Correlation between tumor location and survival in stage I lung adenocarcinoma and squamous cell carcinoma: a SEER-based study.
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ABSTRACT:
SUBMITTER: Hu J
PROVIDER: S-EPMC8317522 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Non-small cell lung cancer (NSCLC) is a leading cause of cancer-associated mortality worldwide. Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are two primary histological subtypes of NSCLC, accounting for ~70% of lung cancer cases. Increasing evidence suggests that AC and SCC differ in the composition of genes and molecular characteristics. Previous research has focused on distinguishing AC from SCC or predicting the NSCLC patient survival rates using gene expression profiles, usually with the aid of a feature selection method. The present study conducted a pre-filtering to identify the genes that have significant expression values and a high connection with other genes in the gene network, and then used the radial coordinate visualization method to identify relevant genes. By applying the proposed procedure to NSCLC data, it was demonstrated that there is a clear segmentation between AC and SCC, however not between patients with a good prognosis and bad prognosis. The focus of discriminating AC and SCC differs from survival prediction and there are almost no overlaps between the two gene signatures. Overall, a supervised learning method is preferred and future studies aiming to identify prognostic gene signatures with an increased prediction efficiency are required.
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Project description:Purpose:KRAS mutations and tumor location have been associated with response to targeted therapy among patients with stage IV colorectal cancer (CRC) in various trials. This study performed the first population-based examination of associations between KRAS mutations, tumor location, and survival, and assessed factors associated with documented KRAS testing. Methods: Patients with stage IV adenocarcinoma of the colon/rectum diagnosed from 2010 to 2013 were extracted from SEER data. Analyses of patient characteristics, KRAS testing, and tumor location were conducted using logistic regression. Cox proportional hazards models assessed relationships between KRAS mutations, tumor location, and risk of all-cause death. Results: Of 22,542 patients, 30% received KRAS testing, and 44% of these had mutations. Those tested tended to be younger, married, and metropolitan area residents, and have private insurance or Medicare. Rates of KRAS testing also varied by registry (range, 20%-46%). Patients with right-sided colon cancer (vs left-sided) tended to be older, female, and black; have mucinous, KRAS-mutant tumors; and have a greater risk of death (hazard ratio [HR], 1.27; 95% CI, 1.22-1.32). KRAS mutations were not associated with greater risk of death in the overall population; however, they were associated with greater risk of death among patients with left-sided colon cancer (HR, 1.19; 95% CI, 1.05-1.33). Conclusions: This large population-based study showed that among patients initially diagnosed with stage IV CRC, right-sided colon cancer was associated with greater risk of death compared with left-sided cancer, and KRAS mutations were only associated with risk of death in left-sided colon cancer. An unexpected finding was that among patients with stage IV disease, right-sided cancer was more commonly seen in black patients versus whites. Future studies should further explore these associations and determine the role of biology versus treatment differences. In addition, use of KRAS testing is increasing, but there is wide geographic variation wherein disparities related to insurance coverage and rurality may warrant further study.
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Project description:OBJECTIVES:Anti-programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) immunotherapy has demonstrated success in the treatment of advanced NSCLC. Recently, PD-1/PD-L1 blockade also has demonstrated interesting results in small trials of neoadjuvant treatment in stage IB to IIIA NSCLC. In addition, several clinical trials using anti-PD-1/PD-L1 immunotherapy as an adjuvant or neoadjuvant treatment in patients with resectable stage NSCLC are ongoing. However, few analyses of anti-PD-1/PD-L1 immunotherapy-related biomarkers in early-stage squamous cell lung carcinoma (SqCLC) have been reported. In this study, we evaluated PD-L1 protein expression, tumor mutation burden, and expression of an immune gene signature in early-stage SqCLC, providing data for identifying the potential role for patients with anti-PD-1/PD-L1 treatment in early-stage SqCLC. METHODS:A total of 255 specimens from patients with early-stage SqCLC were identified within participating centers of the Strategic Partnering to Evaluate Cancer Signatures program. PD-L1 protein expression by immunohistochemistry was evaluated by using the Dako PD-L1 22C3 pharmDx kit on the Dako Link 48 auto-stainer (Dako, Carpinteria, CA). Tumor mutation burden (TMB) was calculated on the basis of data from targeted genome sequencing. The T-effector and interferon gamma (IFN-?) gene signature was determined from Affymetrix gene chip data (Affymetrix, Santa Clara, CA) from frozen specimens. RESULTS:The prevalence of PD-L1 expression was 9.8% at a tumor proportion score cutoff of at least 50%. PD-L1 mRNA and programmed cell death 1 ligand 2 mRNA positively correlated with PD-L1 protein expression on tumor cells (TCs) and tumor-infiltrating immune cells. PD-L1 protein expression on tumor-infiltrating immune cells was correlated with the T-effector and IFN-? gene signature (p < 0.001), but not with TMB. For TCs, all of these biomarkers were independent of each other and neither PD-L1 protein expression, TMB, or T-effector and IFN-? gene signatures were independently prognostic for patient outcomes. CONCLUSIONS:Evaluation of PD-L1 expression, TMB, and T-effector and IFN-? gene signatures in the cohort with early-stage SqCLC found them to be independent of each other, and none was associated with overall survival. Our results also support the hypothesis that PD-L1 expression is regulated by an intrinsic mechanism on TCs and an adaptive mechanism on immune cells.
