The immune response-related mutational signatures and driver genes in non-small-cell lung cancer

Integrated bioinformatics analysis identifies ALDH18A1 as a prognostic hub gene in glutamine metabolism in lung adenocarcinoma

Glutamine metabolism is pivotal in cancer biology, profoundly influencing tumor growth, proliferation, and resistance to therapies. Cancer cells often exhibit an elevated dependence on glutamine for essential functions such as energy production, biosynthesis of macromolecules, and maintenance of redox balance. Moreover, altered glutamine metabolism can contribute to the formation of an immune-suppressive tumor microenvironment characterized by reduced immune cell infiltration and activity. In this study on lung adenocarcinoma, we employed consensus clustering and applied 101 types of machine learning methods to systematically identify key genes associated with glutamine metabolism and develop a risk model. This comprehensive approach provided a clearer understanding of how glutamine metabolism associates with cancer progression and patient outcomes. Notably, we constructed a robust nomogram based on clinical information and patient risk scores, which achieved a stable area under the curve (AUC) greater than 0.8 for predicting patient survival across four datasets, demonstrating high predictive accuracy. This nomogram not only enhances our ability to stratify patient risk but also offers potential targets for therapeutic intervention aimed at disrupting glutamine metabolism and sensitizing tumors to existing treatments. Moreover, we identified ALDH18A1 as a prognostic hub gene of glutamine metabolism, characterized by high expression levels in glutamine cluster 3, which is associated with poor clinical outcomes and worse survival, and is included in the risk model. Such insights underscore the critical role of glutamine metabolism in cancer and highlight avenues for personalized medicine in oncology research.

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.

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

Personalized Immunotherapy Achieves Complete Response in Metastatic Adenoid Cystic Carcinoma Despite Lack of Conventional Biomarkers

There is currently no effective treatment strategy for recurrent/metastatic adenoid cystic carcinoma (R/M ACC). Furthermore, recent single-agent and combination immunotherapy trials have failed in unselected ACC cohorts, unlike non-ACC salivary gland cancers. Genomic profiling revealed no actionable targets but NOTCH1 and KDM6A frameshift and CTCF splice site mutations (no MYB/L fusion) with a low tumor mutational burden (TMB), microsatellite stable (MSS) and negative programmed death ligand 1 (PD-L1) were observed. We recommended an anti-programmed cell death protein 1 (anti-PD-1) plus anti-Cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) combination based on TMB 2-fold greater-than-median TMB in ACC, tumor harboring multiple immunogenic frameshift or splice site mutations, and PD-L1 negativity. Accordingly, we achieved a complete response in a radiotherapy (RT) and chemotherapy (CT)-refractory patient with locally recurrent lacrimal gland (LG) ACC and lung metastasis following personalized immunotherapy in combination with integrative therapeutics. Therefore, it is crucial to assess not only conventional immune biomarkers but also patient-specific parameters, especially in "immune-cold" cancer types.

Genomic Landscape of Pulmonary Sarcomatoid Carcinoma

PURPOSE

Pulmonary sarcomatoid carcinoma (PSC) is a rare aggressive subtype of non-small cell lung cancer (NSCLC) with limited therapeutic strategies. We attempted to elucidate the evolutionary trajectories of PSC using multiregional and longitudinal tumor samples.

MATERIALS AND METHODS

A total of 31 patients were enrolled in this study and 11 longitudinal samples were available from them. Using whole exome sequencing data, we analyzed the mutational signatures in both carcinomatous and sarcomatous areas in primary tumors of the 31 patients and longitudinal samples obtained from 11 patients. Furthermore, digital droplet polymerase chain reaction (ddPCR), and programmed death-ligand 1 (PD-L1) immunohistochemistry using the Ventana SP263 assay were performed.

RESULTS

TP53 was identified as the most frequently altered gene in the primary (74%) and metastatic (73%) samples. MET exon 14 skipping mutations, confirmed by ddPCR, and TP53 mutations were mutually exclusive; whereas, MET exon 14 skipping mutations frequently co-occurred with MDM2 amplification. Metastatic tumors showed dissimilar genetic profiles from either primary component. During metastasis, the signatures of APOBEC decreased in metastatic lesions compared with that in primary lesions. PSC showed higher MET and KEAP1 mutations and stronger PD-L1 protein expression compared with that recorded in other NSCLCs.

CONCLUSION

Decreased APOBEC signatures and subclonal diversity were detected during malignant progression in PSC. Frequent MET mutations and strong PD-L1 expression distinguished PSC from other NSCLCs. The aggressiveness and therapeutic difficulties of PSC were possibly attributable to profound intratumoral and intertumoral genetic diversity. Next-generation sequencing could suggest the appropriate treatment strategy for PSC.

CD8+ T-Cell Signatures as Prognostic and Immunotherapy Response Predictors in Non-Small Cell Lung Cancer

Non-small cell lung carcinoma (NSCLC) represents the majority of lung cancer cases, comprising approximately 85 % of the total. The five-year survival rate for NSCLC patients remains discouragingly low. Recently, immunotherapy has emerged as a promising approach. Nevertheless, only a minority of patients experience considerable benefits from these treatments. This highlights the critical need for effective biomarkers that can predict both patient prognosis and response to immunotherapy. CD8+ T cells play a crucial role in cancer immunotherapy. Their presence within tumours is generally indicative of a favourable prognosis and increased efficacy of immunotherapy. This study was undertaken to identify and authenticate a novel biomarker signature based on CD8+ T-cell marker genes, to prognosticate therapeutic responses in individuals afflicted with NSCLC. This in-depth study was based on a total of 1,200 samples, which included four NSCLC specimens analysed through single-cell RNA sequencing (scRNA-seq), 1,000 NSCLC samples obtained from The Cancer Genome Atlas (TCGA) and 196 NSCLC specimens collected from the GSE37745 cohort. In patients with NSCLC, those presenting a favourable risk profile demonstrated notable elevations in specific immune cells while concurrently exhibiting reductions in other types. CD8+ T cells, with their established role in inducing apoptosis in cancer cells, have emerged as crucial predictors and modulators of treatment strategies for NSCLC patients. The combination of single-cell and bulk RNA sequencing has produced a biomarker signature, emphasizing the CD8+ T cells' crucial role in NSCLC prognosis and treatment.

