysis, the mutation analysis, the immune cell infiltration analysis, the tumor microenvironment analysis, and the drug sensitivity analysis. Finally, the survival time of HCC patients was predicted by constructing nomograms.

RESULTS

Through the lasso regression analysis, we obtained a prognosis model of ten genes including BIRC5 (baculoviral IAP repeat containing 5), CDK4 (cyclin-dependent kinase 4), DCK (deoxycytidine kinase), HSPA4 (heat shock protein family A member 4), HSP90AA1 (heat shock protein 90 α family class A member 1), PSMD2 (Proteasome 26S Subunit Ubiquitin Receptor, Non-ATPase 2), IL1RN (interleukin 1 receptor antagonist), PGF (placental growth factor), SPP1 (secreted phosphoprotein 1), and STC2 (stanniocalcin 2). First, we found that the risk score is an independent prognosis factor and is related to the clinical features of HCC patients, covering AFP (α-fetoprotein) and stage. Second, we observed that the p53 mutation was the most obvious mutation between the high-risk and low-risk groups. Third, we also discovered that the risk score is related to some immune cells, covering B cells, T cells, dendritic, macrophages, neutrophils, etc. Fourth, the high-risk group possesses a lower TIDE score, a higher expression of immune checkpoints, and higher ESTIMATE score. Finally, nomograms include the clinical features and risk signatures, displaying the clinical utility of the signature in the survival prediction of HCC patients.

CONCLUSIONS

Through the comprehensive analysis, we constructed an immune-related prognosis model to predict the survival of HCC patients. In addition to predicting the survival time of HCC patients, this model significantly correlates with the tumor microenvironment. Furthermore, we concluded that these ten immune-related genes (BIRC5, CDK4, DCK, HSPA4, HSP90AA1, PSMD2, IL1RN, PGF, SPP1, and STC2) serve as novel targets for antitumor immunity. Therefore, this study plays a significant role in exploring the clinical application of immune-related genes.

Single Cell RNA-Seq Identifies Immune-Related Prognostic Model and Key Signature-SPP1 in Pancreatic Ductal Adenocarcinoma

There are no reliable biomarkers for early diagnosis or prognosis evaluation in pancreatic ductal adenocarcinoma (PDAC). Multiple scRNA-seq datasets for PDAC were retrieved from online databases and combined with scRNA-seq results from our previous study. The malignant ductal cells were identified through calculating copy number variation (CNV) scores. The robust markers of malignant ductal cells in PDAC were found. Five immune-related signatures, including SPP1, LINC00683, SNHG10, LINC00237, and CASC19, were used to develop a risk score formula to predict the overall survival of PDAC patients. We also constructed an easy-to-use nomogram, combining risk score, N stage, and margin status. The expression level of SPP1 was related to the prognosis and immune regulators. We found that SPP1 was mainly expressed in ductal cells and macrophages in PDAC. In conclusion, we constructed a promising prognostic model based on immune-related signatures for PDAC using scRNA-seq and TCGA_PAAD datasets.

The role of hypoxia-related genes in TACE-refractory hepatocellular carcinoma: Exploration of prognosis, immunological characteristics and drug resistance based on onco-multi-OMICS approach

Transcatheter arterial chemoembolization (TACE) is an effective treatment for hepatocellular carcinoma (HCC). During TACE, chemotherapeutic agents are locally infused into the tumor and simultaneously cause hypoxia in tumor cells. Importantly, the poor effect of TACE in some HCC patients has been shown to be related to dysregulated expression of hypoxia-related genes (HRGs). Therefore, we identified 33 HRGs associated with TACE (HRGTs) by differential analysis and characterized the mutational landscape of HRGTs. Among 586 HCC patients, two molecular subtypes reflecting survival status were identified by consistent clustering analysis based on 24 prognosis-associated HRGs. Comparing the transcriptomic difference of the above molecular subtypes, three molecular subtypes that could reflect changes in the immune microenvironment were then identified. Ultimately, four HRGTs (CTSO, MMP1, SPP1, TPX2) were identified based on machine learning approachs. Importantly, risk assessment can be performed for each patient by these genes. Based on the parameters of the risk model, we determined that high-risk patients have a more active immune microenvironment, indicating “hot tumor” status. And the Tumor Immune Dysfunction and Exclusion (TIDE), the Cancer Immunome Atlas (TCIA), and Genome of Drug Sensitivity in Cancer (GDSC) databases further demonstrated that high-risk patients have a positive response to immunotherapy and have lower IC50 values for drugs targeting cell cycle, PI3K/mTOR, WNT, and RTK related signaling pathways. Finally, single-cell level analysis revealed significant overexpression of CTSO, MMP1, SPP1, and TPX2 in malignant cell after PD-L1/CTLA-4 treatment. In conclusion, Onco-Multi-OMICS analysis showed that HRGs are potential biomarkers for patients with refractory TACE, and it provides a novel immunological perspective for developing personalized therapies.