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Project description:The appeal to enroll patients with primary breast and lung cancer in clinical trials is increasing, but survival of these two primary cancers remains to be elucidated. This study analyzed the prognosis of primary breast duct carcinoma with subsequent lung adenocarcinoma (BCLA) and primary breast duct carcinoma with prior lung adenocarcinoma (LABC). Cohorts of 3,515 patients with BCLA and 654 patients with LABC were identified from the Surveillance, Epidemiology, and End Results database. Patients were classified into simultaneous two primary cancer (sTPC), metachronous two primary cancer (mTPC1), or mTPC2 groups when the interval times between breast and lung cancer were within 6 months, between 7 and 60 months, or over 60 months, respectively. The propensity score matching program (PSM) was applied to determine the survival of BCLA/LABC relative to single breast/lung cancer. Cox proportional hazard regression model and competing risk modes were performed to identify confounders associated with all-cause and cancer-specific death, respectively. Survival of patients with LABC/BCLA relative to single breast/lung cancer was accessed via median survival time. The survival of patients with BCLA/LABC was generally poor compared with the survival of those with single breast cancer. The PSM-estimated HR in the sTPC group with BCLA and in the mTPC1 and mTPC2 groups with LABC were 0.75 (95% CI 0.62-0.90), 0.52 (95% CI 0.27-0.98), and 0.36 (95% CI 0.20-0.65), respectively, whereas the SHRs were 0.80 (95% CI 0.66-0.97), 0.68 (95% CI 0.34-1.34), and 0.46 (95% CI 0.27-0.80), respectively, compared with those in the single lung cancer group. By contrast, the survival rates of the remaining patients did not differ. The median survival times since secondary malignancy were 42, 23, and 20 months in the sTPC, mTPC1, and mTPC2 groups with BCLA, respectively, and 18, 60, and 180 months in those with LABC, respectively. For patients with BCLA, the adjusted Cox regression suggested incidences of all-cause deaths in mTPC1group were statically higher than those in sTPC group, whereas the incidences of all-cause and cancer-specific death in the mTPC1 and mTPC2 groups were statistically lower than those in the sTPC group. The prognosis of patients with breast cancer and subsequent lung cancer of over 18 months was not significantly different than that of single lung cancer, which supported the profound appeal to increase the involvement of these two primary cancers in potential beneficial clinical trials. For patients with lung cancer and prior breast cancer of within 6 months and subsequent breast cancer of over 18 months, prognosis was improved relative to single lung cancer. Therefore, additional attention is needed to eliminate the potential bias may when these patients are recruited in the clinical trials.