Tackling the immunotherapy conundrum: advances and challenges for operable non-small-cell lung cancer treatment

Lung cancer is the most common cause of cancer-related deaths worldwide. Non-small-cell lung cancer (NSCLC) represents the majority of lung cancer cases, and its standard treatment is primarily surgery. Nonetheless, this type of cancer exhibits an important rate of tumor recurrence. Immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in many cancers, especially in early-stage NSCLC. This review considers the latest CheckMate816, IMpower010 and KEYNOTE-091 trials that led to US FDA approvals. The new wave of resectable NSCLC trial results are also summarized. Finally, the latest challenges for these treatment modalities, such as the choice between neoadjuvant and adjuvant use, the accurate identification of biomarkers and the presence of driver mutations such as EGFR, are discussed.

New insights into the biology and development of lung cancer in never smokers-implications for early detection and treatment

Lung cancer is the leading cause of cancer deaths worldwide. Despite never smokers comprising between 10 and 25% of all cases, lung cancer in never smokers (LCNS) is relatively under characterized from an etiological and biological perspective. The application of multi-omics techniques on large patient cohorts has significantly advanced the current understanding of LCNS tumor biology. By synthesizing the findings of multi-omics studies on LCNS from a clinical perspective, we can directly translate knowledge regarding tumor biology into implications for patient care. Primarily focused on never smokers with lung adenocarcinoma, this review details the predominance of driver mutations, particularly in East Asian patients, as well as the frequency and importance of germline variants in LCNS. The mutational patterns present in LCNS tumors are thoroughly explored, highlighting the high abundance of the APOBEC signature. Moreover, this review recognizes the spectrum of immune profiles present in LCNS tumors and posits how it can be translated to treatment selection. The recurring and novel insights from multi-omics studies on LCNS tumor biology have a wide range of clinical implications. Risk factors such as exposure to outdoor air pollution, second hand smoke, and potentially diet have a genomic imprint in LCNS at varying degrees, and although they do not encompass all LCNS cases, they can be leveraged to stratify risk. Germline variants similarly contribute to a notable proportion of LCNS, which warrants detailed documentation of family history of lung cancer among never smokers and demonstrates value in developing testing for pathogenic variants in never smokers for early detection in the future. Molecular driver subtypes and specific co-mutations and mutational signatures have prognostic value in LCNS and can guide treatment selection. LCNS tumors with no known driver alterations tend to be stem-like and genes contributing to this state may serve as potential therapeutic targets. Overall, the comprehensive findings of multi-omics studies exert a wide influence on clinical management and future research directions in the realm of LCNS.

Machine learning-based immune prognostic model and ceRNA network construction for lung adenocarcinoma

PURPOSE

Lung adenocarcinoma (LUAD) is a malignant tumor with a high lethality rate. Immunotherapy has become a breakthrough in cancer treatment and improves patient survival and prognosis. Therefore, it is necessary to find new immune-related markers. However, the current research on immune-related markers in LUAD is not sufficient. Therefore, there is a need to find new immune-related biomarkers to help treat LUAD patients.

METHODS

In this study, a bioinformatics approach combined with a machine learning approach screened reliable immune-related markers to construct a prognostic model to predict the overall survival (OS) of LUAD patients, thus promoting the clinical application of immunotherapy in LUAD. The experimental data were obtained from The Cancer Genome Atlas (TCGA) database, including 535 LUAD and 59 healthy control samples. Firstly, the Hub gene was screened using a bioinformatics approach combined with the Support Vector Machine Recursive Feature Elimination algorithm; then, a multifactorial Cox regression analysis by constructing an immune prognostic model for LUAD and a nomogram to predict the OS rate of LUAD patients. Finally, the regulatory mechanism of Hub genes in LUAD was analyzed by ceRNA.

RESULTS

Five genes, ADM2, CDH17, DKK1, PTX3, and AC145343.1, were screened as potential immune-related genes in LUAD. Among them, ADM2 and AC145343.1 had a good prognosis in LUAD patients (HR < 1) and were novel markers. The remaining three genes screened were associated with poor prognosis in LUAD patients (HR > 1). In addition, the experimental results showed that patients in the low-risk group had better OS rates than those in the high-risk group (P < 0.001).

CONCLUSION

In this paper, we propose an immune prognostic model to predict OS rate in LUAD patients and show the correlation between five immune genes and the level of immune-related cell infiltration. It provides new markers and additional ideas for immunotherapy in patients with LUAD.

PTEN Loss Confers Resistance to Anti-PD-1 Therapy in Non-Small Cell Lung Cancer by Increasing Tumor Infiltration of Regulatory T Cells

Immunotherapy resistance in non-small cell lung cancer (NSCLC) may be mediated by an immunosuppressive microenvironment, which can be shaped by the mutational landscape of the tumor. Here, we observed genetic alterations in the PTEN/PI3K/AKT/mTOR pathway and/or loss of PTEN expression in >25% of patients with NSCLC, with higher frequency in lung squamous carcinomas (LUSC). Patients with PTEN-low tumors had higher levels of PD-L1 and PD-L2 and showed worse progression-free survival when treated with immunotherapy. Development of a Pten-null LUSC mouse model revealed that tumors with PTEN loss were refractory to antiprogrammed cell death protein 1 (anti-PD-1), highly metastatic and fibrotic, and secreted TGFβ/CXCL10 to promote conversion of CD4+ lymphocytes into regulatory T cells (Treg). Human and mouse PTEN-low tumors were enriched in Tregs and expressed higher levels of immunosuppressive genes. Importantly, treatment of mice bearing Pten-null tumors with TLR agonists and anti-TGFβ antibody aimed to alter this immunosuppressive microenvironment and led to tumor rejection and immunologic memory in 100% of mice. These results demonstrate that lack of PTEN causes immunotherapy resistance in LUSCs by establishing an immunosuppressive tumor microenvironment that can be reversed therapeutically.