Anti-Programmed Death Protein-1 (PD-1) Antibody Combined with Paclitaxel Exert Anti-Cancer Effect on Cervical Cancer Cells

The therapeutic effect of combined drugs on cervical cancer has been confirmed. Whether anti-PD-1 antibody combined with paclitaxel mediates the PI3K-Akt pathway to regulate cervical cancer still requires further research. 20 nude mice received subcutaneous administration of Hela cells to establish cervical cancer model which was then assigned into blank control group, control group A (PD-1 antibody (5 mg/ kg) administration), control group B (paclitaxel), and observation group (PD-1 antibody combined with paclitaxel) followed by analysis of cell proliferation, apoptosis, expression of PI3K-Akt signaling proteins and mRNAs. Observation group had lowest tumor size, highest cell proliferation inhibition rate and apoptosis, which were all reversed in blank group with a largest tumor size, lowest cell proliferation inhibition rate and cell apoptosis. There were no differences between control group A and control group B (P > 0.05). The expressions of PI3K, Akt, p53, and p21 proteins were lowest in observation group and highest in blank group. In addition, control group showed no difference to control group B (P > 0.05). In conclusion, anti-PD-1 antibody combined with paclitaxel inhibits PI3K-Akt signaling activity, thereby downregulating PI3K, Akt, p53, and p21 protein, controlling cervical cancer cell division, promoting cell apoptosis, and exerting anti-tumor effects.

Cancer chemotherapy: insights into cellular and tumor microenvironmental mechanisms of action

Chemotherapy has historically been the mainstay of cancer treatment, but our understanding of what drives a successful therapeutic response remains limited. The diverse response of cancer patients to chemotherapy has been attributed principally to differences in the proliferation rate of the tumor cells, but there is actually very little experimental data supporting this hypothesis. Instead, other mechanisms at the cellular level and the composition of the tumor microenvironment appear to drive chemotherapy sensitivity. In particular, the immune system is a critical determinant of chemotherapy response with the depletion or knock-out of key immune cell populations or immunological mediators completely abrogating the benefits of chemotherapy in pre-clinical models. In this perspective, we review the literature regarding the known mechanisms of action of cytotoxic chemotherapy agents and the determinants of response to chemotherapy from the level of individual cells to the composition of the tumor microenvironment. We then summarize current work toward the development of dynamic biomarkers for response and propose a model for a chemotherapy sensitive tumor microenvironment.

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

Overexpression of Secreted Phosphoprotein 1 (SPP1) predicts poor survival in HPV positive cervical cancer

Cervical cancer (CC) is the most prevalent malignant gynecological tumor with limited treatments. The present study describes the role of SPP1 in cancer progression, SPP1 emerged as one of the most overexpressed genes identified through clariom D transcriptome microarray. This investigation aims towards identifying a potential gene with significant prognostic value for detection and early diagnosis of cervical cancer. The elevated expression of SPP1 in cervical squamous cell carcinoma tissue was validated across GEO (Gene Expression Omnibus) microarray data sets, TCGA (The Cancer Genome Atlas), and Oncomine databases. SPP1 expression was found to be prognostically significant, showing association with poor survival rate of the patients. Our study intended to assess the expression of secreted phosphoprotein (SPP1) gene at mRNA and protein levels, and to explore the association of single nucleotide polymorphisms of SPP1 with risk of CC. Further, receiver operating characteristics (ROC) curve was plotted to determine the levels of SPP1 to differentiate CC against control. Results revealed significant (p < 0.01) stage-wise upregulation of SPP1 in CC compared to the normal cervical tissue and this was further confirmed using Immunohistochemistry and real-time PCR. The ROC for SPP1 demonstrated good selective power to differentiate malignant CC and non-malignant cervical tissues. The SPP1 gene -443 T > C promoter polymorphisms are found to be significantly predominant in the disease group and Insilico analysis by the TRANSFAC software confirms its association with loss of STAT6 transcription factor binding site leading to overexpression of the SPP1.