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Project description:BackgroundColorectal carcinoma evolves through a multitude of molecular events including somatic mutations, epigenetic alterations, and aberrant protein expression, influenced by host immune reactions. One way to interrogate the complex carcinogenic process and interactions between aberrant events is to model a biomarker correlation network. Such a network analysis integrates multidimensional tumor biomarker data to identify key molecular events and pathways that are central to an underlying biological process. Due to embryological, physiological, and microbial differences, proximal and distal colorectal cancers have distinct sets of molecular pathological signatures. Given these differences, we hypothesized that a biomarker correlation network might vary by tumor location.ResultsWe performed network analyses of 54 biomarkers, including major mutational events, microsatellite instability (MSI), epigenetic features, protein expression status, and immune reactions using data from 1380 colorectal cancer cases: 690 cases with proximal colon cancer and 690 cases with distal colorectal cancer matched by age and sex. Edges were defined by statistically significant correlations between biomarkers using Spearman correlation analyses. We found that the proximal colon cancer network formed a denser network (total number of edges, n = 173) than the distal colorectal cancer network (n = 95) (P < 0.0001 in permutation tests). The value of the average clustering coefficient was 0.50 in the proximal colon cancer network and 0.30 in the distal colorectal cancer network, indicating the greater clustering tendency of the proximal colon cancer network. In particular, MSI was a key hub, highly connected with other biomarkers in proximal colon cancer, but not in distal colorectal cancer. Among patients with non-MSI-high cancer, BRAF mutation status emerged as a distinct marker with higher connectivity in the network of proximal colon cancer, but not in distal colorectal cancer.ConclusionIn proximal colon cancer, tumor biomarkers tended to be correlated with each other, and MSI and BRAF mutation functioned as key molecular characteristics during the carcinogenesis. Our findings highlight the importance of considering multiple correlated pathways for therapeutic targets especially in proximal colon cancer.
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Project description:The discovery of Warburg effect opens a new era in anti-cancer therapy. Aerobic glycolysis is regarded as a hallmark of cancer cells and increasing literatures indicates that metabolic changes are critical for the maintenance and progression of cancer cells. Besides aerobic glycolysis, increased fatty acid synthesis is also required for the rapid growth of cancer cells, and is considered as one of the most typical metabolic symbols of cancer either. Thus, targeting fatty acid metabolism may provide a potential avenue for the diagnosis and therapeutic treatment of cancer. In this study, we have identified Sterol-CoA desaturase-1 (SCD1) which is the rate-limiting enzyme of unsaturated fatty acid synthesis, universally and highly expressed in lung adenocarcinoma and was required for the cell proliferation, migration and invasion. Both in vitro and in vivo studies demonstrated that high expression of SCD1 remarkably enhanced the ability of tumor formation and invasion, while knockdown of SCD1 significantly repressed tumorigenesis and induced cell apoptosis. Clinical association study suggested that high expression of SCD1 is more frequently observed in late stage patients and presents poor prognosis. Taken together, our results suggested that SCD1 is a potentially novel biomarker of lung adenocarcinoma, and targeting SCD1 may represent a new anti-cancer strategy.
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Project description:Non-small cell lung cancer (NSCLC), which consists mainly of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), are the leading cause of cancer deaths worldwide. In this study, we performed a comprehensive analysis of the tumor microenvironmental and genetic factors to identify prognostic biomarkers for NSCLC. We evaluated the immune and stromal scores of patients with LUAD and LUSC using data from The Cancer Genome Atlas database with the ESTIMATE algorithm. Based on these scores, the differentially expressed genes were obtained and immune-related prognostic genes were identified. Functional analysis and protein-protein interaction network further revealed the immune-related biological processes in which these genes participated. Additionally, 22 subsets of tumor-infiltrating immune cells (TIICs) in the tumor microenvironment were analyzed with the CIBERSORT algorithm. Finally, we validated these valuable genes using an independent cohort from the Gene Expression Omnibus database. The associations of the immune and stromal scores with patients' clinical characteristics and prognosis were positive in LUAD but negative in LUSC and the correlations of TIICs with clinical characteristics were clarified. Several differentially expressed genes were identified to be potential immune-related prognostic genes. This study comprehensively analyzed the tumor microenvironment and presented immune-related prognostic biomarkers for NSCLC.
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Project description:Long non-coding RNAs (lncRNAs) have been implicated in pathogenesis of various cancers, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). We used cBioPortal to analyze lncRNA alteration frequencies and their ability to predict overall survival (OS) using 504 LUSC and 522 LUAD samples from The Cancer Genome Atlas (TCGA) database. In LUSC, 624 lncRNAs had alteration rates > 1% and 64 > 10%. In LUAD 625 lncRNAs had alteration rates > 1% and 36 > 10%. Among those, 620 lncRNAs had alteration frequencies > 1% in both LUSC and LUAD, while 22 were LUSC-specific and 23 were LUAD-specific. Twenty lncRNAs had alteration frequencies > 10% in both LUSC and LUAD, while 44 were LUSC-specific and 16 were LUAD specific. Genome ontology and pathway analyses produced similar results for LUSC and LUAD. Two lncRNAs (IGF2BP2-AS1 and DGCR5) correlated with better OS in LUSC, and three (MIR31HG, CDKN2A-AS1 and LINC01600) predicted poor OS in LUAD. Chip-seq and luciferase reporter assays identified potential IGF2BP2-AS1, DGCR5 and LINC01600 promoters and enhancers. This study presented lncRNA landscapes and revealed differentially expressed, highly altered lncRNAs in LUSC and LUAD. LncRNAs that act as oncogenes and lncRNA-regulating transcription factors provide novel targets for anti-lung cancer therapeutics.