SIGNIFICANCE

PTEN loss leads to the development of an immunosuppressive microenvironment in lung cancer that confers resistance to anti-PD-1 therapy, which can be overcome by targeting PTEN loss-mediated immunosuppression.

Cancer Cell-Intrinsic Alterations Associated with an Immunosuppressive Tumor Microenvironment and Resistance to Immunotherapy in Lung Cancer

Despite the great clinical success of immunotherapy in lung cancer patients, only a small percentage of them (<40%) will benefit from this therapy alone or combined with other strategies. Cancer cell-intrinsic and cell-extrinsic mechanisms have been associated with a lack of response to immunotherapy. The present study is focused on cancer cell-intrinsic genetic, epigenetic, transcriptomic and metabolic alterations that reshape the tumor microenvironment (TME) and determine response or refractoriness to immune checkpoint inhibitors (ICIs). Mutations in KRAS, SKT11(LKB1), KEAP1 and TP53 and co-mutations of these genes are the main determinants of ICI response in non-small-cell lung cancer (NSCLC) patients. Recent insights into metabolic changes in cancer cells that impose restrictions on cytotoxic T cells and the efficacy of ICIs indicate that targeting such metabolic restrictions may favor therapeutic responses. Other emerging pathways for therapeutic interventions include epigenetic modulators and DNA damage repair (DDR) pathways, especially in small-cell lung cancer (SCLC). Therefore, the many potential pathways for enhancing the effect of ICIs suggest that, in a few years, we will have much more personalized medicine for lung cancer patients treated with immunotherapy. Such strategies could include vaccines and chimeric antigen receptor (CAR) cells.

Loss of BLK expression as a potential predictor of poor prognosis and immune checkpoint blockade response in NSCLC and contribute to tumor progression

BACKGROUND

Immune checkpoint blockade (ICB) has been proved to have significant anti-tumor effect in the clinical treatment of non-small cell lung cancer (NSCLC). Therefore, biomarkers predicting ICB response can provide better treatment for patients with NSCLC.

METHODS

Differential expression genes (DEGs) were identified by ImmuCellAI database. Copy number alteration (CNA) was analyzed by cBioPortal. The predicted efficiency of 4 genes on cancer immunotherapy was assessed by ROC analysis. The survival value of BLK was analyzed by Kaplan-Meier plotter and Prognoscan analysis. Clinical significance of BLK IHC-TMA score in NSCLC was also explored. The CCK-8 assay, wound healing assay, western blot assay in vitro and subcutaneous xenograft experiments in vivo were used for investigating the functions of BLK. The RNA-sequencing were performed to screen BLK regulated genes and conducted for GO/KEGG enrichment analysis. The transcriptional regulatory factor of BLK promoter region was predicted by ChIP-seq analysis.

RESULTS

39 common DEGs between ICB Response (R) group and No Response (NR) group with NSCLC were identified, in which the CNA frequency of BLK deletion (> 6%) was found. The predicted efficiency of BLK on immunotherapy was performed best in NSCLC (AUC>0.7). Low expression of BLK was related to NSCLC with significantly poor prognosis. BLK overexpression can inhibit growth of NSCLC via activating apoptosis pathway, inhibiting the G2M checkpoint and Glycolysis pathway. The enrichment analysis indicated that BLK regulated genes related to oncogenic potential in NSCLC. Besides, BLK expression was inhibited via H3K27me3 modification in A549 and H1299 cells. BLK mRNA level was negatively correlated with methylation and positively correlated with the tumor purity in NSCLC.

CONCLUSION

Our study provides strong evidence that low expression of BLK may serve as a biomarker for poor prognosis in NSCLC, while response to ICB therapy and contributes to NSCLC tumor progression.

APOBEC3-mediated mutagenesis in cancer: causes, clinical significance and therapeutic potential

Apolipoprotein B mRNA-editing enzyme, catalytic polypeptides (APOBECs) are cytosine deaminases involved in innate and adaptive immunity. However, some APOBEC family members can also deaminate host genomes to generate oncogenic mutations. The resulting mutations, primarily signatures 2 and 13, occur in many tumor types and are among the most common mutational signatures in cancer. This review summarizes the current evidence implicating APOBEC3s as major mutators and outlines the exogenous and endogenous triggers of APOBEC3 expression and mutational activity. The review also discusses how APOBEC3-mediated mutagenesis impacts tumor evolution through both mutagenic and non-mutagenic pathways, including by inducing driver mutations and modulating the tumor immune microenvironment. Moving from molecular biology to clinical outcomes, the review concludes by summarizing the divergent prognostic significance of APOBEC3s across cancer types and their therapeutic potential in the current and future clinical landscapes.

Integrated analysis of tertiary lymphoid structures in relation to tumor-infiltrating lymphocytes and patient survival in pancreatic ductal adenocarcinoma

BACKGROUND

Tertiary lymphoid structure (TLS) reflects an intense immune response against cancer, which correlates with favorable patient survival. However, the association of TLS with tumor-infiltrating lymphocytes (TILs) and clinical outcomes has not been investigated comprehensively in pancreatic ductal adenocarcinoma (PDAC).

METHODS

We utilized an integrative molecular pathological epidemiology database on 162 cases with resected PDAC, and examined TLS in relation to levels of TILs, patient survival, and treatment response. In whole-section slides, we assessed the formation of TLS and conducted immunohistochemistry for tumor-infiltrating T cells (CD4, CD8, CD45RO, and FOXP3). As confounding factors, we assessed alterations of four main driver genes (KRAS, TP53, CDKN2A [p16], and SMAD4) using next-generation sequencing and immunohistochemistry, and tumor CD274 (PD-L1) expression assessed by immunohistochemistry.

