Adenocarcinoma Cohort Research Articles

Early prediction of residual disease after neoadjuvant chemoradiotherapy and cetuximab for locally advanced esophageal cancer using 18F-FDG PET-CT imaging: a prospective cohort study

Previous studies in locally advanced esophageal cancer (LAEC) suggested that a change in the tumor's metabolic response, i.e., decrease of its interim 18F-FDG uptake compared with baseline, may predict histopathological response. We evaluated the possible predictive correlation between various PET-CT and histopathological parameters following a neoadjuvant biological-containing chemoradiotherapy (CRT) regimen. Patients with resectable LAEC received neoadjuvant cisplatin/5-fluorouracil-based CRT and cetuximab following one cycle of induction chemotherapy and cetuximab. Changes in maximum and mean standardized uptake values (ΔSUV-max and ΔSUV-mean, respectively) and metabolic tumor volume (ΔMTV), measured by PET-CT at baseline and 2 weeks after the onset of treatment, were compared with histopathological findings at surgery. Histopathological response was defined by tumor regression grade (TRG), pathological complete response (pCR) and microscopic or macroscopic residual disease (RD). Of 18 patients, 13 (72%) with adenocarcinoma (AC) and 5 (28%) with squamous cell carcinoma (SCC), were included. None of the changes in the parameters of PET was associated with pCR; only ΔSUV-mean was associated with TRG in the AC cohort. In contrast, both ΔSUV-mean% and ΔSUV-max% were significantly associated with RD, both in the whole cohort and in the AC cohort. Changes in FDG-uptake predicted RD2 at surgery: only patients with less than 13% decrease in SUV-mean% or less than 29% decrease in SUV-max% had RD2, while all patients with RD0 or RD1 had greater reductions [100% specificity and 100% positive predictive value (PPV)]. Changes in ΔSUV-max and ΔSUV-mean after two weeks of onset of cetuximab-based neoadjuvant chemotherapy for LAEC may predict macroscopic RD but not TRG or pCR at surgery.

Assessment of PD-L1 mRNA expression in gastrointestinal tumors and the response to immunotherapy.

Programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) has been proposed as a predictive biomarker to predict response to immunotherapy. Given the limitations of IHC test in PD-L1 detection, this study aimed to investigate the technical feasibility of using quantitative RT-PCR (qRT-PCR) to replace IHC in PD-L1 detection in gastrointestinal tumors. The Cancer Genome Atlas database was used to evaluate the relationship between PD-L1 expression in tumor tissue and the patient prognosis. In addition, 52 patients with gastrointestinal cancer were enrolled and divided into the stomach (STAD), colon (COAD), and rectum (READ) adenocarcinoma cohorts. IHC test was used to determine the PD-L1 level of the tissue specimens, and the qRT-PCR test was used to analyze the mRNA expression in both blood and tissue specimens. Moreover, the correlation between blood PD-L1 mRNA expression and immunotherapy efficacy was investigated in additional 15 patients with gastric cancer that further enrolled. The expression level of PD-L1 in tumor tissue is related to the tumor stage of COAD (p-value = 0.001) and primary therapy outcomes in patients with READ (p-value = 0.003) but not significantly correlated to the overall survival (OS) time of patients with gastrointestinal cancer. Moreover, the concordance of PD-L1 mRNA expression level of tissue and paired blood samples is low, despite a weak linear relationship that was found in the STAD cohort (r = 0.43, p-value = 0.049). We further demonstrated that qRT-PCR results in both tissue and blood specimens were numerically but not statistically significant consistent with IHC results (corresponding to a p-value of 0.84 and 0.55, respectively). Remarkably, high PD-L1 expression in blood of patients with STAD shows a better response to immunotherapy (p-value = 0.04), which could be well identified at the relative expression cutoff of 1.5 (sensitivity of 85.7%, specificity of 75.0%, and AUC of 0.82). Our study established a novel strategy for rapidly distinguishing patients with gastrointestinal cancer with the response to immunotherapy and has potential clinical benefits.