Biological and Clinicopathological Characteristics of OPN in Cervical Cancers

Background: Cervical cancer (CC) is the most common gynecological malignancy. Recently, an increasing number of studies have indicated that osteopontin (OPN) is a promising diagnostic and prognostic biomarker for CC. However, the biological role and detailed mechanism of OPN in CC remain unclear.

Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets and a clinical sample microarray were used in our study. To identify the clinicopathological characteristics of OPN in CC, we compared the expression of OPN between normal and CC tissue samples and analyzed the correlations between OPN expression and multiple clinicopathological features. To identify biological processes involving OPN, OPN-associated genes were screened with Pearson correlation analysis and applied in hallmark gene set enrichment analysis (GSEA). Additionally, leukocyte infiltration was evaluated based on OPN expression. Finally, OPN-related signaling pathways were identified by GSEA.

Results: OPN expression was higher in CC samples than in normal tissue samples and positively correlated with age, FIGO stage, tumor size, lymphovascular invasion and an unfavorable prognosis. OPN-associated genes were mainly enriched in the immune response, and increased OPN expression was accompanied by increased M2 macrophage infiltration. Additionally, OPN was correlated with hypoxia, high glycolytic metabolism, apoptosis, angiogenesis, epithelial-mesenchymal transition and multiple signaling pathways (the p53 pathway, the PI3K/Akt pathway, IL6/STAT3 signaling, mTORC1 signaling and KRAS signaling).

Conclusion: Our study showed that OPN is involved in immunological activities and multiple tumor processes, identifying it as a potential therapeutic target and useful prognostic factor in CC patients.

Metformin suppresses lung adenocarcinoma by downregulating long non-coding RNA (lncRNA) AFAP1-AS1 and secreted phosphoprotein 1 (SPP1) while upregulating miR-3163

AFAP1-AS1 plays a pro-tumor role in lung cancer. However, no investigation has focused on whether it is involved in the anticancer activity of metformin (Met) in the treatment of lung adenocarcinoma (LUAD). Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of long non-coding (lnc)RNA AFAP1-AS1, the microRNA (miR)-3163, and secreted phosphoprotein 1 (SPP1) in LUAD tissues, or of A549 and H3122 cells. Cell Counting Kit-8, wound scratch, and cell invasion assays were performed to evaluate the effect of the overexpression of lncRNA AFAP1-AS1, miR-3163, and SPP1 on the malignant behaviors of A549 and H3122 cells. Phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) signaling pathway-related proteins were detected by Western blot analysis. Dual luciferase reporter or RIP assays were used to determine the interplay between AFAP1-AS1 and miR-3163, or of miR-3163 and SPP1. Met inhibits the malignant characteristics of A549 and H3122 cells in vitro. GEPIA database analysis showed that AFAP1-AS1 is a highly expressed lncRNA in LUAD tissues, which was validated by RT-qPCR. Overexpression of AFAP1-AS1 suppressed the met-mediated anti-tumor activity in A549 and H3122 cells, while AFAP1-AS1 silencing promoted it. Met inhibited AFAP1-AS1 expression, which resulted in reduced proliferation, migration, and invasion in A549 and H3122 cells. This led to AFAP1-AS1-mediated suppression of miR-3163 and, subsequently, the upregulation of SPP1. Met exerts its antitumor activities by regulating the AFAP1-AS1/miR-3163/SPP1/PI3K/Akt/mTOR axis. Our findings deepen our understanding of mechanisms underlying anti-tumor effect of Met in LUAD.

LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

Identification of a novel six-gene signature with potential prognostic and therapeutic value in cervical cancer

Introduction

Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection.

Materials

Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature.

Results

We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer.

Conclusion

Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

Background

Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.

Methods

Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.

Results

Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.

Conclusions

We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08358-7.

SNX10 and PTGDS are associated with the progression and prognosis of cervical squamous cell carcinoma

Background

Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.

Methods

We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.

Results

Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P < 0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression while SNX10 presented high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency (AUC = 0.738). GSEA analysis demonstrated that the two genes were correlated with the chemokine signaling pathway (P < 0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p = 0.037). Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients (P = 0.007 and 0.003).

Conclusions

PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08212-w.

Upregulation of SPP1 Is a Marker for Poor Lung Cancer Prognosis and Contributes to Cancer Progression and Cisplatin Resistance

The chemoresistance of lung cancer is a significant contributor to its high mortality and morbidity rate. There is an urgent need to identify differentially expressed genes in lung cancer patients with a poor prognosis to develop effective means to overcome drug resistance in subsequent treatment. In this study, we identified the secreted phosphoprotein 1 (SPP1) as a potential gene associated with a poor diagnosis of lung cancer patients using the Cancer Genome Atlas analysis, which suggested that the expression of SPP1 in tumor tissues was significantly higher than normal tissues. The high expression of SPP1 was also correlated with tumor grade and poor clinical prognosis. To understand the roles of SPP1 and the DNA methyltransferase 1 (DNMT1), which regulated SPP1 expression, in affecting cell viability, migration and invasion, SPP1 and DNMT1 were overexpressed in the human lung cancer A549 and NCI-446 cells, followed by analyzing cell viability, migration and invasion. We showed that SPP1 promoted the proliferation, migration and invasion of lung cancer cells, and increased the resistance of lung cancer to the chemotherapeutic drug cisplatin. Knocking down SPP1 in cells restored sensitivity to cisplatin. Further, A549 cells without SPP1 overexpression demonstrated lower tumor growth rate than SPP1 overexpression cells using the xenograft tumor mouse model. High expression of SPP1 in lung cancer tumor tissue was caused by the reduced methylation level of its promoter region mediated by DNMT1. Our data suggested that SPP1 can be used as a marker for highly malignant lung cancer and targeting SPP1 may be a potential lung cancer treatment strategy.

Identification of VWF as a Novel Biomarker in Lung Adenocarcinoma by Comprehensive Analysis

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.

Identification of Differentially Expressed Genes in Cervical Cancer Patients by Comparative Transcriptome Analysis

Cervical cancer is one of the most malignant reproductive diseases seen in women worldwide. The identification of dysregulated genes in clinical samples of cervical cancer may pave the way for development of better prognostic markers and therapeutic targets. To identify the dysregulated genes (DEGs), we have retrospectively collected 10 biopsies, seven from cervical cancer patients and three from normal subjects who underwent a hysterectomy. Total RNA isolated from biopsies was subjected to microarray analysis using the human Clariom D Affymetrix platform. Based on the results of principal component analysis (PCA), only eight samples are qualified for further studies; GO and KEGG were used to identify the key genes and were compared with TCGA and GEO datasets. Identified genes were further validated by quantitative real-time PCR and receiver operating characteristic (ROC) curves, and the highest Youden index was calculated in order to evaluate cutoff points (COPs) that allowed distinguishing of tissue samples of cervical squamous carcinoma patients from those of healthy individuals. By comparative microarray analysis, a total of 108 genes common across the six patients' samples were chosen; among these, 78 genes were upregulated and 26 genes were downregulated. The key genes identified were SPP1, LYN, ARRB2, COL6A3, FOXM1, CCL21, TTK, and MELK. Based on their relative expression, the genes were ordered as follows: TTK > ARRB2 > SPP1 > FOXM1 > LYN > MELK > CCL21 > COL6A3; this generated data is in sync with the TCGA datasets, except for ARRB2. Protein-protein interaction network analysis revealed that TTK and MELK are closely associated with SMC4, AURKA, PLK4, and KIF18A. The candidate genes SPP1, FOXM1, LYN, COL6A3, CCL21, TTK and MELK at mRNA level, emerge as promising candidate markers for cervical cancer prognosis and also emerge as potential therapeutic drug targets.