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Project description:Understanding the different genetic landscape between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is important for understanding the underlying molecular mechanism, which may facilitate the development of effective and precise treatments. Although previous studies have identified a number of differentially expressed genes (DEGs) responsible for lung cancer, it is unknown which of these genes are causal. The present study integrated DNA methylation, RNA sequencing, clinical characteristics and survival outcomes of patients with LUAD and LUSC from The Cancer Genome Atlas. DEGs were first identified using edgeR by comparing tumor and normal tissue, and differentially methylated probes (DMPs) were assessed using ChAMP. Candidate genes for further time-to-event instrumental variable analysis were selected as the intersecting genes between DEGs and the genes including DMP CpG sites within the transcription start site (TSS1500), with DMPs in TSS1500 region being the instrumental variables. Extensive sensitivity analyses were conducted to assess the robustness of the results. The present study identified 906 DEGs for LUAD, among which 538 also had DMPs in the TSS1500 region. In addition, 1,543 DEGs were identified for LUSC, among which 1,053 also had DMPs in the TSS1500 region. Time-to-event instrumental variable analysis detected eight potential causal genes for LUAD survival, including aryl hydrocarbon receptor nuclear translocator like 2, semaphorin 3G, serum deprivation-response protein, chloride intracellular channel protein 5, LIM zinc finger domain containing 2, epithelial membrane protein 2, carbonic anhydrase 7 and LOC116437. The results also identified that phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2 may be a potential causal gene for LUSC. Therefore, the results of the present study suggested that there was molecular heterogeneity between these two lung cancer subtypes. Such analysis framework can be extended to other cancer genomics research.
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Project description:Background: The lung cancer staging system is insufficient for a comprehensive evaluation of patient prognosis. We constructed a novel immunoscore model to predict patients with high risk and poor survival. Method: Immunoscore was developed based on z-score transformed enrichment score of 11 immune-related gene sets of 109 immune risk genes. The immunoscore model was trained in lung adenocarcinoma cohort from The Cancer Genome Atlas (TCGA-LUAD) (n = 400), and validated in other two independent cohorts from Gene Expression Omnibus (GEO), GSE31210 (n = 219) and GSE68465 (n = 356). Meta-set (n = 975) was formed by combining all training and testing sets. Result: High immunoscore conferred worse prognosis in all sets. It was an independent prognostic factors in multivariate Cox analysis in training, testing and meta-set [hazard ratio (HR) = 2.96 (2.24-3.9), P < 0.001 in training set; HR = 1.99 (1.21-3.26), P = 0.006 in testing set 1; HR = 1.48 (1.69-2.39), P = 0.005 in testing set 2; HR = 2.01 (1.69-2.39), P < 0.001 in meta-set]. Immunoscore-clinical prognostic signature (ICPS) was developed by integrating immunoscore and clinical characteristic, and had higher C-index than immunoscore or stage alone in all sets [0.72 (ICPS) vs. 0.7 (immunoscore) or 0.59 (stage) in training set; 0.75 vs. 0.72 or 0.7 in testing set 1; 0.65 vs. 0.61 or 0.62 in testing set 2; 0.7 vs. 0.66 or 0.64 in meta-set]. Genome analysis revealed that immunoscore was positively correlated with tumor mutation burden (R = 0.22, P < 0.001). Besides, high immunoscore was correlated with high proportion of carcinoma-associated fibroblasts (R = 0.32, P < 0.001) in tumor microenvironment but fewer CD8+ cells infiltration (R = -0.28, P < 0.001). Conclusion: The immunoscore and ICPS are potential biomarkers for evaluating patient survival. Further investigations are required to validate and improve their prediction accuracy.
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