Landscape and clinical impact of metabolic alterations in non-squamous non-small cell lung cancer

Metabolomics studies to date have described widespread metabolic reprogramming events during the development of non-squamous non-small cell lung cancer (NSCLC). Extending far beyond the Warburg effect, not only is carbohydrate metabolism affected, but also metabolism of amino acids, cofactors, lipids, and nucleotides. We evaluated the clinical impact of metabolic reprogramming. We performed comparative analysis of publicly available data on non-squamous NSCLC, to identify concensus altered metabolic pathways. We investigated whether alterations of metabolic genes controlling those consensus metabolic pathways impacted clinical outcome. Using the clinically annotated lung adenocarcinoma (LUAD) cohort from The Cancer Genome Atlas, we surveyed the distribution and frequency of function-altering mutations in metabolic genes and their impact on overall survival (OS). We identified 42 metabolic genes of clinical significance, the majority of which (37 of 42) clustered across three metabolic superpathways (carbohydrates, amino acids, and nucleotides) and most functions (40 of 42) were associated with shorter OS. Multivariate analyses showed that dysfunction of carbohydrate metabolism had the most profound impact on OS [hazard ratio (HR) =5.208; 95% confidence interval (CI): 3.272 to 8.291], false discovery rate (FDR)-P≤0.0001, followed by amino acid metabolism (HR =3.346; 95% CI: 2.129 to 5.258), FDR-P≤0.0001 and nucleotide metabolism (HR =2.578; 95% CI: 1.598 to 4.159), FDR-P=0.0001. The deleterious effect of metabolic reprogramming on non-squamous NSCLC was observed independently of disease stage and across treatments groups. By providing a detailed landscape of metabolic alterations in non-squamous NSCLC, our findings offer new insights in the biology of the disease and metabolic adaptation mechanisms of clinical significance.

Identification of key biomarkers for STAD using filter feature selection approaches

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer death worldwide. Discovery of diagnostic biomarkers prompts the early detection of GC. In this study, we used limma method combined with joint mutual information (JMI), a machine learning algorithm, to identify a signature of 11 genes that performed well in distinguishing tumor and normal samples in a stomach adenocarcinoma cohort. Other two GC datasets were used to validate the classifying performances. Several of the candidate genes were correlated with GC tumor progression and survival. Overall, we highlight the application of feature selection approaches in the analysis of high-dimensional biological data, which will improve study accuracies and reduce workloads for the researchers when identifying potential tumor biomarkers.

High levels of AXL expression in untreated EGFR-mutated non-small cell lung cancer negatively impacts the use of osimertinib.

For non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations, the initial therapeutic interventions will have crucial impacts on their clinical outcomes. Drug tolerant factors reportedly have an impact on EGFR-tyrosine kinase inhibitor sensitivity. This prospective study investigated the impacts of drug tolerant-related protein expression in tumors based on the efficacy of osimertinib in the first-setting of EGFR-mutated advanced NSCLC patients. A total of 92 patients with EGFR-mutated advanced or postoperative recurrent NSCLC were analyzed and treated with osimertinib at 14 institutions in Japan. AXL, p53, and programmed death-ligand 1 (PD-L1) expression in patient tumors was determined using immunohistochemistry. The AXL signaling pathway was investigated using a cell line-based assay and AXL-related gene expression in The Cancer Genome Atlas (TCGA) database. High levels of AXL and positive-p53 expression were detected in 26.1% and 53.3% of the pretreatment EGFR-mutated NSCLC tumors, respectively. High AXL expression levels were significantly associated with a shorter progression-free survival compared with low AXL expression levels, irrespective of the EGFR activating mutation status (p= 0.026). Cell line-based assays indicated that the overexpression of AXL protein accelerated PD-L1 expression, which induced insensitivity to osimertinib. In the TCGA database, AXL RNA levels were positively correlated with PD-L1 expression in the lung adenocarcinoma cohort. The results show that high AXL expression levels in tumors impact clinical predictions when using osimertinib to treat EGFR-mutated NSCLC patients. Trial Registration: UMIN000043942.

Transcriptomic characterization and construction of M2 macrophage-related prognostic and immunotherapeutic signature in ovarian metastasis of gastric cancer.

