Titin Mutation Is Associated With Tumor Mutation Burden and Promotes Antitumor Immunity in Lung Squamous Cell Carcinoma

Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma

Macrophages played an important role in the progression and treatment of head and neck squamous cell carcinoma (HNSCC). We employed weighted gene co-expression network analysis (WGCNA) to identify macrophage-related genes (MRGs) and classify patients with HNSCC into two distinct subtypes. A macrophage-related risk signature (MRS) model, comprising nine genes: IGF2BP2, PPP1R14C, SLC7A5, KRT9, RAC2, NTN4, CTLA4, APOC1, and CYP27A1, was formulated by integrating 101 machine learning algorithm combinations. We observed lower overall survival (OS) in the high-risk group and the high-risk group showed elevated expression levels in most of the immune checkpoint and human leukocyte antigen (HLA) genes, suggesting a strong immune evasion capacity. Correspondingly, TIDE score positively correlated with risk score, implying that high-risk tumors may resist immunotherapy more effectively. At the single-cell level, we noted macrophages in the tumor microenvironment (TME) predominantly stalled in the G2/M phase, potentially hindering epithelial-mesenchymal transition and playing a crucial role in the inhibition of tumor progression. Finally, the proliferation and migration abilities of HNSCC cells significantly decreased after the expression of IGF2BP2 and SLC7A5 reduced. It also decreased migration ability of macrophages and facilitated their polarization towards the M1 direction. Our study constructed a novel MRS for HNSCC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy for HNSCC patients.

Identification of a novel apoptosis-related genes signature to improve gastric cancer prognosis prediction

Dysregulation of apoptosis occurs in different types of malignant tumors and is likely to influence the tumor evolution, as well as clinical prognosis. However, the limited number of studies investigating the predictive power of apoptosis-related genes (ARGs) in gastric cancer indicates a gap in the current research. 174 ARGs who differentially expressed were screened using public databases, including the Gene Expression Omnibus and the Molecular Signatures Database. Univariate and LASSO regression analyses were rigorous approaches to recognize the 12 optimal genes (CTHRC1, PDGFRL, VCAN, GJA1, LOX, UPP1, ANGPT2, CRIM1, HIF1A, APOD, RNase1, and ID1) that make up the prognostic risk model. Molecular mutations, related signaling pathways, and immune system characteristics in different subgroups defined by the risk model were analyzed using different R packages. Moreover, based on the database of Genomics of Drug Sensitivity in Cancer, chemotherapy sensitivity was predicted among the risk subgroups. As a result, there were differences in mutation profiles, signaling pathways, and infiltrated immune cells between patients in various risk groups. Moreover, the low-risk group displayed greater sensitivity to chemotherapy than the high-risk group. Risk model provided a better prognostic value than the T, N, and M stages, according to the receiver operating characteristic curve. Finally, in a nomogram, the risk model and clinical factors were combined to visualize the survival rates of patients with GC. In response to the differential expression of apoptosis-related genes, a novel model for predicting the prognosis of GC patients was developed. This model may be highly valuable for guiding doctors to deliver treatment plans tailored to the need of patients with GC.

cancercelllines.org-a novel resource for genomic variants in cancer cell lines

Cancer cell lines are an important component in biological and medical research, enabling studies of cellular mechanisms as well as the development and testing of pharmaceuticals. Genomic alterations in cancer cell lines are widely studied as models for oncogenetic events and are represented in a wide range of primary resources. We have created a comprehensive, curated knowledge resource-cancercelllines.org-with the aim to enable easy access to genomic profiling data in cancer cell lines, curated from a variety of resources and integrating both copy number and single nucleotide variants data. We have gathered over 5600 copy number profiles as well as single nucleotide variant annotations for 16 000 cell lines and provide these data with mappings to the GRCh38 reference genome. Both genomic variations and associated curated metadata can be queried through the GA4GH Beacon v2 Application Programming Interface (API) and a graphical user interface with extensive data retrieval enabled using GA4GH data schemas under a permissive licensing scheme. Database URL: https://cancercelllines.org.