RESULTS

TLSs were found in 112 patients with PDAC (69.1%). TLS was associated with high levels of CD4⁺ TILs (multivariable odds ratio [OR], 3.50; 95% confidence interval [CI] 1.65-7.80; P = 0.0002), CD8⁺ TILs (multivariable OR, 11.0; 95% CI 4.57-29.7, P < 0.0001) and CD45RO⁺ TILs (multivariable OR, 2.65; 95% CI 1.25-5.80, P = 0.01), but not with levels of FOXP3⁺ TILs. TLS was associated with longer pancreatic cancer-specific survival (multivariable hazard ratio, 0.37; 95% CI 0.25-0.56, P < 0.0001) and favorable outcomes of adjuvant S-1-treatment. TLS was not associated with driver gene alterations but tumor CD274 negative expression.

CONCLUSIONS

Our comprehensive data supports the surrogacy of TLS for vigorous anti-tumor immune response characterized by high levels of helper and cytotoxic T cells and their prognostic role.

Progress on neoadjuvant immunotherapy in resectable non-small cell lung cancer and potential biomarkers

Immune checkpoint inhibitors (ICIs) are highly concerned in the treatment of non-small cell lung cancer (NSCLC), represented by inhibitors of programmed death protein 1 (PD-1) and its ligand (PD-L1), and inhibitors of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4). The introduction of immunotherapy in the treatment of perioperative NSCLC has improved the prognosis to a great extent, as demonstrated by several phase II and III clinical trials. The target population for immunotherapy in early-stage NSCLC is still under discussion, and the biomarkers for neoadjuvant immunotherapy population selection are the next pending problem. The predictive efficacy of many potential makers is still being explored, including PD-L1 expression levels, tumor mutation burden, circulating tumor DNA, components of the tumor microenvironment, and several clinical factors. We summarize key findings on the utility of ICIs in clinical trials of preoperative NSCLC patients and conclude analyses of relevant biomarkers to provide a better understanding of potentially predictive biomarkers in neoadjuvant immunotherapy.

Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies

The high primary resistance incidence and unavoidable secondary resistance are the major clinical obstacle to lasting long-term benefits in Non-small-cell lung cancer (NSCLC) patients treated with immunotherapy. The mechanisms of immunotherapy resistance in NSCLC are complex, mainly involving tumor cells and tumor microenvironment (TME) infiltrating immune cells, including TAMs, B cells, NK cells, and T cells. The selection of clinical strategies for NSCLC progression after immunotherapy resistance should depend on the progressive mode. The progression pattern of NSCLC patients after immunotherapy resistance can be divided into oligo-progression and systemic/multiple progression, which should be considered for further treatment selection. In the future, it needs to explore how to optimize the combined therapy and explore strategies to reprogram infiltrating immune cells under various genetic backgrounds of tumor cells and timely reshape TME during antitumor treatments.

Development and validation of a mutation-based model to predict immunotherapeutic efficacy in NSCLC

Background

Immunotherapy has become increasingly important in the perioperative period of non-small-cell lung cancer (NSCLC). In this study, we intended to develop a mutation-based model to predict the therapeutic effificacy of immune checkpoint inhibitors (ICIs) in patients with NSCLC.

Methods

Random Forest (RF) classifiers were generated to identify tumor gene mutated features associated with immunotherapy outcomes. Then the best classifier with the highest accuracy served for the development of the predictive model. The correlations of some reported biomarkers with the model were analyzed, such as TMB, PD-(L)1, KEAP1-driven co-mutations, and immune subtypes. The training cohort and validation cohorts performed survival analyses to estimate the predictive efficiency independently.

Results

An 18-gene set was selected using random forest (RF) classififiers. A predictive model was developed based on the number of mutant genes among the candidate genes, and patients were divided into the MT group (mutant gene ≥ 2) and WT group (mutant gene < 2). The MT group (N = 54) had better overall survival (OS) compared to the WT group (N = 290); the median OS was not reached vs. nine months (P < 0.0001, AUC = 0.73). The robust predictive performance was confifirmed in three validation cohorts, with an AUC of 0.70, 0.57, and 0.64 (P < 0.05). The MT group was characterized by high tumor neoantigen burden (TNB), increased immune infifiltration cells such as CD8 T and macrophage cells, and upregulated immune checkpoint molecules, suggesting potential biological advantages in ICIs therapy.

Conclusions

The predictive model could precisely predict the immunotherapeutic efficacy in NSCLC based on the mutant genes within the model. Furthermore, some immune-related features and cell expression could support robust efficiency.

Programmed Cell Death-Ligand 1 in Head and Neck Squamous Cell Carcinoma: Molecular Insights, Preclinical and Clinical Data, and Therapies

Aberrant expression of the programmed cell death protein ligand 1 (PD-L1) constitutes one of the main immune evasion mechanisms of cancer cells. The approval of drugs against the PD-1-PD-L1 axis has given new impetus to the chemo-therapy of many malignancies. We performed a literature review from 1992 to August 2022, summarizing evidence regarding molecular structures, physiological and pathological roles, mechanisms of PD-L1 overexpression, and immunotherapy evasion. Furthermore, we summarized the studies concerning head and neck squamous cell carcinomas (HNSCC) immunotherapy and the prospects for improving the associated outcomes, such as identifying treatment response biomarkers, new pharmacological combinations, and new molecules. PD-L1 overexpression can occur via four mechanisms: genetic modifications; inflammatory signaling; oncogenic pathways; microRNA or protein-level regulation. Four molecular mechanisms of resistance to immunotherapy have been identified: tumor cell adaptation; changes in T-cell function or proliferation; alterations of the tumor microenvironment; alternative immunological checkpoints. Immunotherapy was indeed shown to be superior to traditional chemotherapy in locally advanced/recurrent/metastatic HNSCC treatments.

APOBEC3: Friend or Foe in Human Papillomavirus Infection and Oncogenesis?