Ovarian metastasis (OM) poses a major threat to the outcome of gastric cancer (GC) patients. Recently, immunotherapy emerged as a novel promising therapeutic strategy to treat late-stage GC, whereas its efficacy is influenced by tumor immune microenvironment (TIME). M2 macrophage, a key subset within TIME, plays dual immunosuppressive and pro-tumorigenic roles in cancer progression and is recognized as a potential therapeutic target. However, molecular mechanisms underlying OM remain elusive and the TIME-related prognostic and immunotherapeutic index for these patients is yet to establish. Differential expressed genes (DEGs) between paired normal mucosa, primary GC and OM of patients from Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 6) were identified by transcriptome sequencing, followed by the functional annotation of enriched hallmark pathways of DEGs between them. CIBERSORT was used to profile the relative expression level of 22 immune cell subsets in normal tissues, primary and metastatic tumors, followed by weighted gene coexpression network analysis (WGCNA) uncovering immune cell-correlated gene sets. The intersected genes between DEGs and M2 macrophage-related genes were processed by least absolute shrinkage and selection operator (LASSO) regression analysis to construct a predictive signature, M2GO, which was further validated by training set and test set of The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD), GSE62254 and GSE84437 cohorts. GC patients were divided into M2GO-high and -low subgroup according to the optimal cutoff value of the M2GO score. Furthermore, the clinical, molecular and immune features between M2GO-high and -low subgroups were analyzed. Clinical cohorts of immunotherapy were used to validate the predictive value of M2GO in regard to immunotherapy effectiveness. Transcriptomic sequencing and follow-up analyses of triple-matched normal tissues, primary and ovarian metastatic tumors identified distinctive sets of DEGs and enriched immune-, cancer- and metastasis-related pathways between them. Of note, M2 macrophage, a major immunosuppressive and pro-tumorigenic component within TIME, was significantly up-regulated in OMs. WGCNA and LASSO regression were applied to establish a novel OM- and M2 macrophage-related predictive signature, M2GO, based on M2 macrophage-related prognostic genes including GJA1, MAGED1 and SERPINE1. M2GO served as an independent prognostic factor of GC patients. Comprehensive molecular and immune characterization of M2GO-based subgroups uncovered their distinctive features in terms of enriched functional pathways, tumor mutation burden, key immune checkpoints, major regulators of natural immune cGAS-STING pathway, infiltrated subsets of immune cells and tumor immune exclusion/dysfunction (TIDE) score. Notably, the M2GO score was significantly lower in responsive group than non-responsive group (P < 0.05) in clinical cohort of metastatic GC patients undergoing immunotherapy. Transcriptomic characterization of paired normal mucosae, primary and ovarian metastatic tumors revealed their unique molecular and immune features. Follow-up analyses established a novel OM- and M2 macrophage-related signature, M2GO, which served as a promising prognostic and immunotherapeutic biomarker to distinguish the clinical outcome, molecular and immune features of GC patients and predict their differential responses to immunotherapy.

Upregulated Solute Carrier SLC39A1 Promotes Gastric Cancer Proliferation and Indicates Unfavorable Prognosis.

Solute carrier 39A1 (SLC39A1) is an indirect zinc transporter which showed diverse tumor-related functions in different malignancies. Here, we aimed to investigate its expression and role in gastric adenocarcinoma. A retrospective gastric adenocarcinoma cohort (n = 154) was collected from our hospital to test their tissue expression of SLC39A1 through immunohistochemical staining method. After SLC39A1 overexpression or knockdown, proliferation and invasion assays were conducted for proliferation and invasion estimation, respectively. Xenograft in nude mice was used as the in vivo strategy to validate in vitro findings. Compared with adjacent stomach tissues, gastric adenocarcinoma tissues showed significantly higher SLC39A1 on both mRNA and protein levels. Higher SLC39A1 was observed in patients with larger tumor size (P=0.003) and advanced tumor stages (P < 0.001). Univariate (P=0.001) and multivariate analyses (P=0.035) confirmed the independent prognostic significance of SLC39A1 on gastric adenocarcinoma outcomes. The median survival time was 22.0 months in patients with high-SLC39A1 expression, while up to 57.0 months in those with low-SLC39A1 (P=0.001). In vitro and in vivo assays demonstrated that overexpressing SLC39A1 could promote gastric cancer growth and invasion, while silencing SLC39A1 led to opposite effects. Aberrant high-SLC39A1 expression can serve as an independent unfavorable prognostic factor for gastric adenocarcinoma. High SLC39A1 is critical for a more aggressive tumor phenotype by promoting cell proliferation and invasion. Therefore, targeting SLC39A1 may provide novel therapeutic insights.

Significance of thyroid transcription factor 1 and Napsin A for prompting the status of EGFR mutations in lung adenocarcinoma patients.

