BackgroundTo explore the possible carcinogenesis and help better diagnose and treat patients with synchronous multiple primary lung cancers (sMPLC), we systematically investigated the genetic and DNA methylation profiles of early-stage sMPLC and single primary lung cancer (SPLC) and explored the immune profiles in the tumor microenvironment.MethodsHundred and ninety-one patients with 191 nodules in the SPLC group and 132 patients with 295 nodules in the sMPLC group were enrolled. All the samples were subjected to wide panel-genomic sequencing. Genome-wide DNA methylation was assessed using the Infinium Human Methylation 850 K BeadChip. RNA-seq and CIBERSORT analyses were performed to identify the immune characteristics in these two groups.ResultsLesions from sMPLC patients had lower TMB levels than that from SPLC patients. sMPLC had a similar genetic mutational landscape with SPLC, despite some subgroup genetic discrepancies. Distinct DNA methylation patterns were identified between the two groups. The differentially methylated genes were related to immune response pathways. RNA-seq analyses revealed more immune-related DEGs in sMPLC. Accordingly, more immune-related biological processes and pathways were identified in sMPLC. Aberrant DNA methylation was associated with the abnormal expression of immune-related genes. CIBERSORT analysis revealed the infiltration of immune cells was different between the two groups.ConclusionOur study for the first time demonstrated genetic, epigenetic, and immune profile discrepancies between sMPLC and SPLC. Relative to the similar genetic mutational landscape, the DNA methylation patterns and related immune profiles were significantly different between sMPLC and SPLC, indicating their essential roles in the initiation and development of sMPLC.

Immune checkpoint genes (ICGs) play pivotal roles in tumor immune microenvironment (TIME), and thus, targeting them represents a promising strategy for cancer immunotherapy. However, the genetic landscape of ICGs in lung adenocarcinoma (LUAD) is still unknown. Herein, we comprehensively evaluated the ICG expression profiles of 1439 LUAD samples and linked ICG expression patterns with infiltration of immune cells, clinical features, and response to immune checkpoint blockade (ICB). The ICGscore was developed to quantify ICG expression patterns of individual patient by principal component analysis algorithms. Three distinct ICG expression patterns and three ICG-related genomic clusters were determined, which were implicated in different clinical outcomes, level of immune infiltrates, and biological process. LUAD patients were subdivided into high- and low-ICGscore subgroups. Patients with higher ICGscore were characterized by favorable survival outcomes, increased immune cell infiltration, and enhanced expression of ICGs. Further analysis revealed that lower ICGscore was associated with greater tumor mutation loads and higher mutation rates of TTN, KEAP1, and ZFHX4. High ICGscore has the potential to be a robust indicator in clinical benefit of immunotherapy. Taken together, unraveling the ICG expression patterns will advance our understanding of heterogeneity of TIME and guides more effective immunotherapeutic strategies in LUAD.

Abstract Background: There is extensive genetic and transcriptional heterogeneity in Gastric cancer (GC). Increasing evidence has demonstrated that cuproptosis could exert an important function in tumor progression. Long noncoding RNAs (lncRNAs)，which exert a pivotal function in the development of GC, especially involving in tumor-associated immune progression. Thus, it is indispensable to establish a cuproptosis-related lncRNAs (crlncRNAs)signature. Methods: Based on 19 genes associated with cuproptosis, to investigate whether lncRNA was markedly associated with cuproptosis, Pearson correlation analysis came in handy. To identify characteristics of copper death-related lncRNAs and build predictive models, univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were used to identify 6 key cuproptosis-related lncRNAs (crlncRNAs). To validate the predictive power of the signature, Cox regression on the univariate and multivariate data, Kaplan-Meier survival analysis, receiver operating characteristic curves (ROC), area under the curve (AUC) are used in the training, testing, and total sets. We further examined the functional enrichment, the status of immune cells, immune cell infiltrations, landscape of mutation status, Tumor Immune Dysfunction and Exclusion (TIDE) score, correlation and drugs sensitivity among the different risk groups. Results: 16 prognostically related crlncRNAs(PRcrlncRNAs) were filtered to make the prognostic signature, 6 key crlncRNAs were included. The risk score was the independent parameter in predicting OS (Overall survival) according to Cox regression on the univariate and multivariate data and it is acceptable in predicting prognosis concerning the accuracy of the model, which is confirmed by ROC analysis in GC patients. Differences in median OS and PFS (progression-free survival) between high- and low-risk groups were statistically significant. The TIDE score was higher in high-risk patients, which could predict less chemosensitivity with some drugs in the light of the TIDE analysis. Conclusions: Our study is innovative to develop and validate a novel STAD-associated crlncRNAs model that could effectively instruct the prognosis, as well as participating in the immune microenvironment in STAD, which would provide a new insight in the development of molecularly targeted therapies associated to cuproptosis.

Background: Plasma heat shock protein 90 alpha (Hsp90 alpha) has been suggested as a novel biomarker for the diagnosis and prognosis of cancer. Carcinoembryonic antigen (CEA) and carbohydrate antigen199 (CA199) are traditional tumor biomarkers for colorectal cancer (CRC). Previous studies have shown that Hsp90 alpha and the combination of Hsp90 alpha and CEA are optimal biomarkers for CRC at an early stage. However, research on the use of Hsp90 alpha alone or in combination with CEA and/or CA199 in diagnosing CRC development, particularly liver metastasis, is limited. This study sought to investigate the value of Hsp90 alpha alone or in combination with CEA/CA199 in diagnosing CRC liver metastasis.Methods: The clinical data of 472 CRC patients were retrospectively analyzed, which were confirmed by clinical manifestations and a histopathological examination associated with an imaging diagnosis. The levels of Hsp90 alpha, and CEA, and CA199 were assessed by enzyme-linked immunoassays and electrochemiluminescence immunoassays. Liver metastasis was diagnosed by imaging or pathology of the liver. Logistic regression models were used to analyze associations between Hsp90 alpha, CEA, and CA199, and liver metastasis in CRC. The areas under the curves (AUCs) were used to compare the utility of Hsp90 alpha, CEA, and CA199 in the diagnosis of CRC liver metastasis (CRLM). Additionally, we compared the diagnostic utility of the models, including the Hsp90 alpha plus 1 of the other serum markers, and a combination of the 3 serum makers. Results: The plasma levels of Hsp90 alpha, CEA, and CA199 were positively associated with a higher risk of CRLM [odds ratios (OR) ranging from 1.36-2.72]. The AUCs of CEA, CA199, and Hsp90 alpha for CRLM were 0.80, 0.69, and 0.55, respectively. The AUCs for the combination of Hsp90 alpha and CEA, combination of Hsp90 alpha and CA199, combinations of Hsp90 alpha, CEA, and CA199 were 0.75, 0.66, 0.76, respectively. The combination of Hsp90 alpha, CEA, and CA199 did not improve the diagnostic utility for liver metastasis in CRC. Conclusions: The level of Hsp90 alpha was elevated in CRC and was associated with CRLM. Thus, the Hsp90 alpha is a potential biomarker for CRLM. CEA has the largest diagnostic utility for CRLM. Adding Hsp90 alpha to CEA/CA199 did not improve their diagnostic utility for CRLM.