Genetic Variants That Impact Alternative Polyadenylation in Cancer Represent Candidate Causal Risk Loci

Alternative polyadenylation (APA) is emerging as a major mechanism of posttranscriptional regulation. APA can impact the development and progression of cancer, suggesting that the genetic determinants of APA might play an important role in regulating cancer risk. Here, we depicted a pan-cancer atlas of human APA quantitative trait loci (apaQTL), containing approximately 0.7 million apaQTLs across 32 cancer types. Systematic multiomics analyses indicated that cancer apaQTLs could contribute to APA regulation by altering poly(A) motifs, RNA-binding proteins (RBP), and chromatin regulatory elements and were preferentially enriched in genome-wide association studies (GWAS)-identified cancer susceptibility loci. Moreover, apaQTL-related genes (aGene) were broadly related to cancer signaling pathways, high mutational burden, immune infiltration, and drug response, implicating their potential as therapeutic targets. Furthermore, apaQTLs were mapped in Chinese colorectal cancer tumor tissues and then screened for functional apaQTLs associated with colorectal cancer risk in 17,789 cases and 19,951 controls using GWAS-ChIP data, with independent validation in a large-scale population consisting of 6,024 cases and 10,022 controls. A multi-ancestry-associated apaQTL variant rs1020670 with a C>G change in DNM1L was identified, and the G allele contributed to an increased risk of colorectal cancer. Mechanistically, the risk variant promoted aberrant APA and facilitated higher usage of DNM1L proximal poly(A) sites mediated by the RBP CSTF2T, which led to higher expression of DNM1L with a short 3'UTR. This stabilized DNM1L to upregulate its expression, provoking colorectal cancer cell proliferation. Collectively, these findings generate a resource for understanding APA regulation and the genetic basis of human cancers, providing insights into cancer etiology.

SIGNIFICANCE

Cancer risk is mediated by alternative polyadenylation quantitative trait loci, including the rs1020670-G variant that promotes alternative polyadenylation of DNM1L and increases colorectal cancer risk.

The landscape of objective response rate of anti-PD-1/L1 monotherapy across 31 types of cancer: a system review and novel biomarker investigating

BACKGROUND

Immune checkpoint inhibitors (ICIs) have dramatically changed the landscape of cancer treatment. However, only a few patients respond to ICI treatment. Thus, uncovering clinically accessible ICI biomarkers would help identify which patients will respond well to ICI treatment. A comprehensive objective response rate (ORR) data of anti-PD-1/PD-L1 monotherapy in pan-cancer would offer the original data to explore the new biomarkers for ICIs.

METHODS

We systematically searched PubMed, Cochrane, and Embase for clinical trials on July 1, 2021, limited to the years 2017-2021, from which we obtained studies centering around anti-PD-1/PD-L1 monotherapy. Finally, 121 out of 3099 publications and 143 ORR data were included. All of the 31 tumor types/subtypes can be found in the TCGA database. The gene expression profiles and mutation data were downloaded from TCGA. A comprehensive genome-wide screening of ORR highly correlated mutations among 31 cancers was conducted by Pearson correlation analysis based on the TCGA database.

RESULTS

According to the ORR, we classified 31 types of cancer into high, medium, and low response types. Further analysis uncovered that "high response" cancers had more T cell infiltration, more neoantigens, and less M2 macrophage infiltration. A panel of 28 biomarkers reviewed from recent articles were investigated with ORR. We also found the TMB as a traditional biomarker had a high correlation coefficient with ORR in pan-cancer, however, the correlation between ITH and ORR was low across pan-cancer. Moreover, we primarily identified 1044 ORR highly correlated mutations through a comprehensive screening of TCGA data, among which USH2A, ZFHX4 and PLCO mutations were found to be highly correlated to strengthened tumor immunogenicity and inflamed antitumor immunity, as well as improved outcomes for ICIs treatment among multiple immunotherapy cohorts.

CONCLUSION

Our study provides comprehensive data on ORR of anti-PD-1/PD-L1 monotherapy across 31 tumor types/subtypes and an essential reference of ORR to explore new biomarkers. We also screened out a list of 1044 immune response related genes and we showed that USH2A, ZFHX4 and PLCO mutations may act as good biomarkers for predicting patient response to anti-PD-1/PD-L1 ICIs.

Whole exome sequencing analysis of canine urothelial carcinomas without BRAF V595E mutation: Short in-frame deletions in BRAF and MAP2K1 suggest alternative mechanisms for MAPK pathway disruption