Human papillomavirus (HPV) infection is a causative agent of multiple human cancers, including cervical and head and neck cancers. In these HPV-positive tumors, somatic mutations are caused by aberrant activation of DNA mutators such as members of the apolipoprotein B messenger RNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) family of cytidine deaminases. APOBEC3 proteins are most notable for their restriction of various viruses, including anti-HPV activity. However, the potential role of APOBEC3 proteins in HPV-induced cancer progression has recently garnered significant attention. Ongoing research stems from the observations that elevated APOBEC3 expression is driven by HPV oncogene expression and that APOBEC3 activity is likely a significant contributor to somatic mutagenesis in HPV-positive cancers. This review focuses on recent advances in the study of APOBEC3 proteins and their roles in HPV infection and HPV-driven oncogenesis. Further, we discuss critical gaps and unanswered questions in our understanding of APOBEC3 in virus-associated cancers.

Integrated multi-omics characterization of KRAS mutant colorectal cancer

KRAS mutation is the most frequent oncogenic aberration in colorectal cancer (CRC). The molecular mechanism and clinical implications of KRAS mutation in CRC remain unclear and show high heterogeneity within these tumors. Methods: We harnessed the multi-omics data (genomic, transcriptomic, proteomic, and phosphoproteomic etc.) of KRAS-mutant CRC tumors and performed unsupervised clustering to identify proteomics-based subgroups and molecular characterization. Results: In-depth analysis of the tumor microenvironment by single-cell transcriptomic revealed the cellular landscape of KRAS-mutant CRC tumors and identified the specific cell subsets with KRAS mutation. Integrated multi-omics analyses separated the KRAS-mutant tumors into two distinct molecular subtypes, termed KRAS-M1 (KM1) and KRAS-M2 (KM2). The two subtypes had a similar distribution of mutated residues in KRAS (G12D/V/C etc.) but were characterized by distinct features in terms of prognosis, genetic alterations, microenvironment dysregulation, biological phenotype, and potential therapeutic approaches. Proteogenomic analyses revealed that the EMT, TGF-β and angiogenesis pathways were enriched in the KM2 subtype and that the KM2 subtype was associated with the mesenchymal phenotype-related CMS4 subtype, which indicated stromal invasion and worse prognosis. The KM1 subtype was characterized predominantly by activation of the cell cycle, E2F and RNA transcription and was associated with the chromosomal instability (CIN)-related ProS-E proteomic subtype, which suggested cyclin-dependent features and better survival outcomes. Moreover, drug sensitivity analyses based on three compound databases revealed subgroup-specific agents for KM1 and KM2 tumors. Conclusions: This study clarifies the molecular heterogeneity of KRAS-mutant CRC and reveals new biological subtypes and therapeutic possibilities for these tumors.

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.

Pan-Cancer Analysis for Immune Cell Infiltration and Mutational Signatures Using Non-Negative Canonical Correlation Analysis

Mutational signatures indicate the mutational processes and substitution patterns in cancer cell genomes. However, the functional consequences of mutational signatures remain unclear, and there have been no comprehensive systematic studies to examine the relationships between the mutational signatures and the immune cell infiltration. Here, the relationship between mutational signatures and immune cell infiltration using non-negative canonical correlation analysis based on 8927 patients across 25 tumor types was investigated. By inspecting mutational signatures with the maximal coefficients determined by the non-negative canonical correlation analysis, the study identified mutational signatures related to immune cell infiltration composed of tumor microenvironments. The analysis was validated by showing that the genes associated with the identified mutational signatures were linked to overall survival by a Kaplan–Meier curve and a log-rank test and were mainly related to immunity by gene set enrichment analysis. These results will help expand our knowledge of tumor biology and recognize the functional roles and associations of immune systems with mutational signatures.

Integrated Bioinformatic Analysis of DNA Methylation and Immune Infiltration in Endometrial Cancer

Background

Endometrial cancer greatly threatens the health of female. Emerging evidences have demonstrated that DNA methylation and immune infiltration are involved in the occurrence and development of endometrial cancer. However, the mechanism and prognostic biomarkers of endometrial cancer are still unclear. In this study, we assess DNA methylation and immune infiltration via bioinformatic analysis.

Methods

The latest RNA-Seq, DNA methylation data, and clinical data related to endometrial cancer were downloaded from the UCSC Xena dataset. The methylation-driven genes were selected, and then the risk score was obtained using “MethylMix” and “corrplot” R packages. The connection between methylated genes and the expression of screened driven genes were explored using “survminer” and “beeswarm” packages, respectively. Finally, the role of VTCN1in immune infiltration was analyzed using “CIBERSORT” package.

Results

In this study, 179 upregulated genes, and 311 downregulated genes were identified and found to be related to extracellular matrix organization, cell–cell junctions, and cell adhesion molecular binding. The methylation-driven gene VTCN1 was selected, and patients classified to the hypomethylation and high expression group displayed poor prognosis. The VTCN1 gene exhibited highest correlation coefficient between methylation and expression. More importantly, the hypomethylation of promoter of VTCN1 led to its high expression, thereby induce tumor development by inhibiting CD8+ T cell infiltration.

Conclusions

Overall, our study was the first to reveal the mechanism of endometrial cancer by assessing DNA methylation and immune infiltration via integrated bioinformatic analysis. In addition, we found a pivotal prognostic biomarker for the disease. Our study provides potential targets for the diagnosis and prognosis of endometrial cancer in the future.

Proteomic characterization of a candidate polygenic driver of metabolism in non-small cell lung cancer

Proteome analysis revealed signatures of co-expressed upregulated metabolism proteins highly conserved between primary and non-small cell lung cancer (NSCLC) patient-derived xenograft tumors (Li et al. 2014, Nat. Communications 5:5469). The C10 signature is encoded by seven genes (ADSS, ATP2A2, CTPS1, IMPDH2, PKM2, PTGES3, SGPL1) and DNA alterations in C10-encoding genes are associated with longer survival in a subset of NSCLC. To explore the C10 signature as an oncogenic driver and address potential mechanisms of action, C10 protein expression and protein-protein interactions were determined. In independent NSCLC cohorts, the coordinated expression of C10 proteins was significant and mutations in C10 genes were associated with better outcome. Affinity purification-mass spectrometry and in vivo proximity-based biotin identification defined a C10 interactome involving 667 proteins including candidate drug targets and clusters associated with glycolysis, calcium homeostasis, and nucleotide and sphingolipid metabolism. DNA alterations in genes encoding C10 interactome components were also found to be associated with better survival. These data support the notion that the coordinated upregulation of the C10 signature impinges metabolic processes that collectively function as an oncogenic driver in NSCLC.

