Association of clock-like mutational signature with immune checkpoint inhibitor outcome in patients with melanoma and NSCLC

Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer

Metabolic reprogramming dictates tumor molecular attributes and therapeutic potentials. However, the comprehensive metabolic characteristics in gastric cancer (GC) remain obscure. Here, metabolic signature-based clustering analysis identifies three subtypes with distinct molecular and clinical features: MSC1 showed better prognosis and upregulation of the tricarboxylic acid (TCA) cycle and lipid metabolism, combined with frequent TP53 and RHOA mutation; MSC2 had moderate prognosis and elevated nucleotide and amino acid metabolism, enriched by intestinal histology and mismatch repair deficient (dMMR); and MSC3 exhibited poor prognosis and enhanced glycan and energy metabolism, accompanied by diffuse histology and frequent CDH1 mutation. The Shandong Provincial Hospital (SDPH) in-house dataset with matched transcriptomic, metabolomic, and spatial-metabolomic analysis also validated these findings. Further, we constructed the metabolic subtype-related prognosis gene (MSPG) scoring model to quantify the activity of individual tumors and found a positive correlation with cuproptosis signaling. In conclusion, comprehensive recognition of the metabolite signature can enhance the understanding of diversity and heterogeneity in GC.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

Prognostic and immune correlation analysis of mitochondrial autophagy and aging-related genes in lung adenocarcinoma

PURPOSE

Mitophagy and aging (MiAg) are very important pathophysiological mechanisms contributing to tumorigenesis. MiAg-related genes have prognostic value in lung adenocarcinoma (LUAD). However, prognostic, and immune correlation studies of MiAg-related genes in LUAD are lacking.

METHODS

MiAg differentially expressed genes (DEGs) in LUAD were obtained from public sequencing datasets. A prognostic model including MiAg DEGs was constructed according to patients divided into low- and high-risk groups. Gene Ontology, gene set enrichment analysis, gene set variation analysis, CIBERSORT immune infiltration analysis, and clinical characteristic correlation analyses were performed for functional annotation and correlation of MiAgs with prognosis in patients with LUAD.

RESULTS

Seven MiAg DEGs of LUAD were identified: CAV1, DSG2, DSP, MYH11, NME1, PAICS, PLOD2, and the expression levels of these genes were significantly correlated (P < 0.05). The RiskScore of the MiAg DEG prognostic model demonstrated high predictive ability of overall survival of patients diagnosed with LUAD. Patients with high and low MiAg phenotypic scores exhibited significant differences in the infiltration levels of eight types of immune cells (P < 0.05). The multi-factor DEG regression model showed higher efficacy in predicting 5-year survival than 3- and 1-year survival of patients with LUAD.

CONCLUSIONS

Seven MiAg-related genes were identified to be significantly associated with the prognosis of patients diagnosed with LUAD. Moreover, the identified MiAg DEGs might affect the immunotherapy strategy of patients with LUAD.

Life quality improvement of patients with non-small cell lung cancer undergoing targeted therapy: A case study of continuous care

To investigate the improvement effect of targeted therapy on non-small cell carcinoma patients life quality after the continuous nursing intervention. 104 non-small cell lung cancer patients in our hospital from July 2017 to November 2019 were allocated evenly and randomly into the control group (C) and the study group (S). By using clinical baseline data, quality of life questionnaire core 30 for cancer patients, evaluation of patient compliance behavior, the MOS item short-form health survey (SF-36), self rating depression scale (SDS), self rating anxiety scale (SAS), Overall Survival (OS) progression-free survival and adverse reaction symptoms were evaluated for the life quality of patients. There was comparability between the 2 sets of basic data. There was no significant difference in quality of life questionnaire core 30, SF-36, SAS, or SDS scores before treatment. After 3 months, there was a significant difference in the scores of various scales before treatment. At the same time, there was significant statistical significance before and after treatment in Group S. Their compliance rates were 84.62% and 98.08%. Adverse reactions incidence in Group S was lower. Taking a 2-year follow-up period as an example, significant statistical differences existed in OS and progression-free survival rates between adenocarcinoma and squamous carcinoma. SDS and SAS had high consistency in scoring with QLQ-30 and SF-36 scales. Targeted treatment for non-small cell carcinoma patients significantly improves their life quality and reduces the incidence of adverse reactions after continuous nursing intervention.