Molecular profiling studies have shown that 85% of canine urothelial carcinomas (UC) harbor an activating BRAF V595E mutation, which is orthologous to the V600E variant found in several human cancer subtypes. In dogs, this mutation provides both a powerful diagnostic marker and a potential therapeutic target; however, due to their relative infrequency, the remaining 15% of cases remain understudied at the molecular level. We performed whole exome sequencing analysis of 28 canine urine sediments exhibiting the characteristic DNA copy number signatures of canine UC, in which the BRAF V595E mutation was undetected (UDV595E specimens). Among these we identified 13 specimens (46%) harboring short in-frame deletions within either BRAF exon 12 (7/28 cases) or MAP2K1 exons 2 or 3 (6/28 cases). Orthologous variants occur in several human cancer subtypes and confer structural changes to the protein product that are predictive of response to different classes of small molecule MAPK pathway inhibitors. DNA damage response and repair genes, and chromatin modifiers were also recurrently mutated in UDV595E specimens, as were genes that are positive predictors of immunotherapy response in human cancers. Our findings suggest that short in-frame deletions within BRAF exon 12 and MAP2K1 exons 2 and 3 in UDV595E cases are alternative MAPK-pathway activating events that may have significant therapeutic implications for selecting first-line treatment for canine UC. We developed a simple, cost-effective capillary electrophoresis genotyping assay for detection of these deletions in parallel with the BRAF V595E mutation. The identification of these deletion events in dogs offers a compelling cross-species platform in which to study the relationship between somatic alteration, protein conformation, and therapeutic sensitivity.

The Driverless Triple-Wild-Type (BRAF, RAS, KIT) Cutaneous Melanoma: Whole Genome Sequencing Discoveries

The genetic makeup of the triple-wild-type melanoma (BRAF, NRAS and NF1) has been known for some time, but those studies grouped together rare histopathological versions with common ones, as well as mucosal and even uveal ones. Here we used whole genome sequencing to genetically characterize the triple-wild-type melanoma (TWM), termed here as BRAF, RAS and KIT wild type (the most frequent oncogenic drivers of skin melanoma), using the most common histological forms and excluding rare ones. All these tumors except one were clearly induced by UV based on the mutational signature. The tumor mutational burden was low in TWM, except in the NF1 mutant forms, and a relatively high frequency of elevated LOH scores suggested frequent homologue recombination deficiency, but this was only confirmed by the mutation signature in one case. Furthermore, all these TWMs were microsatellite-stabile. In this driverless setting, we revealed rare oncogenic drivers known from melanoma or other cancer types and identified rare actionable tyrosine kinase mutations in NTRK1, RET and VEGFR1. Mutations of TWM identified genes involved in antitumor immunity (negative and positive predictors of immunotherapy), Ca++ and BMP signaling. The two regressed melanomas of this cohort shared a 17-gene mutation signature, containing genes involved in antitumor immunity and several cell surface receptors. Even with this comprehensive genomic approach, a few cases remained driverless, suggesting that unrecognized drivers are hiding among passenger mutations.

Genetic trajectory and clonal evolution of multiple primary lung cancer with lymph node metastasis

Multiple primary lung cancer (MPLC) with lymph node metastasis (LNM) is a rare phenomenon of multifocal lung cancer. The genomic landscapes of MPLC and the clonal evolution pattern between primary lung lesions and lymph node metastasis haven't been fully illustrated. We performed whole-exome sequencing (WES) on 52 FFPE (Formalin-fixed Paraffin-Embedded) samples from 11 patients diagnosed with MPLC with LNM. Genomic profiling and phylogenetic analysis were conducted to infer the evolutional trajectory within each patient. The top 5 most frequently mutated genes in our study were TTN (76.74%), MUC16 (62.79%), MUC19 (55.81%), FRG1 (46.51%), and NBPF20 (46.51%). For most patients in our study, a substantial of genetic alterations were mutually exclusive among the multiple pulmonary tumors of the same patient, suggesting their heterogenous origins. Individually, the genetic profile of lymph node metastatic lesions overlapped with that of multiple lung cancers in different degrees but are more genetically related to specific pulmonary lesions. SETD2 was a potential metastasis biomarker of MPLC. The mean putative neo-antigen number of the primary tumor (646.5) is higher than that of lymph node metastases (300, p = 0.2416). Primary lung tumors and lymph node metastases are highly heterogenous in immune repertoires. Our findings portrayed the comprehensive genomic landscape of MPLC with LNM. We characterized the genomic heterogeneity among different tumors. We offered novel clues to the clonal evolution between MPLC and their lymphatic metastases, thus advancing the treatment strategies and preventions of MPLC with LNM.