To evaluate the prompting value of thyroid transcription factor 1 (TTF-1) and Napsin A for the status of epidermal growth factor receptor (EGFR) mutations in an independent cohort of lung adenocarcinomas (LUADs) when genetic testing is unavailable. In this study, 976 untreated primary LUADs were retrospectively reviewed. The clinical and pathological data, including age, gender, smoking history, predictive values of TTF-1 and Napsin A, EGFR status, and tumor-node-metastasis (TNM) stage were obtained through medical records available in Shanxi Province Cancer Hospital. All patients were divided into 2 groups, a mutant group (n=362) and wild-type group (n=614), according to their EGFR status. The clinical data and the expression of TTF-1 and Napsin A were compared between the 2 groups. TTF-1 and Napsin A are detected by fully automated IHC.PCR was carried out to detect the EGFR mutation. Univariate and multivariate logistic regression analyses were undertaken to distinguish independent factors of EGFR mutations. A total of 362 cases (37.1%) of EGFR mutations were detected, which were more frequent in females, never smokers, lymphatic metastasis, distant metastasis, and the positive expression of TTF-1 and Napsin A. Multivariate analysis indicated that females [odds ratio (OR), 1.950; 95% confidence interval (CI): 1.2958 to 2.938; P=0.001], never smokers (OR, 2.040; 95% CI: 1.345 to 3.094; P=0.001), and the positive expression of TTF-1 (OR, 2.366; 95% CI: 1.440 to 3.887; P=0.001) and Napsin A (OR, 2.295; 95% CI: 1.448 to 3.638; P<0.001) were effective prompting for EGFR mutations. The positive expression of TTF-1 and Napsin A had the prompting value for EGFR mutations in patients with LUAD, and the indicators could be combined with other clinical characteristics to enhance the prediction of the EGFR status in LUAD.

Human Papillomavirus Oncoproteins Confer Sensitivity to Cisplatin by Interfering with Epidermal Growth Factor Receptor Nuclear Trafficking Related to More Favorable Clinical Survival Outcomes in Non-Small Cell Lung Cancer.

High-risk human papillomavirus (HPV) infections and epidermal growth factor receptor (EGFR) expression have been reported to be associated with more favorable survival outcomes in lung adenocarcinoma patients. In this study, we utilized transfected HPV 16E5/16E6/16E7 H292 cells to investigate the mechanism of HPV oncoproteins interfering with EGFR nuclear trafficking related to a better response to cisplatin. Furthermore, we correlated HPV 16E6/18E6 expression and differentially localized EGFR expression with the clinical association and survival impact in lung adenocarcinoma patients. Our results found significantly higher phosphorylated nuclear EGFR expression upon epidermal growth factor stimulus and better responses to cisplatin in transfected HPV 16E5/16E6/16E7 NCI-H292 cells and xenograft animal models. Our data were compatible with clinical results of a high correlation of HPV 16E6/18E6 and EGFR expression in non-small cell lung cancer tissues and the synergistic effects of both with the best survival prognosis in a lung adenocarcinoma cohort, especially in patients with older age, no brain metastasis, smoking history, and wild-type EGFR status. Cumulatively, our study supports HPV 16E5/16E6/16E7 oncoproteins interfering with EGFR nuclear trafficking, resulting in increased sensitivity to cisplatin. HPV 16E6/18E6 and EGFR expression serve as good prognostic factors in lung adenocarcinoma patients.

A universal co-expression gene network and prognostic model for hepatic-biliary-pancreatic cancers identified by integrative analyses.

Hepatic, biliary and pancreatic cancers are a diverse set of malignancies with poor prognoses. It is possible that common molecular mechanisms are involved in the carcinogenesis of these cancers. Here, we identified LINC01537 and seven protein-coding genes by integrative analysis of transcriptomes of mRNAs, microRNAs and long non-coding RNAs from cholangiocarcinoma, hepatocellular carcinoma and pancreatic adenocarcinoma cohorts in TCGA. A predictive model constructed from seven biomarkers was established to successfully predict the survival rate of patients, which was then further verified in external cohorts. Additionally, patients with high-risk scores in our model were prone to epithelial-mesenchymal transition. Finally, activation of the biomarker PDE2A significantly attenuated migration and epithelial-mesenchymal transition in the HepG2 liver cancer cell line.

Prognostic Modeling of Lung Adenocarcinoma Based on Hypoxia and Ferroptosis-Related Genes.

Background It is well known that hypoxia and ferroptosis are intimately connected with tumor development. The purpose of this investigation was to identify whether they have a prognostic signature. To this end, genes related to hypoxia and ferroptosis scores were investigated using bioinformatics analysis to stratify the risk of lung adenocarcinoma. Methods Hypoxia and ferroptosis scores were estimated using The Cancer Genome Atlas (TCGA) database-derived cohort transcriptome profiles via the single sample gene set enrichment analysis (ssGSEA) algorithm. The candidate genes associated with hypoxia and ferroptosis scores were identified using weighted correlation network analysis (WGCNA) and differential expression analysis. The prognostic genes in this study were discovered using the Cox regression (CR) model in conjunction with the LASSO method, which was then utilized to create a prognostic signature. The efficacy, accuracy, and clinical value of the prognostic model were evaluated using an independent validation cohort, Receiver Operator Characteristic (ROC) curve, and nomogram. The analysis of function and immune cell infiltration was also carried out. Results Here, we appraised 152 candidate genes expressed not the same, which were related to hypoxia and ferroptosis for prognostic modeling in The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort, and these genes were further validated in the GSE31210 cohort. We found that the 14-gene-based prognostic model, utilizing MAPK4, TNS4, WFDC2, FSTL3, ITGA2, KLK11, PHLDB2, VGLL3, SNX30, KCNQ3, SMAD9, ANGPTL4, LAMA3, and STK32A, performed well in predicting the prognosis in lung adenocarcinoma. ROC and nomogram analyses showed that risk scores based on prognostic signatures provided desirable predictive accuracy and clinical utility. Moreover, gene set variance analysis showed differential enrichment of 33 hallmark gene sets between different risk groups. Additionally, our results indicated that a higher risk score will lead to more fibroblasts and activated CD4 T cells but fewer myeloid dendritic cells, endothelial cells, eosinophils, immature dendritic cells, and neutrophils. Conclusion Our research found a 14-gene signature and established a nomogram that accurately predicted the prognosis in patients with lung adenocarcinoma. Clinical decision-making and therapeutic customization may benefit from these results, which may serve as a valuable reference in the future.