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.

An overview of mutational and copy number signatures in human cancer

The genome of each cell in the human body is constantly under assault from a plethora of exogenous and endogenous processes that can damage DNA. If not successfully repaired, DNA damage generally becomes permanently imprinted in cells, and all their progenies, as somatic mutations. In most cases, the patterns of these somatic mutations contain the tell‐tale signs of the mutagenic processes that have imprinted and are termed mutational signatures. Recent pan‐cancer genomic analyses have elucidated the compendium of mutational signatures for all types of small mutational events, including (1) single base substitutions, (2) doublet base substitutions, and (3) small insertions/deletions. In contrast to small mutational events, where, in most cases, DNA damage is a prerequisite, aneuploidy, which refers to the abnormal number of chromosomes in a cell, usually develops from mistakes during DNA replication. Such mistakes include DNA replication stress, mitotic errors caused by faulty microtubule dynamics, or cohesion defects that contribute to chromosomal breakage and can lead to copy number (CN) alterations (CNAs) or even to structural rearrangements. These aberrations also leave behind genomic scars which can be inferred from sequencing as CN signatures and rearrangement signatures. The analyses of mutational signatures of small mutational events have been extensively reviewed, so we will not comprehensively re‐examine them here. Rather, our focus will be on summarising the existing knowledge for mutational signatures of CNAs. As studying CN signatures is an emerging field, we briefly summarise the utility that mutational signatures of small mutational events have provided in basic science, cancer treatment, and cancer prevention, and we emphasise the future role that CN signatures may play in each of these fields. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Roles of PTEN inactivation and PD-1/PD-L1 activation in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer in China and developing countries. The purpose of this review is to summarize the roles of inactivation of the tumor suppressor gene, phosphatase and tensin homolog (PTEN), and activation of the programmed cell death protein 1 (PD-1) upon binding to its ligand (PD-L1) in the promotion of ESCC. Studies of ESCC performed in vitro and in vivo indicated that PTEN and PD-L1 function in the regulation of cell proliferation, invasion, and migration; the epithelial-mesenchymal transition; resistance to chemotherapy and radiotherapy; and the PI3K/AKT signaling pathway. Certain genetic variants of PTEN are related to susceptibility to ESCC, and PTEN and PD-L1 also function in ESCC progression and affect the prognosis of patients with ESCC. There is also evidence that the expression of PD-L1 and PTEN are associated with the progression of certain other cancers. Future studies should further examine the relationship of PD-L1 and PTEN and their possible interactions in ESCC.

Implications of genetic heterogeneity in hepatocellular cancer

Hepatocellular carcinoma (HCC) exhibits a remarkable degree of heterogeneity, not only at an inter-patient level but also between and within tumors in the same patient. The advent of next-generation sequencing (NGS)-based technologies has allowed the creation of high-resolution atlases of HCC. This review outlines recent findings from genomic, epigenomic, transcriptomic, and proteomic sequencing that have yielded valuable insights into the spatial and temporal heterogeneity of HCC. The high heterogeneity of HCC has both clinical and therapeutic implications. The challenges in prospectively validating molecular classifications for HCC either for prognostication or for prediction of therapeutic response are partly due to the immense heterogeneity in HCC. Moreover, the heterogeneity of HCC tumors combined with the lack of commonly mutated, druggable targets severely limits treatment options for HCC. Recently, immune checkpoint inhibitors and combination therapies have shown promise for advanced HCC, while T cell therapies and vaccines are currently being investigated. Yet, immunotherapies show benefit only in a limited subset of patients, making it imperative to decipher tumor heterogeneity in HCC in order to enable optimal patient selection. This review summarizes the cutting-edge research on heterogeneity in HCC and explores the implications of heterogeneity on stratifying patients and developing biomarkers and therapies for HCC.

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.

Metabolic syndrome related gene signature predicts the prognosis of patients with pancreatic ductal carcinoma. A novel link between metabolic dysregulation and pancreatic ductal carcinoma

Background

Pancreatic cancer is one of the most common malignancies worldwide. In recent years, specific metabolic activities, which involves the development of tumor, caused wide public concern. In this study, we wish to explore the correlation between metabolism and progression of tumor.

Methods

A retrospective analysis including 95 patients with pancreatic ductal adenocarcinoma (PDAC) and PDAC patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and The Gene Expression Omnibus (GEO) database were involved in our study. Multivariate Cox regression analysis was used to construct the prognosis model. The potential connection between metabolism and immunity of PDAC was investigated through a weighted gene co-expression network analysis (WGCNA). 22 types of Tumor-infiltrating immune cells (TIICs) between high-risk and low-risk groups were estimated through CIBERSORT. Moreover, the potential immune-related signaling pathways between high-risk and low-risk groups were explored through the gene set enrichment analysis (GSEA). The role of key gene GMPS in developing pancreatic tumor was further investigated through CCK-8, colony-information, and Transwell.

Results

The prognostic value of the MetS factors was analyzed using the Cox regression model, and a clinical MetS-based nomogram was established. Then, we established a metabolism-related signature to predict the prognosis of PDAC patients based on the TCGA databases and was validated in the ICGC database and the GEO database to find the distinct molecular mechanism of MetS genes in PDAC. The result of WGCNA showed that the blue module was associated with risk score, and genes in the blue module were found to be enriched in the immune-related signaling pathway. Furthermore, the result of CIBERSORT demonstrated that proportions of T cells CD8, T cells Regulatory, Tregs NK cells Activated, Dendritic cells Activated, and Mast cells Resting were different between high-risk and low-risk groups. These differences are potential causes of different prognoses of PDAC patients. GSEA and the protein–protein interaction network (PPI) further revealed that our metabolism-related signature was significantly enriched in immune‐related biological processes. Moreover, knockdown of GMPS in PDAC cells suppressed proliferation, migration, and invasion of tumor cells, whereas overexpression of GMPS performed oppositely.