Construction of an aging-related risk signature in high-grade serous ovarian cancer for predicting survival outcome and immunogenicity

Studies have shown that aging significantly impacts tumorigenesis, survival outcome, and treatment efficacy in various tumors, covering high-grade serous ovarian cancer (HGSOC). Therefore, the objective for this investigation is to construct an aging-relevant risk signature for the first time, which will help evaluate the immunogenicity and survival status for patients with HGSOC. Totaling 1727 patients with HGSOC, along with their mRNA genomic data and clinical survival data, were obtained based on 5 independent cohorts. The Lasso-Cox regression model was utilized to identify the aging genes that had the most significant impact on prognosis. The risk signature was developed by integrating the determined gene expression and accordant model weights. Additionally, immunocytes in the microenvironment, signaling pathways, and immune-relevant signatures were assessed based on distinct risk subgroups. Finally, 2 cohorts that underwent treatment with immune checkpoint inhibitor (ICI) were employed to confirm the effects of identified risk signature on ICI efficacy. An aging signature was constructed from 12 relevant genes, which showed improved survival outcomes in low-risk HGSOC patients across discovery and 4 validation cohorts (all P < .05). The low-risk subgroup showed better immunocyte infiltration and higher enrichment of immune pathways and ICI predictors based on further immunology analysis. Notably, in the immunotherapeutic cohorts, low-risk aging signature was observed to link to better immunotherapeutic outcomes and increased response rates. Together, our constructed signature of aging has the potential to assess not only the prognosis outcome and immunogenicity, but also, importantly, the efficacy of ICI treatment. This signature provides valuable insights for prognosis prediction and immunotherapeutic effect evaluation, ultimately promoting individualized treatment for HGSOC patients.

Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES

Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).

METHODS

Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.

RESULTS

The ICI efficacy predictor performed poorly with an accuracy of 0.51-0.09+0.09, average precision of 0.52-0.11+0.11, and an area under the receiver operating characteristic curve of 0.50-0.09+0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions.

CONCLUSION

MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.

Clock-like Mutation Signature May Be Prognostic for Worse Survival Than Signatures of UV Damage in Cutaneous Melanoma

Novel treatment modalities comprising immune checkpoint inhibitors and targeted therapies have revolutionized treatment of metastatic melanoma. Still, some patients suffer from rapid progression and decease within months after a diagnosis of stage IV melanoma. We aimed to assess whether genomic alterations may predict survival after the development of stage IV disease, irrespective of received therapy. We analyzed tumor samples of 79 patients with stage IV melanoma using a custom next-generation gene-sequencing panel, MelArray, designed to detect alterations in 190 melanoma-relevant genes. We classified the patients: first, as short survivors (survival ≤6 months after stage IV disease, n = 22) and long survivors (survival >6 months, n = 57); second, by using a cut-off of one year; and third, by comparing the longest surviving 20 patients to the shortest surviving 20. Among analyzed genes, no individual gene alterations, or combinations of alterations, could be dichotomously associated with survival. However, the cohort's mutational profiles closely matched three known mutational signatures curated by the Catalog of Somatic Mutations in Cancer (COSMIC): UV signature COSMIC_7 (cosine-similarity 0.932), clock-like signature COSMIC_5 (cosine-similarity 0.829), and COSMIC_30 (cosine-similarity 0.726). Patients with UV signature had longer survival compared to patients with clock-like and COSMIC 30 (p < 0.0001). Subgroup dichotomization at 6 months showed that 75% of patients with UV signature survived longer than 6 months, and about 75% of patients with clock-like signature survived less than 6 months after development of stage IV disease. In our cohort, clock-like COSMIC_5 mutational signature predicted poor survival while a UV signature COSMIC_7 predicted longer survival. The prognostic value of mutational signatures should be evaluated in prospective studies.