The Role of microRNAs in the Cisplatin- and Radio-Resistance of Cervical Cancer

Cervical cancer is the fourth leading cause of cancer-related death among women worldwide. The chemotherapeutical agent cisplatin, a small platinum-based compound, is considered as the standard therapy for locally advanced cervical cancer or recurrent cancers, sometimes in combination with radiotherapy or other drugs. However, drug resistance and radio-resistance phenomena could reduce the life expectancy of cervical cancer patients. Resistance mechanisms are complex and often involve multiple cellular pathways in which microRNAs (miRNAs) play a fundamental role. miRNAs are a class of endogenous non-coding small RNAs responsible for post-transcriptional gene regulation. Convincing evidence demonstrates that several deregulated miRNAs are important regulators in the onset of drug and radioresistance in cervical cancer, thus underlying their potential applications in a clinical setting. In this review, we summarized the mechanisms by which miRNAs affect both cisplatin and radioresistance in cervical cancer. We also described the regulatory loops between miRNAs and lncRNAs promoting drug resistance. Besides, we reported evidence for the role of miRNAs in sensitizing cancer cells to cisplatin-based chemotherapy, and provided some suggestions for the development of new combined therapies for cervical cancer.

The inhibition of HeLa cells proliferation through SPARCL1 mediated by SPP1

Secreted protein acidic and rich in cysteines-like 1 (SPARCL1) is implicated in tumor progression and considered as a tumor suppressor. Aim of the study is to investigate the role of SPARCL1 in the regulation of tumor biology. SPARCL1 expression in human cervical cells was determined through western blot and RT-PCR. The effects of SPARCL1 overexpression on cell proliferation, migration and invasion were evaluated through CCK8 assay, colony formation assay, Wound healing assay and Transwell assay, respectively. The gain function of Secreted phosphor protein 1 (SPP1) was also evaluated in these cell functions. We observed that SPARCL1 expression at protein levels and transcription levels was lower in HeLa cells than that in Ect1/E6E7 cells. When SPARCL1 was overexpressed in HeLa cells, cell proliferation, migration and invasion were greatly repressed. Additionally, SPARCL1 overexpression markedly downregulated SPP1 expression at transcription levels. Mechanistical study revealed that SPP1 overexpression could greatly counteract the effects of SPARCL1 overexpression on the aforementioned cell processes and inhibit the phosphorylation of focal adhesion kinase (FAK) and extracellular regulated protein kinases (ERK). Our findings indicated that HeLa cells overexpressing SPARCL1 showed weaker abilities of proliferation, migration and invasion, and its effects could be neutralized by SPP1 overexpression possibly via FAK/ERK pathway. The relationship of SPARCL1 and SPP1 could help us to further understand the pathogenesis of cervical cancer and SPARCL1/SPP1 could be beneficial therapeutic targets in cervical cancer.

A Novel Four-Gene Prognostic Signature as a Risk Biomarker in Cervical Cancer

Background

Cervical cancer (CC) is a major malignancy affecting women worldwide, with limited treatment options for patients with advanced disease. The aim of this study was to identify novel prognostic biomarkers for CC.

Methods

RNA-Seq data from four Gene Expression Omnibus datasets (GSE5787, GSE6791, GSE26511, and GSE63514) were used to identify differentially expressed genes (DEGs) between CC and normal cervical tissues. Functional and enrichment analyses of the DEGs were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Oncomine database, Cytoscape software, and Kaplan-Meier survival analyses were used for in-depth screening of hub DEGs. The Cox regression was then used to develop a prognostic signature, which was in turn used to create a nomogram.

Results

A total of 207 DEGs were identified in the tissue samples, eight of which were prognostically significant in terms of overall survival (OS). Thereafter, a novel four-gene signature consisting of DSG2, MMP1, SPP1, and MCM2 was developed and validated using stepwise Cox analysis. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.785, 0.609, and 0.686 in the training, verification, and combination groups, respectively. The protein expression levels of the four genes were well validated by the western blotting. Moreover, the nomogram analysis showed that a combination of this four-gene signature plus lymph node metastasis (LNM) status effectively predicted the 1- and 3-year OS probabilities of CC patients with accuracies of 69.01% and 83.93%, respectively.