An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer

Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets in various tumors. However, the role of IRGs in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features characterizing the IRGs in GC. Data were acquired from the TCGA and GEO databases. The Cox regression analyses were performed to develop a prognostic risk signature. The genetic variants, immune infiltration, and drug responses associated with the risk signature were explored using bioinformatics methods. Lastly, the expression of the IRS was verified by qRT-PCR in cell lines. In this manner, an immune-related signature (IRS) was established based on 8 IRGs. According to the IRS, patients were divided into the low-risk group (LRG) and high-risk group (HRG). Compared with the HRG, the LRG was characterized by a better prognosis, high genomic instability, more CD8+ T cell infiltration, greater sensitivity to chemotherapeutic drugs, and greater likelihood of benefiting from the immunotherapy. Moreover, the expression result showed good consistency between the qRT-PCR and TCGA cohort. Our findings provide insights into the specific clinical and immune features underlying the IRS, which may be important for patient treatment.

Whole-genome characterization of large-cell lung carcinoma: A comparative analysis based on the histological classification

Background: According to the 2015 World Health Organization classification, large cell neuroendocrine carcinoma (LCNEC) was isolated from Large-cell lung cancer (LCLC) tumors, which constitutes 2%-3% of non-small cell lung cancer (NSCLC). However, LCLC tumors are still fairly vaguely defined at the molecular level compared to other subgroups. Materials and Methods: In this study, whole-genome sequencing (WGS) was performed on 23 LCLC and 15 LCNEC tumor specimens. Meanwhile, data from the TCGA (586 LUADs and 511 LUSCs) and U Cologne (120 SCLCs) were analyzed and compared. Results: The most common driver mutations were found in TP53 (13/23, 57%), FAM135B (8/23, 35%) and FAT3 (7/23, 30%) in LCLC, while their counterparts in LCNEC were TP53 (13/15, 87%), LRP1B (6/15, 40%) and FAT1 (6/15, 40%). Notably, FAM135B mutations only occurred in LCLC (P = 0.013). Cosmic signature analysis revealed widespread defective DNA mismatch repair and tobacco-induced mutations in both LCLC and LCNEC. Additionally, LCNEC had a higher incidence of chromosomal copy number variations (CNVs) and structural variations (SVs) compared with LCLC, although the differences were not statistically significant. Particularly, chromothripsis SVs was significantly associated with CNVs. Furthermore, mutational landscape of different subtypes indicated differences between subtypes, and there seems to be more commonalty between our cohort and SCLC than with other subtypes. SMARCA4 mutations may be specific driver gene alteration in our cohort. Conclusion: Our results support that LCLC and LCNEC tumors follow distinct tumorigenic pathways. To our knowledge, this is the first genome-wide profiling comparison of LCLC and LCNEC.

Heterogeneous pattern of gene expression driven by TTN mutation is involved in the construction of a prognosis model of lung squamous cell carcinoma

Objective

To investigate the impact that TTN mutation had on the gene heterogeneity expression and prognosis in patients with lung adenocarcinoma.

Methods

In this study, the Cancer Genome Atlas (TCGA) dataset was used to analyze the TTN mutations in lung adenocarcinoma. Lung adenocarcinoma data was collected from the TCGA database, clinical information of patients was analyzed, and bioinformatics statistical methods were applied for mutation analysis and prognosis survival analysis. The results were verified using the GEO dataset.

Results

The incidence of TTN mutations in lung adenocarcinoma was found to be 73%, and it was related to the prognosis of lung adenocarcinoma. Ten genes were screened with significant contributions to prognosis. A prognosis model was constructed and verified by LASSO COX analysis in the TCGA and GEO datasets based on these ten beneficial factors. The independent prognostic factor H2BC9 for TTN mutation-driven gene heterogeneity expression was screened through multi-factor COX regression analysis.

Conclusion

Our data showed that the gene heterogeneity expression, which was driven by TTN mutations, prolonged the survival of lung adenocarcinoma patients and provided valuable clues for the prognosis of TTN gene mutations in lung adenocarcinoma.

Analysis of prognostic oncogene filaggrin (FLG) wild-type subtype and its implications for immune checkpoint blockade therapy in bladder urothelial carcinoma

BACKGROUND

Bladder urothelial carcinoma (BLCA) is one of the most common urinary tract malignant tumors. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. This study aimed to investigate the role of specific genetic mutations that may serve as immune biomarkers for ICB therapy in BLCA.

METHODS

Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the subtypes with poor prognosis of BLCA. Functional enrichment analysis was also conducted. The infiltrating immune cells and the prediction of ICB response between different subtypes were explored using the immuCellAI algorithm. Cell Counting Kit-8 (CCK-8) and flow cytometry assays were conducted to explore the effect of filaggrin (FLG) knockdown in BLCA 5637 and T24 cell lines.