Integrating somatic CNV and gene expression in breast cancers from women with PTEN hamartoma tumor syndrome

Women with germline PTEN variants (PTEN hamartoma tumor syndrome, PHTS) have up to 85% lifetime risk of female breast cancer (BC). We previously showed that PHTS-derived BCs are distinct from sporadic BCs both at the clinical and genomic levels. In this study, we examined somatic copy number variations (CNV) and transcriptome data to further characterize the somatic landscape of PHTS-derived BCs. We analyzed exome sequencing data from 44 BCs from women with PHTS for CNV. The control group comprised of 558 women with sporadic BCs from The Cancer Genome Atlas (TCGA) dataset. Here, we found that PHTS-derived BCs have several distinct CNV peaks compared to TCGA. Furthermore, RNA sequencing data revealed that PHTS-derived BCs have a distinct immunologic cell type signature, which points toward cancer immune evasion. Transcriptomic data also revealed PHTS-derived BCs with pathogenic germline PTEN variants appear to have vitamin E degradation as a key pathway associated with tumorigenesis. In conclusion, our study revealed distinct CNV x transcript features in PHTS-derived BCs, which further facilitate understanding of BC biology arising in the setting of germline PTEN mutations.

Unveiling the interplay between mutational signatures and tumor microenvironment: a pan-cancer analysis

Background

While recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context.

Materials and methods

We performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis.

Results

Our analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature.

Conclusion

Our study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

Using genomic scars to select immunotherapy beneficiaries in advanced non-small cell lung cancer

In advanced non-small cell lung cancer (NSCLC), response to immunotherapy is difficult to predict from pre-treatment information. Given the toxicity of immunotherapy and its financial burden on the healthcare system, we set out to identify patients for whom treatment is effective. To this end, we used mutational signatures from DNA mutations in pre-treatment tissue. Single base substitutions, doublet base substitutions, indels, and copy number alteration signatures were analysed in [Formula: see text] patients (the discovery set). We found that tobacco smoking signature (SBS4) and thiopurine chemotherapy exposure-associated signature (SBS87) were linked to durable benefit. Combining both signatures in a machine learning model separated patients with a progression-free survival hazard ratio of 0.40[Formula: see text] on the cross-validated discovery set and 0.24[Formula: see text] on an independent external validation set ([Formula: see text]). This paper demonstrates that the fingerprints of mutagenesis, codified through mutational signatures, select advanced NSCLC patients who may benefit from immunotherapy, thus potentially reducing unnecessary patient burden.

A mutational signature and significantly mutated driver genes associated with immune checkpoint inhibitor response across multiple cancers

Immune checkpoint inhibitor (ICI) treatments dramatically prolong the survival outcomes of several advanced cancers. However, as multiple studies reported, only a subset of patients could benefit from the ICI treatment. In this study, we aim to uncover novel molecular biomarkers predictive of immunotherapy efficacy across multiple cancers. Pre-treatment somatic mutational profiles and immunotherapy clinical information were obtained from 1097 samples of multiple cancers, including melanoma, non-small cell lung cancer (NSCLC), clear cell renal cell carcinoma (ccRCC), bladder carcinoma (BLCA), and head and neck squamous cell carcinoma (HNSCC). Mutational signatures, molecular subtypes, and significantly mutated genes (SMGs) were determined, and their connections with ICI response and outcome were also evaluated. We extracted a total of six mutational signatures across all samples. Among, a mutational signature featured by T > C substitutions was identified to associate with an ICI resistance. A molecular subtype determined based on mutational activities was connected with a significantly improved ICI response rate and outcome. Totaling 50 SMGs were identified, and we observed that patients with COL11A1 or COL4A6 mutations exhibited a superior ICI treatment efficacy than those without such mutations. In this study, we uncovered several novel molecular determinants of cancer immunotherapy response under a multiple-cancer setting, which provides clues for enrolling patients to receive immunotherapy and customizing personalized treatment strategies.

Molecular underpinnings of exceptional response in primary malignant melanoma of the esophagus to anti-PD-1 monotherapy

BACKGROUND

Accumulating data suggest that mucosal melanoma, well known for its poor response to immune checkpoint blockade (ICB) and abysmal prognosis, is a heterogeneous subtype of melanoma with distinct genomic and clinical characteristics between different anatomic locations of the primary lesions. Primary malignant melanoma of the esophagus (PMME) is a rare, highly aggressive disease with a poorer prognosis compared with that of non-esophageal mucosal melanoma (NEMM). In this study, we retrospectively analyzed the efficacy of anti-programmed death (PD)-1 in patients with PMME and explored its molecular basis.