Conclusions

We developed a four-gene signature that can accurately predict the prognosis in terms of OS, of CC patients, and could be a valuable tool for designing treatment strategies.

Silencing of SPP1 Suppresses Progression of Tongue Cancer by Mediating the PI3K/Akt Signaling Pathway

Background:

In the present study, we aimed to find an effective target for the treatment of tongue cancer using gene chip screening and signal pathway research.

Methods:

We used microarray screening and gene expression profile analyses to find important differentially expressed genes in tongue cancer. We constructed a protein-protein interaction network, and used enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes to screen for important genes. We then silenced the genes of interest in SCC154 cells to study the relationship with the Phosphatidylinositol 3-kinase/Akt signal pathway. Western blot analyses, the 3-(4,5Dimethylthiazol-yl)-2,5Dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT) test, and immunofluorescence assays were used to compare the expression levels of Phosphatidylinositol 3-kinase/Akt signal pathway-related proteins, cell viability, and cell proliferation ability in normal SCC154 cells, Si-RNA SCC154 cells, and gene-silenced SCC154 cells. The scratch test, Transwell test, and western blotting were used to determine migration, invasion, and carcinogenesis.

Results:

Using GSE9844, GSE13601, and GSE31056 gene chips, we identified 93 upregulated genes and 76 downregulated genes in tongue cancer. Using the protein-protein interaction network and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we further identified 47 differentially expressed genes. Using Kaplan-Meier plotter online tools, we also identified 3 genes (SPP1, Recombinant Human Secreted Phosphoprotein 1; PLAU, plasminogen activator urinary; and APP, amyloid precursor protein). Compared with normal SCC154 cells and Si-RNA control SCC154 cells, the expressions of Phosphatidylinositol 3-kinase/Akt pathway proteins in si-SPP1 SCC154 cells were significantly decreased (*P < 0.05), and the protein activities and proliferation abilities were also significantly decreased (*P < 0.05), while the migration ability, invasion ability, and cancer forming ability were significantly increased (*P < 0.05).

Conclusion:

Inhibition of the SPP1 gene may have a therapeutic effect on tongue cancer, and could be an effective target for the treatment of this disorder.

Estimation of Hub Genes and Infiltrating Immune Cells in Non-Smoking Females with Lung Adenocarcinoma by Integrated Bioinformatic Analysis

BACKGROUND In recent years, the morbidity and mortality rates of lung adenocarcinoma in non-smoking females have been increasing dramatically. Although much research has been done with some progress, the molecular mechanism remains unclear. In this study we aimed to estimate hub genes and infiltrating immune cells in non-smoking females with lung adenocarcinoma. MATERIAL AND METHODS Firstly, we obtained differentially expressed genes (DEGs) by GEO2R analysis based on 3 independent mRNA microarray datasets of GSE10072, GSE31547, and GSE32863. The DAVID database was utilized for functional enrichment analysis of DEGs. Moreover, we identified hub genes with prognostic value by STRING, Cytoscape, and Kaplan Meier plotter. Subsequently, these genes were further analyzed by Gene Expression Profiling Interactive Analysis, Oncomine, Tumor Immune Estimation Resource, and Human Protein Atlas. Finally, the immune infiltration analysis was performed by CIBERSORT and The Cancer Genome Atlas with R packages. RESULTS We found 315 DEGs enriching in the extracellular matrix organization, cell adhesion, integrin binding, angiogenesis, and hypoxic response. And among these DEGs, we identified 10 hub genes (SPP1, ENG, ATF3, TOP2A, COL1A1, PAICS, CAV1, CAT, TGFBR2, and ANGPT1) of significant prognostic value. Simultaneously, we illustrated the distribution and differential expressions of 22 immune cell subtypes. and dendritic cells resting and macrophages M1 were identified with prognostic significance. CONCLUSIONS The results indicated that 10 hub genes and 2 immune cell subtypes might be promising biomarkers for lung adenocarcinoma in non-smoking females. This finding needs to be further evaluated.