Molecular characterization of adenocarcinomas arising in the urinary bladder following augmentation cystoplasty: a multi-institutional study

Development of malignancy is a rare complication following augmentation cystoplasty, and the majority of tumors observed in this setting are adenocarcinomas. Here, we sought to genetically profile these tumors by targeted DNA sequencing of a multi-institutional cohort of adenocarcinomas that developed in the urinary bladder following augmentation cystoplasty. Carcinomas arising in the urinary bladder of patients with history of augmentation cystoplasty were obtained from 4 major academic institutions, with cases diagnosed as urothelial carcinoma excluded from the study. The cases were analyzed using a DNA sequencing panel that includes 529 genes and genome-wide copy number assessment. The most frequently altered genes included TP53, KRAS, and MYC, and the vast majority of cases demonstrated mutational profiles consistent with gastrointestinal adenocarcinomas. One case demonstrated an EML4::ALK fusion together with an MSH3 frameshift mutation and hypermutated phenotype, characteristic of a rare but aggressive subtype of colorectal adenocarcinoma that may benefit from targeted ALK inhibition therapy. Importantly, six other tumors in the cohort also had potentially targetable molecular alterations, involving ATM (2 cases), BRCA1 (2 cases), EGFR (1 case), and ERBB2 (1 case). To our knowledge, this study represents the most comprehensive molecular characterization to date of adenocarcinomas arising in the urinary bladder following augmentation cystoplasty. Despite the unique environment of the augmented tissue, the resulting tumors demonstrate a spectrum of driver mutations similar to that of primary gastrointestinal adenocarcinomas. Importantly, molecular alterations potentially amenable to targeted therapy were identified in the majority of cases.

Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes.

In an evolving population, proliferation is dependent on fitness so that a numerically dominant population typically possesses the most well adapted phenotype. In contrast, the evolutionary “losers” typically disappear from the population so that their genetic record is lost. Historically, cancer research has focused on observed genetic mutations in the dominant tumor cell populations which presumably increase fitness. Negative selection, i.e., removal of deleterious mutations from a population, is not observable but can provide critical information regarding genes involved in essential cellular processes. Similar to immunoediting, “evolutionary triage” eliminates mutations in tumor cells that increase susceptibility to the host immune response while mutations that shield them from immune attack increase proliferation and are readily observable (e.g., B2M mutations). These dynamics permit an “inverse problem” analysis linking the fitness consequences of a mutation to its prevalence in a tumor cohort. This is evident in “driver mutations” but, equally important, can identify essential genes in which mutations are seen significantly less than expected by chance. Here we utilized this new approach to investigate evolutionary triage in immune-related genes from TCGA lung adenocarcinoma cohorts. Negative selection differs between the two cohorts and is observed in endoplasmic reticulum aminopeptidase genes, ERAP1 and ERAP2 genes, and DNAM-1/TIGIT ligands. Targeting genes or molecular pathways under positive or negative evolutionary selection may permit new treatment options and increase the efficacy of current immunotherapy.

Computed tomography-based radiomics quantification predicts epidermal growth factor receptor mutation status and efficacy of first-line targeted therapy in lung adenocarcinoma.