METHODS

The response and survival of patients with PMME and NEMM under anti-PD-1 monotherapy were retrospectively analyzed. To explore the molecular mechanisms of the difference in therapeutic efficacy between PMME and NEMM, we performed genomic analysis, bulk RNA sequencing, and multiplex immunohistochemistry staining.

RESULTS

We found that PMME (n=28) responded better to anti-PD-1 treatment than NEMM (n=64), with a significantly higher objective response rate (33.3% (95% CI 14.3% to 52.3%) vs 6.6% (95% CI 0.2% to 12.9%)) and disease control rate (74.1% (95% CI 56.4% to 91.7%) vs 37.7% (95% CI 25.2% to 50.2%)). Genomic sequencing analysis revealed that the genomic aberration landscape of PMME predominated in classical cancer driver genes, with approximately half of PMME cases harboring mutations in BRAF, N/KRAS, and NF1. In contrast, most NEMM cases were triple wild-type. Transcriptome analysis revealed that, compared with NEMM, PMME displayed more significant proliferation and inflammatory features with higher expression of genes related to antigen presentation and differentiation, and a less immunosuppressive signature with lower expression of inhibitory immune checkpoints and dedifferentiation-related genes. The multiplex immunohistochemical analysis also demonstrated higher CD8⁺ T-cell infiltration in PMME than in NEMM.

CONCLUSIONS

PMME is an outlier of mucosal melanoma showing a malicious phenotype but a particularly high response rate to ICB because of its distinct molecular characteristics. Patient stratification based on anatomic origin can facilitate clinical decision-making in patients with mucosal melanoma following the verification of our results in future prospective studies.

Prognostic biomarkers correlated with immune infiltration in non-small cell lung cancer

Lung cancer is the leading cause of cancer-related mortality in men and women globally. Non-small cell lung cancer (NSCLC) is the most prevalent subtype, accounting for 85-90% of all cancers. Although there have been dramatic advances in therapeutic approaches in recent decades, the recurrence and metastasis rates of NSCLC are as high as 30-40% with the 5-year overall survival rate being less than 15%. Therefore, it is necessary to explore the pathogenesis of NSCLC at the genetic level and identify prognostic biomarkers and novel therapeutic targets. Here, we aimed to identify mutated genes with high frequencies in Chinese NSCLC patients using next-generation sequencing and to investigate their relationships with the tumor mutation burden (TMB) and tumor immune microenvironment. A total of 110 NSCLC patients were enrolled to profile the genetic variations. Mutations in EGFR (62.37%), TP53 (61.29%), LRP1B (13.98%), FAT1 (12.90%), KMT2D (11.83%), CREBBP (10.75%), and RB1 (9.68%) were most prevalent. TP53, LRP1B, KMT2D, and CREBBP mutations were all significantly associated with high TMB (P < 0.05 or P < 0.01). The infiltrating levels of immune cells and immune molecules were enriched significantly in the LRP1B mutation group. LRP1B mutations significantly correlated with stimulating and inhibitory immunoregulators. Gene set enrichment analysis revealed that cell cycle, the Notch signaling pathway, the insulin signaling pathway, and the mTOR signaling pathway are related to LRP1B mutations in the immune system. LRP1B mutations may be of clinical importance in enhancing the anti-tumor immune response and may be a promising biomarker for predicting immunotherapy responsiveness.

Two subtypes of cutaneous melanoma with distinct mutational signatures and clinico-genomic characteristics

Background: To decipher mutational signatures and their associations with biological implications in cutaneous melanomas (CMs), including those with a low ultraviolet (UV) signature.

Materials and Methods: We applied non-negative matrix factorization (NMF) and unsupervised clustering to the 96-class mutational context of The Cancer Genome Atlas (TCGA) cohort (N = 466) as well as other publicly available datasets (N = 527). To explore the feasibility of mutational signature-based classification using panel sequencing data, independent panel sequencing data were analyzed.

Results: NMF decomposition of the TCGA cohort and other publicly available datasets consistently found two mutational signatures: UV (SBS7a/7b dominant) and non-UV (SBS1/5 dominant) signatures. Based on mutational signatures, TCGA CMs were classified into two clusters: UV-high and UV-low. CMs belonging to the UV-low cluster showed significantly worse overall survival and landmark survival at 1-year than those in the UV-high cluster; low or high UV signature remained the most significant prognostic factor in multivariate analysis. The UV-low cluster showed distinct genomic and functional characteristic patterns: low mutation counts, increased proportion of triple wild-type and KIT mutations, high burden of copy number alteration, expression of genes related to keratinocyte differentiation, and low activation of tumor immunity. We verified that UV-high and UV-low clusters can be distinguished by panel sequencing.