RESULTS

An overview of mutation information in BLCA patients was shown. FLG was identified to be strongly associated with the prognosis of BLCA patients and FLG wild-type was associated with poorer outcome. Prognostic FLG wild-type was divided into 2 subtypes (Sub1 and Sub2). Following an investigation of the subtypes, Sub2 of FLG wild-type was found to be associated with poorer outcome in BLCA. The differentially expressed genes (DEGs) between Sub1 and Sub2 were screened out and the DEGs were enriched in malignant tumor proliferation, DNA damage repair, and immune-related pathways. Furthermore, Sub2 of FLG wild-type was associated with infiltrated immune cells, and responded worse to ICB. Sub2 of FLG wild-type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. The cellular experiments revealed that knockdown of FLG could suppress BLCA cell proliferation and promote apoptosis.

CONCLUSIONS

FLG is an oncogene that may affect the prognosis of BLCA patients through mutation. Sub2 of FLG wild-type is associated with poor prognosis and can be used to predict ICB response for BLCA treatment. This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

N6-Methyladenosine (m6A)-Related lncRNAs Are Potential Signatures for Predicting Prognosis and Immune Response in Lung Squamous Cell Carcinoma

Background

Despite increasing understanding of m⁶A-related lncRNAs in lung cancer, the role of m⁶A-related lncRNAs in the prognosis and treatment of lung squamous cell carcinoma is poorly understood to date. Thus, the current study aims to elucidate its role and build a model to predict the prognosis of LUSC patients.

Materials and Methods

The data of the current study were accessed from the TCGA database. Pearson correlation analysis was performed to identify lncRNAs correlated to m⁶A. Next, an m⁶A-related lncRNAs risk model was built using a single factor, least absolute association, selection operator, and multivariate Cox regression analysis.

Results

The relevance between 23 m⁶A genes and 14,056 lncRNAs is shown by Pearson correlation analysis by Sankey diagram. Multivariate Cox regression analysis determined that 11 m⁶A-lncRNAs show predictive potential in prognosis, which is confirmed by the consistency index, Kaplan–Meier analysis, principal component analysis, and ROC curve. Additionally, the immune analysis showed that the enrichment of immune cells, major histocompatibility complex molecules, and immune checkpoints in the high and low-risk subgroups were markedly disparate, with the high-risk group showing a stronger immune escape ability and a worse response to immunotherapy.

Conclusion

In conclusion, the risk model based on m⁶A-related lncRNAs showed great promise in predicting the prognosis and the efficacy of immunotherapy.

Comprehensive Analysis of Genomic and Expression Data Identified Potential Markers for Predicting Prognosis and Immune Response in CRC

Colorectal cancer (CRC) is the most prevalent type of malignant tumor of the gastrointestinal tract. In the current study, we characterized the landscape of genomic alterations in CRC patients. Based on the results of whole-exome sequencing (WES), we identified 31 significantly mutated genes. Among them, several genes including TP53, KRAS, APC, PI3KCA, and BRAF were reported as significantly mutated genes in previous studies. In the current study, the most frequently mutated gene was TP53, which encodes tumor suppressor p53, affecting approximately 60% of CRC patients. In addition, we performed the expression profiles of significantly mutated genes between the normal group and tumor groups and identified 20 differentially expressed genes (DEGs); among them, CSMD3, DCHS2, LRP2, RYR2, and ZFHX4 were significantly negatively correlated with PFS. Moreover, consensus clustering analysis for CRC based on the expression of significantly somatic mutated genes was performed. In total, three subtypes of CRC were identified in CRC, including cluster1 (n = 453), cluster2 (n = 158), and cluster 3 (n = 9), based on expression level of significantly somatic mutated genes. Clinicopathological features analysis showed subtype C1 had the longest progression-free survival (PFS) with median time of 8.2 years, while subtypes C2 and C3 had 4.1 and 2.7 years of PFS, respectively. Moreover, we found three subtypes related to tumor infiltration depth, lymph node metastasis, and distant metastasis. Immune infiltration analysis showed the tumor infiltration levels of B cell native, T cell CD8+, T cell CD4+ memory activated, T cell gamma delta, NK cell resting, macrophage M0, macrophage M2, myeloid dendritic cell activated, mast cell activated, and mast cell resting significantly changed among the three groups, demonstrating the three subgroups classified by 22 somatically significantly mutated genes had a high capacity to differentiate patients with different immune statuses, which is helpful for the prediction of immunotherapy response of CRC patients. Our findings could provide novel potential predictive indicators for CRC prognosis and therapy targets for CRC immunotherapy.