BackgroundBiomarkers that predict the efficacy of first-line tyrosine kinase inhibitors (TKIs) are pivotal in epidermal growth factor receptor (EGFR) mutant advanced lung adenocarcinoma. Imaging-based biomarkers have attracted much attention in anticancer therapy. This study aims to use the machine learning method to distinguish EGFR mutation status and further explores the predictive role of EGFR mutation-related radiomics features in response to first-line TKIs.MethodsWe retrospectively analyzed pretreatment CT images and clinical information from a cohort of lung adenocarcinomas. We entered the top-ranked features into a support vector machine (SVM) classifier to establish a radiomics signature that predicted EGFR mutation status. Furthermore, we identified the best response-related features based on EGFR mutant-related features in first-line TKI therapy patients. Then we test and validate the predictive effect of the best response-related features for progression-free survival (PFS).ResultsSix hundred ninety-two patients were enrolled in building radiomics signatures. The 13 top-ranked features were input into an SVM classifier to establish the radiomics signature of the training cohort (n = 514), and the predictive score of the radiomics signature was assessed on an independent validation group with 178 patients and obtained an area under the curve (AUC) of 74.13%, an F1 score of 68.29%, a specificity of 79.55%, an accuracy of 70.79%, and a sensitivity of 62.22%. More importantly, the skewness-Low (≤0.882) or 10th percentile-Low group (≤21.132) had a superior partial response (PR) rate than the skewness-High or 10th percentile-High group (p < 0.01). Higher skewness (hazard ratio (HR) = 1.722, p = 0.001) was also found to be significantly associated with worse PFS.ConclusionsThe radiomics signature can be used to predict EGFR mutation status. Skewness may contribute to the stratification of disease progression in lung cancer patients treated with first-line TKIs.

Translation of the 27-gene immuno-oncology test (IO score) to predict outcomes in immune checkpoint inhibitor treated metastatic urothelial cancer patients

BackgroundThe IO Score is a 27-gene immuno-oncology (IO) classifier that has previously predicted benefit to immune checkpoint inhibitor (ICI) therapy in triple negative breast cancer (TNBC) and non-small cell lung cancer (NSCLC). It generates both a continuous score and a binary result using a defined threshold that is conserved between breast and lung. Herein, we aimed to evaluate the IO Score’s binary threshold in ICI-naïve TCGA bladder cancer patients (TCGA-BLCA) and assess its clinical utility in metastatic urothelial cancer (mUC) using the IMvigor210 clinical trial treated with the ICI, atezolizumab.MethodsWe identified a list of tumor immune microenvironment (TIME) related genes expressed across the TCGA breast, lung squamous and lung adenocarcinoma cohorts (TCGA-BRCA, TCGA-LUSQ, and TCGA-LUAD, 939 genes total) and then examined the expression of these 939 genes in TCGA-BLCA, to identify patients as having high inflammatory gene expression. Using this as a test of classification, we assessed the previously established threshold of IO Score. We then evaluated the IO Score with this threshold in the IMvigor210 cohort for its association with overall survival (OS).ResultsIn TCGA-BLCA, IO Score positive patients had a strong concordance with high inflammatory gene expression (p < 0.0001). Given this concordance, we applied the IO Score to the ICI treated IMvigor210 patients. IO Score positive patients (40%) had a significant Cox proportional hazard ratio (HR) of 0.59 (95% CI 0.45–0.78 p < 0.001) for OS and improved median OS (15.6 versus 7.5 months) compared to IO Score negative patients. The IO Score remained significant in bivariate models combined with all other clinical factors and biomarkers, including PD-L1 protein expression and tumor mutational burden.ConclusionThe IMvigor210 results demonstrate the potential for the IO Score as a clinically useful biomarker in mUC. As this is the third tumor type assessed using the same algorithm and threshold, the IO Score may be a promising candidate as a tissue agnostic marker of ICI clinical benefit. The concordance between IO Score and inflammatory gene expression suggests that the classifier is capturing common features of the TIME across cancer types.

Comprehensive genomic profiling of Finnish lung adenocarcinoma cohort reveals high clinical actionability and SMARCA4 altered tumors with variable histology and poor prognosis

IntroductionLung adenocarcinoma is the most common type of lung cancer and typically carries a high number of mutations. However, the genetic background of the tumors varies according to patients’ ethnic background and smoking status. Little data is available on the mutational landscape and the frequency of actionable genomic alterations in lung adenocarcinoma in the Finnish population. Materials and methodsWe evaluated the gene alteration frequencies of 135 stage I–IV lung adenocarcinomas operated at Turku University Hospital between 2004 and 2017 with a large commercial comprehensive genomic profiling panel. Additionally, we correlated the alterations in selected genes with disease outcomes in 115 stage I–III patients with comprehensive follow-up data. The genomic alterations in a sub-cohort of 30 never-smokers were assessed separately. ResultsSeventy percent of patients in the overall cohort and 77% in the never-smoker sub-cohort harbored an alteration or a genomic signature targetable by FDA and/or EMA approved drug for non-small cell carcinoma, respectively. In multivariable analysis for disease-specific survival, any alteration in SMARCA4 (DSS; HR 3.911, 95%CI 1.561–9.795, P=0.004) exhibited independent prognostic significance along with stage, tumor mutation burden, and predominant histological subtypes. ConclusionsOver two thirds of our overall cohort, and especially never-smokers had an actionable genomic alteration or signature. SMARCA4 alterations, detected in 7.4% of the tumors, independently predicted a shortened overall and disease-specific survival regardless of the alteration type. Most SMARCA4 alterations in our cohort were missense mutations associated with differentiated predominant histological subtypes and immunohistochemical SMARCA4/BRG1 and TTF-1 positive status.