Conclusion: Our study revealed two mutational signatures of CMs that divide CMs into two clusters with distinct clinico-genomic characteristics. Our results will be helpful for the clinical application of mutational signature-based classification of CMs.

Distinct non-clock-like signatures of the basal cell carcinomas from three sisters with a lethal Gorlin-Goltz syndrome

Background

Gorlin-Goltz syndrome (GS) is an inherited disease characterized by predisposition to basal cell carcinomas (BCCs) and various developmental defects, whose numerous disease-causing PTCH1 mutations have been identified in the hedgehog (Hh) signaling pathway.

Methods

In this study, whole exome sequencing was used to screen for both somatic and germline deleterious mutations in three sisters with a lethal GS. The mutations we found were confirmed by subcloning and Sanger sequencing of the genomic DNA. RNA-seq was performed to profile gene expression in paired BCCs samples and the expression levels for selected genes were validated by quantitative PCR.

Results

The clinical and histopathologic features were analyzed for the proband in the three-generation GS family. We identified the insertion mutation PTCH1 c.1341dupA (p. L448Tfs*49), which segregated with BCC phenotype and contributed to the death of two in four patients from a Chinese family with GS. Compared with adjacent non-cancerous tissues (ANCT), four second-hit mutations were found in four of the six pairs of BCC from three patients. Of note, somatic genomic alterations in all six BCC samples were mainly clustered into non-clock-like Signature 7 (ultraviolet mutagenesis) and 11 (related to certain alkylating agents). Both RNA-seq and quantitative RT-PCR confirmed that the mRNA levels of PTCH1 and its effector GLI1 were markedly upregulated in six pairs of BCC samples versus ANCT.

Conclusions

The distinct non-clock-like signatures of BCCs indicated that GS was not a life-threatening illness. The main reasons for untimely death of GS patients were PTCH1 mutation, exposure to intense ultraviolet radiationand the poor economic conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01324-7.

Single-cell transcriptomic analysis reveals circadian rhythm disruption associated with poor prognosis and drug-resistance in lung adenocarcinoma

Circadian rhythm disruption (CRD) represents a major contributor to tumor proliferation. Nonetheless, the role of CRD in the clinical prediction of cancer outcomes has not been well studied. In this study, we developed a computational algorithm, which was implemented in an open-source R package CRDscore, to define the intratumoral status of circadian disruption in three representative single-cell RNA-seq data sets of lung adenocarcinoma. We found that the malignant cells with high CRDscore were characterized by activation of glycolysis and epithelial-mesenchymal transition pathways. Furthermore, cell communication analysis indicated that CRD played a pivotal role in T cell exhaustion, which may be responsible for the poor prognosis of the malignancy. We then validated the findings with public bulk transcriptome datasets involving 22 cancer types. Cox regression analysis revealed that the CRDscore was a valuable prognostic biomarker. A model containing 23 circadian-related genes performed well in predicting immunotherapeutic outcomes in 14 independent cohorts. Importantly, decreased CRDscore was detect by RNA sequencing on H1299 cells with melatonin treatment. Meanwhile, the cells downregulated the expression level of SNAIL and TWIST, which contributed to an invasive phenotype. In conclusion, this study provides a novel computational framework for characterizing CRD status using single-cell transcriptomic data and further confirmed the molecular mechanisms underlying metabolic reprogramming and T cell exhaustion under CRD. The better understanding of the mechanisms may provide new possibilities for incorporating "anticancer approaches based on circadian clocks" into the treatment protocols of precision medicine.

Mutation burden-orthogonal tumor genomic subtypes delineate responses to immune checkpoint therapy

Background

In cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.

Methods

Based on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (Genomic Subtyping and Predictive Response Analysis for Cancer Tumor ICi Efficacy, GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.

Results

Systematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.

Conclusions

The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Deciphering the tumor cell-infiltrating landscapes reveal microenvironment subtypes and therapeutic potentials for nonsquamous NSCLC

Recent studies highlighted the clinicopathologic importance of tumor microenvironment (TME) in delineating molecular attributes and therapeutic potentials. However, the overall TME cell-infiltration landscape in non-squamous NSCLC have not been comprehensively recognized. In this study, we employed consensus non-negative matrix factorization (NMF) molecular subtyping to determine the TME cell infiltration patterns and identified three TME clusters (TME-C1, -C2, -C3) characterized by distinct clinicopathologic features, infiltrating cells, and biological processes. Proteomics analyses revealed that cGAS-STING immune signaling mediated protein and phosphorylation level were significantly upregulated in inflamed-related TME-C2 clusters. The TMEsig-score extracted from the TME-related signature divided NSCLC patients into high- and low-score subgroups, where a high score was associated with favorable prognosis and immune infiltration. Genomic landscape revealed that patients with low TMEsig-score harbored greater somatic copy number alternations and higher mutation frequency of driver genes involving STK11, KEAP1 and SMARCA4 et al. Drug sensitivity analyses suggested that tumors with high TMEsig-score were responsible for favorable clinical response to immune check-point inhibitors (ICI) treatment. In summary, this study highlights that comprehensive recognizing of the TME cell infiltration landscape will contribute to enhance our understanding of TME immune regulation and promote effectiveness of precision biotherapy strategies.

Th1 immune maturation effects of

Nocardia rubra cell-wall skeleton (Nr-CWS) is reported as an external immunotherapeutic enhancer with the advantage of antitumor effect on human cancers. However, the immune regulatory role of Nr-CWS is not fully illustrated. We studied mouse CD4+ T lymphocytes isolated from mice spleen were induced by Nr-CWS and observed that the differentiation of Th1 CD4+ T cells and the cytokines of IL-2, TNF-α, IFN-γ were all enhanced by Nr-CWS. Furthermore, RNA sequencing was conducted to investigate the different mRNA profiling induced by Nr-CWS. We observed that paired box 8 (PAX8) was significantly up-regulated in Nr-CWS-treated Th1 cells compared to control. As a transcription factor, chromatin immunoprecipitation sequencing was carried out to study the genome-wide distribution of PAX8. Interestingly, we found that the binding domain of PAX8 was elevated by Nr-CWS, and the target genes associated with these binding sites showed a positive correlation between their transcription and PAX8 binding strength. Finally, we determined that Nr-CWS could enhance the activity of the PI3 K/Akt signaling pathway. Akt agonist could mimic the effect of Nr-CWS for PAX8 up-regulation, while Akt inhibitor compromised the expression of PAX8. Taken together, we determined a novel role of Nr-CWS in boosting the activity of Th1 maturation via the PI3 K/Akt/PAX8 axis.

Shared genetic and epigenetic changes link aging and cancer

Aging is a universal biological process that increases the risk of multiple diseases including cancer. Growing evidence shows that alterations in the genome and epigenome, driven by similar mechanisms, are found in both aged cells and cancer cells. In this review, we detail the genetic and epigenetic changes associated with normal aging and the mechanisms responsible for these changes. By highlighting genetic and epigenetic alterations in the context of tumorigenesis, cancer progression, and the aging tumor microenvironment, we examine the possible impacts of the normal aging process on malignant transformation. Finally, we examine the implications of age-related genetic and epigenetic alterations in both tumors and patients for the treatment of cancer.

An aging-related signature predicts favorable outcome and immunogenicity in lung adenocarcinoma

Aging has been demonstrated to play vital roles in the prognosis and treatment efficacy of cancers, including lung adenocarcinoma (LUAD). This novel study aimed to construct an aging‐related risk signature to evaluate the prognosis and immunogenicity of LUAD. Transcriptomic profiles and clinical information were collected from a total of 2518 LUAD patients from 12 independent cohorts. The risk signature was developed by combining specific gene expression with the corresponding regression coefficients. One cohort treated with the immune checkpoint inhibitor (ICI) was also used. Subsequently, a risk signature was developed based on 21 aging‐related genes. LUAD patients with low‐risk scores exhibited improved survival outcomes in both the discovery and validation cohorts. Further immunology analysis revealed elevated lymphocyte infiltration, decreased infiltration of immune‐suppressive cells, immune response‐related pathways, and favorable ICI predictor enrichment in the low‐risk subgroup. Genomic mutation exploration indicated the enhanced mutation burden and higher mutation rates in significantly driver genes of TP53, KEAP1, SMARCA4, and RBM10 were enriched in patients with a low‐risk signature. In the immunotherapeutic cohort, it was observed that low‐risk aging scores were markedly associated with prolonged ICI prognosis. Overall, the estimated aging signature proved capable of evaluating the prognosis, tumor microenvironment, and immunogenicity, which further provided clues for tailoring prognosis prediction and immunotherapy strategies, apart from promoting individualized treatment plans for LUAD patients.