Molecular and pathological subtypes related to prostate cancer disparities and disease outcomes in African American and European American patients.

Prostate cancer (PCa) disproportionately affects African American (AA) men, yet present biomarkers do not address the observed racial disparity. The objective of this study was to identify biomarkers with potential benefits to AA PCa patients. Differentially expressed genes (DEG) analysis coupled with gene set enrichment analysis (GSEA) and leading-edge genes analysis showed that the keratin family of genes, including KRT8, KRT15, KRT19, KRT34, and KRT80, constituted the single most prominent family of genes enriched in AA compared to European American (EA) PCa cell lines. In PCa patients (TCGA and MSKCC patient cohorts), KRT8, KRT15, and KRT19 expression were relatively higher in AA than in EA patients. The differences in the expression of KRT15 and KRT19, but not KRT8, were enhanced by Gleason score and ERG fusion status; in low Gleason (Gleason ≤ 6 [TCGA cohort] and Gleason ≤ 7 [MSKCC cohort]), the expression of KRT15 and KRT19 was significantly (p ≤ 0.05) higher in AA than in EA patients. Survival analysis revealed that high expression of KRT15 and KRT19 was associated with increased risk of biochemical recurrence in low Gleason category patients in the TCGA patient cohort. Interestingly, KRT15 and KRT19 expression were also associated with an increased risk of death in the metastatic prostate adenocarcinoma cohort, suggesting the potential to predict the risks of disease recurrence and death in the low Gleason category and advanced disease conditions respectively. Gene set enrichment analysis revealed known oncogenic gene signatures, including KRAS and ERBB2, to be enriched in patients expressing high KRT15 and KRT19. Furthermore, high KRT15 and KRT19 were linked to the basal and LumA PCa subtypes, which are associated with poor postoperative androgen deprivation therapy (ADT) response compared to the LumB subtype. Taken together, the present study identifies genes with high expression in AA than in EA PCa. The identified genes are linked to oncogenic gene signatures, including KRAS and ERBB2, and to basal and LumA PCa subtypes that are associated with poor postoperative ADT response. This study, therefore, reveals biomarkers with the potential to address biomarker bias in PCa risk stratification and/or prognosis.

Relationship between ATOH1 and tumor microenvironment in colon adenocarcinoma patients with different microsatellite instability status

BackgroundColon adenocarcinoma (COAD) is one of the major varieties of malignant tumors threatening human health today. Immune checkpoint inhibitors (ICIs) have recently begun to emerge as an effective option for the treatment of COAD patients, but not all patients can benefit from ICI treatment. Previous studies have suggested that ICIs boast significant clinical effects on patients with microsatellite instability-high (MSI-H), while conversely patients with microsatellite-stable/microsatellite instability-low (MSS/MSI-L) have shown limited response.MethodsWe used ATAC-seq, RNA-seq, and mutation data from The Cancer Genome Atlas Colon adenocarcinoma (TCGA-COAD) cohort to perform multi-omics differential analysis on COAD samples with different MSI statuses, then further screened genes by additionally combining these results with survival analysis. We analyzed the effects of the screened genes on the tumor microenvironment and immunogenicity of COAD patients, and subsequently determined their influence on the efficacy of ICIs in COAD patients using a series of predictive indexes.ResultsTwelve genes were screened in the TCGA-COAD cohort, and after the combined survival analysis, we identified ATOH1 as having significant effects. ATOH1 is characterized by high chromatin accessibility, high expression, and high mutation in COAD patients in the MSI-H group. COAD patients with high ATOH1 expression are associated with a better prognosis, unique immune microenvironment, and higher efficacy in ICI treatment. Enrichment analysis showed that COAD patients with high ATOH1 expression displayed significant upregulation in their humoral immunity and other related pathways.ConclusionsWe speculate that ATOH1 may influence the efficacy of ICIs therapy in patients with COAD by affecting the immune microenvironment and immunogenicity of the tumor.

A potential EBV-related classifier is associated with the efficacy of immunotherapy in gastric cancer.