Identification of m6A Regulator-Associated Methylation Modification Clusters and Immune Profiles in Melanoma

RNA N6-methyladenosine (m⁶A) modification in tumorigenesis and progression has been highlighted and discovered in recent years. However, the molecular and clinical implications of m⁶A modification in melanoma tumor microenvironment (TME) and immune infiltration remain largely unknown. Here, we utilized consensus molecular clustering with nonnegative matrix factorization based on the melanoma transcriptomic profiles of 23 m⁶A regulators to determine the m⁶A modification clusters and m⁶A-related gene signature. Three distinct m⁶A modification patterns (m⁶A-C1, C2, and C3), which are characterized by specific m⁶A regulator expression, survival outcomes, and biological pathways, were identified in more than 1,000 melanoma samples. The immune profile analyses showed that these three m⁶A modification subtypes were highly consistent with the three known immune phenotypes: immune-desert (C1), immune-excluded (C2), and immune-inflamed (C3). Tumor digital cytometry (CIBERSORT, ssGSEA) algorithm revealed an upregulated infiltration of CD8⁺ T cell and NK cell in m⁶A-C3 subtype. An m⁶A scoring scheme calculated by principal component of m⁶A signatures stratified melanoma patients into high- and low-m⁶sig score subgroups; a high score was significantly associated with prolonged survival and enhanced immune infiltration. Furthermore, fewer somatic copy number alternations (SCNA) and PD-L1 expression were found in patients with high m⁶Sig score. In addition, patients with high m⁶Sig score demonstrated marked immune responses and durable clinical benefits in two independent immunotherapy cohorts. Overall, this study indicated that m⁶A modification is involved in melanoma tumor microenvironment immune regulation and contributes to formation of tumor immunogenicity. Comprehensive evaluation of the m⁶A modification pattern of individual tumors will provide more insights into molecular mechanisms of TME characterization and promote more effective personalized biotherapy strategies.

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

Therapeutic perspectives of extracellular vesicles and extracellular microRNAs in atherosclerosis

Extracellular signaling molecules, such as growth factors, cytokines, and hormones, regulate cell behaviors and fate through endocrine, paracrine, and autocrine actions and play essential roles in maintaining tissue homeostasis. MicroRNAs, an important class of posttranscriptional modulators, could stably present in extracellular space and body fluids and participate in intercellular communication in health and diseases. Indeed, recent studies demonstrated that microRNAs could be secreted through vesicular and non-vesicular routes, transported in body fluids, and then transmitted to recipient cells to regulate target gene expression and signaling events. Over the past decade, a great deal of effort has been made to investigate the functional roles of extracellular vesicles and extracellular microRNAs in pathological conditions. Emerging evidence suggests that altered levels of extracellular vesicles and extracellular microRNAs in body fluids, as part of the cellular responses to atherogenic factors, are associated with the development of atherosclerosis. This review article provides a brief overview of extracellular vesicles and perspectives of their applications as therapeutic tools for cardiovascular pathologies. In addition, we highlight the role of extracellular microRNAs in atherogenesis and offer a summary of circulating microRNAs in liquid biopsies associated with atherosclerosis.

Elevated Stratifin promotes cisplatin-based chemotherapy failure and poor prognosis in non-small cell lung cancer

Drug resistance is a key factor in the treatment failure of clinical non-small cell lung cancer (NSCLC) patients after adjuvant chemotherapy. Here, our results provide the first evidence that eukaryotic translation initiation factor 2b subunit delta (EIF2B4)-Stratifin (SFN) fusion and increased SFN expression are associated with chemotherapy tolerance and activation of the phosphatidylinositol 3 kinase/v-akt murine thymoma viral oncogene (PI3K/Akt) signaling pathway in NSCLC patients, suggesting that SFN might have potential prognostic value as a tumor biomarker for the prognosis of patients with NSCLC.