BackgroundGastric cancer (GC) is a global health problem. As a complicated heterogeneous disease, The Cancer Genome Atlas (TCGA) Research Network recognized four subtypes of GC, including Epstein-Barr virus (EBV)-positive GC (EBVaGC), which accounts for approximately 9% of all GC cases. The response to immunotherapy in GC is limited, and whether EBV status is a predictor of immunotherapy remains controversial.MethodsThe differential gene expression analysis was utilized to compare the gene expression between the EBV-positive group and the EBV-negative group in the TCGA-Stomach Adenocarcinoma (TCGA-STAD) cohort. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network analysis, and gene functional enrichment analysis were used to investigate the most pivotal hub genes and their roles. The “Estimation of Stromal and Immune cells in Malignant Tumours using Expression data” (ESTIMATE) and CIBERSORT algorithms were performed to infer the immune compositions of tissue samples. Furthermore, quantitative real-time polymerase chain reaction (RT-qPCR) and survival analysis were used to validate the expression and prognosis of these hub genes in Sun Yat-sen University Cancer Center (SYSUCC) cohort. A GC cohort that received anti-programmed cell death 1 (PD-1) therapy was used to analyze the predicted efficacy based on the expression of hub genes.ResultsThere is a total of 1,686 differentially expressed genes (DEGs) between the EBV-positive group and EBV-negative group, and WGCNA identified a yellow-colored module that was most related to EBV features. Functional enrichment analysis of 144 genes in this yellow module demonstrated that these genes primarily performed immune-related functions, and PPI network analysis through the CytoHubba plug-in identified 11 hub genes in the network. The RT-qPCR results in the SYSUCC cohort further validated that the hub genes were all increased in the EBV-positive group. Finally, we found that a potential classifier was associated with the efficacy of immunotherapy based on the expression of these 11 hub genes.ConclusionsOur study identified several hub genes associated with EBV status that are closely related to the immune microenvironmental features of EBVaGC and may be used as molecular markers for predicting the immune response in GC.

Abstract 510: Molecular subtypes related to prostate cancer disparities and disease outcome in African American and European American patients

Abstract Prostate cancer disproportionately affects African American (AAM) men, yet present biomarkers do not factor in prostate cancer racial disparity. The objective of this study was to identify biomarkers with potential benefits to AAM prostate cancer patients. Differentially expressed genes (DEG) analysis coupled with gene set enrichment analysis (GSEA) and leading-edge genes analysis showed that the keratin family of genes, including KRT8, KRT15, KRT19, KRT34, and KRT80, constituted the single most prominent family of genes enriched in AAM compared to European American (EAM) prostate cancer cell lines. In prostate cancer patients (TCGA and MSKCC patient cohorts), only KRT8, KRT15, and KRT19 expression were relatively higher in AAM than in EAM. The differences in the expression of KRT15 and KRT19, but not KRT8, were enhanced by Gleason score and ERG fusion status; in low Gleason (Gleason ≤ 6 [TCGA cohort] and Gleason ≤ 7 [MSKCC cohort]), the expression of KRT15 and KRT19 was significantly (p ≤ 0.05) higher in AAM than in EAM patients. Survival analysis revealed that high expression of KRT15 and KRT19 was associated with increased risk of biochemical recurrence in low Gleason category patients in the TCGA patient cohort. Interestingly, KRT15 and KRT19 expression was associated with an increased risk of death in the metastatic prostate adenocarcinoma (SU2C/PCF Dream Team, PNAS 2019) cohort, suggesting the potential to predict the risks of disease recurrence and death in the low Gleason category and advanced disease conditions respectively. Gene set enrichment analysis revealed known oncogenic gene signatures, including KRAS and ERBB2, to be enriched in patients expressing high KRT15 and KRT19. Furthermore, high KRT15 and KRT19 were linked to the basal and LumA prostate cancer subtypes associated with poor postoperative androgen deprivation therapy (ADT) response compared to the LumB subtype. Taken together, the present study identifies genes with high expression in AAM than in EAM prostate cancer. The identified genes are linked to oncogenic gene signatures, including KRAS and ERBB2, and to basal and LumA prostate cancer subtypes that are associated with poor postoperative ADT response. The study, therefore, reveals biomarkers with the potential to address biomarker bias in prostate cancer diagnosis and/or prognosis. Future studies would explore the diagnostic and/or prognostic potential of identified markers in prostate cancer tissue samples. Citation Format: Joakin Opeli Mori, Jason White, Balasubramanyam Karanam, Clayton Yates, Honghe Wang. Molecular subtypes related to prostate cancer disparities and disease outcome in African American and European American patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 510.