Conclusion

The results shine light on fundamental mechanisms of metabolic genes on PDAC and establish a reliable and referable signature to evaluate the prognosis of PDAC. GMPS was identified as a potential candidate oncogene with in PDAC, which can be a novel biomarker and therapeutic target for PDAC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02378-w.

Comprehensive Analysis of m6A Regulators Characterized by the Immune Cell Infiltration in Head and Neck Squamous Cell Carcinoma to Aid Immunotherapy and Chemotherapy

Background

N6-Methyladenosine (m⁶A), which is a prevalent regulator of mRNA expression, has gathered increasing study interests. Though the role of m⁶A as being important in many biological processes (such as growth and proliferation of cancers) has been well documented, its potential role in tumor immune microenvironment (TIME) has rarely been analyzed.

Methods

We downloaded RNA expression, single nucleotide polymorphism (SNP), and copy number variation (CNV) data from The Cancer Genome Atlas (TCGA). We then curated 21 m⁶A regulators and clustered patients into three m⁶A subtypes and m⁶A-related gene subtypes and compared them based on overall survival (OS). The combination of CIBERSORT as well as ssGSEA quantified the infiltration levels of immune cells and immune-related functions. The m⁶A scores were determined by using principal component analysis (PCA) algorithm. Furthermore, we evaluate the correlation of m⁶A regulators with immune and response to therapy.

Results

Three m⁶A clusters were identified based on the TCGA-HNSCC cohort, and there were significant associations among them in overall outcomes and caner-related pathways. We found that three m⁶A clusters were consistent with three phenotypes: immune-inflamed, immune-dessert, and immune-excluded. HNSCC patients were divided into high– and low–m⁶A score groups based on the cutoff of m⁶A score. Patients with lower m⁶A score had better overall survival outcome. Further analysis indicated that patients with higher m⁶A score presented higher tumor mutation burden (TMB). In addition, patients in low–m⁶A score subgroup had high chemotherapeutics sensitivity. GEO cohort confirmed patients with low m⁶A score demonstrated significant overall survival advantages and clinical benefits. Low m⁶A score carry an increased neoantigen load, eliciting a response to immunotherapy, and its value in predicting survival outcomes of immunotherapy was also confirmed in three anti-PD-1 cohorts.

Conclusions

Our study demonstrated that m⁶A regulators are closely related to TIME and the m⁶A score was an effective prognostic biomarker and predictive indicator for immunotherapy and chemotherapeutics. Comprehensive evaluation of m⁶A regulators in tumors will extend our understanding of TIME and effectively guide increasing study investigations on immunotherapy and chemotherapy strategies for HNSCC.

Mutational signature analysis in non-small cell lung cancer patients with a high tumor mutational burden

BACKGROUND

Lung cancer is the leading cause of cancer death worldwide. With the growing number of targeted therapies and the introduction of immuno-oncology (IO), personalized medicine has become standard of care in patients with metastatic disease. The development of predictive and prognostic biomarkers is of great importance. Mutational signatures harbor potential clinical value as predictors of therapy response in cancer. Here we set out to investigate particular mutational processes by assessing mutational signatures and associations with clinical features, tumor mutational burden (TMB) and targetable mutations.

METHODS

In this retrospective study, we studied tumor DNA from patients with non-small cell lung cancer (NSCLC) irrespective of stage. The samples were sequenced using a 2 megabase (Mb) gene panel. On each sample TMB was determined and defined as the total number of single nucleotide mutations per Mb (mut/Mb) including non-synonymous mutations. Mutational signature profiling was performed on tumor samples in which at least 30 somatic single base substitutions (SBS) were detected.

RESULTS

In total 195 samples were sequenced. Median total TMB was 10.3 mut/Mb (range 0-109.3). Mutational signatures were evaluated in 76 tumor samples (39%; median TMB 15.2 mut/Mb). SBS signature 4 (SBS4), associated with tobacco smoking, was prominently present in 25 of 76 samples (33%). SBS2 and/or SBS13, both associated with activity of the AID/APOBEC family of cytidine deaminases, were observed in 11 of 76 samples (14%). SBS4 was significantly more present in early stages (I and II) versus advanced stages (III and IV; P = .005).

CONCLUSION

In a large proportion of NSCLC patients tissue panel sequencing with a 2 Mb panel can be used to determine the mutational signatures. In general, mutational signature SBS4 was more often found in early versus advanced stages of NSCLC. Further studies are needed to determine the clinical utility of mutational signature analyses.

A Systematic Analysis Identifies Key Regulators Involved in Cell Proliferation and Potential Drugs for the Treatment of Human Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common and malignant cancer types. Abnormal cell proliferation, exemplified by cell cycle and cell division dysregulation, is one of the most prominent hallmarks of cancer and is responsible for recurrence, metastasis, and resistance to cancer therapy. However, LUAD-specific gene regulation and clinical significance remain obscure. Here, by using both tissues and cells from LUAD and normal lung samples, 434 increased and 828 decreased genes of biological significance were detected, including 127 cell cycle-associated genes (95 increased and 32 decreased), 66 cell division-associated genes (56 increased and 10 decreased), and 81 cell proliferation-associated genes (34 increased and 47 decreased). Among them, 12 increased genes (TPX2, CENPF, BUB1, PLK1, KIF2C, AURKB, CDKN3, BUB1B, HMGA2, CDK1, ASPM, and CKS1B) and 2 decreased genes (TACC1 and MYH10) were associated with all the three above processes. Importantly, 2 (CDKN3 and CKS1B) out of the 11 increased genes (except HMGA2) are previously uncharacterized ones in LUAD and can potentially be prognostic markers. Moreover, PLK1 could be a promising therapeutic target for LUAD. Besides, protein–protein interaction network analysis showed that CDK1 and CDC20 were the hub genes, which might play crucial roles in cell proliferation of LUAD. Furthermore, transcriptional regulatory network analysis suggested that the transcription factor E2F1 could be a key regulator in controlling cell proliferation of LUAD via expression modulation of most cell cycle-, cell division-, and cell proliferation-related DEGs. Finally, trichostatin A, hycanthone, vorinostat, and mebeverine were identified as four potential therapeutic agents for LUAD. This work revealed key regulators contributing to cell proliferation in human LUAD and identified four potential therapeutic agents for treatment strategy.

Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma

Urothelial cancer (UC) is one of the common refractory tumors and chemotherapy is the primary treatment for it. The advent of immune checkpoint inhibitors (ICI) has facilitated the development of treatment strategies for UC patients. To screen out UC patients sensitive to ICI, researchers have proposed that PD-L1, tumor mutation burden and TCGA molecular subtypes can be used as predictors of ICI efficacy. However, the performance of these predictors needs further validation. We need to identify novel biomarkers to screen out UC patients sensitive to ICI. In our study, we collected the data of two clinical cohorts: the ICI cohort and the TCGA cohort. The result of the multivariate Cox regression analysis showed that glycogen metabolism score (GMS) (HR = 1.26, p = 0.017) was the negative predictor of prognosis for UC patients receiving ICI treatment. Low-GMS patients had a higher proportion of patients achieving complete response or partial response to ICI. After the comparison of gene mutation status between high-GMS and low-GMS patients, we identified six genes with significant differences in mutation frequencies, which may provide new directions for potential drug targets. Moreover, we analyzed the immune infiltration status and immune-related genes expression between high-GMS and low-GMS patients. A reduced proportion of tumor-associated fibroblasts and elevated proportion of CD8⁺ T cells can be observed in low-GMS patients while several immunosuppressive molecules were elevated in the high-GMS patients. Using the sequencing data of the GSE164042 dataset, we also found that myeloid-derived suppressor cell and neutrophil related signature scores were lower in α-glucosidase knockout bladder carcinoma cells when compared to the control group. In addition, angiogenesis, classic carcinogenic pathways, immunosuppressive cells related pathways and immunosuppressive cytokine secretion were mainly enriched in high-GMS patients and cell samples from the control group. Finally, we suspected that the combination treatment of ICI and histone deacetylase inhibitors may achieve better clinical responses in UC patients based on the analysis of drug sensitivity data. In conclusion, our study revealed the predictive value of GMS for ICI efficacy of UC patients, providing a novel perspective for the exploration of new drug targets and potential treatment strategies.

NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images

Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.

The association between the incidence risk of pneumonitis and PD-1/PD-L1 inhibitors in advanced NSCLC: A meta-analysis of randomized controlled trials

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have shown a significant efficacy for patients with non-small cell lung cancer (NSCLC). However, checkpoint inhibitor pneumonitis (CIP) is a rare but severe and life-threatening adverse event. Hence, we performed a systematic review and meta-analysis to evaluate the incidence and risk of CIP in patients with NSCLC.

METHODS

Pubmed, Embase, Cochrane Library and ClinicalTrials.gov (http://clinicaltrials.gov/) were searched up to December 15, 2020. Studies regarding all-grade and high-grade pneumonitis were included. The data was analyzed using meta-packages of R 3.6.0.

RESULTS

A total of sixteen randomized controlled trials including 9500 patients were identified for further evaluation. The overall incidence of all-grade and high-grade CIP was 4.17% and 2.02%, respectively. Compared with conventional chemotherapy, patients treated with ICIs significantly increased risk of all-grade (RR: 4.11, p < 0.0001) and high-grade (RR: 3.16, p < 0.0001) pneumonitis. Subgroup analysis showed the ICIs combined with chemotherapy was associated with a higher incidence of CIP than monotherapy alone (6.03% vs 3.32%, p = 0.01). And the rate of death owing to CIP was higher than chemotherapy-mediated pneumonitis.

CONCLUSION

There were a higher incidence and risk of pneumonitis with the application of ICIs when compared with chemotherapy. Higher mortality rate of pneumonitis was more frequent in ICIs group. Thus, early detection, proper administration and optimal management are needed for physicians prevent potentially CIP deterioration.

Anti-PD-1 and Anti-PD-L1 in Head and Neck Cancer: A Network Meta-Analysis

Objective

The monoclonal antibodies anti-programmed death protein-1 (anti-PD-1) nivolumab and pembrolizumab are the first immune checkpoint inhibitors (ICIs) approved for treatment of recurrent/metastatic head and neck carcinoma R/M HNSCC in first line and in platinum refractory disease. This network meta-analysis aims to investigate the efficacy of anti-PD-1- vs anti-PD-L1-based therapy in R/M HNSCC cancer patients through a systematic review of the literature to provide support for evidence-based treatment decisions. In particular, the effectiveness of ICIs for R/M HNSCC is analyzed according to the different mechanisms of action of the check-points inhibitory drugs in different subgroups of patients.

Methods

We did a systematic literature review and network meta-analysis (NMA) of randomized controlled trials (RCTs) in PubMed, ClinicalTrials.gov, Embase, Medline, the Cochrane Central Register of Controlled Trials, Web of Science. Our search identified a total of five randomized controlled trials: Keynote 040, Keynote 048, Eagle, Condor, Checkmate 141. These trials included 3001 patients. Treatment was sub-categorized into PD-L1-based, PD-1-based, and standard chemotherapy. Treatments were indirectly compared with anti-PD-L1-based therapy.

Results

The network meta-analysis demonstrated no significant differences in OS between different subgroups except for the metastatic patients in which anti-PD-1-based therapy was associated with significantly less risk of death. Furthermore, anti-PD-1-based therapy appeared to be effective in smoker patients and in human papilloma-negative (HPV) patients. Conversely, anti-PD-L1-based therapy seems to be better efficient in female patients, in locally recurrent setting and in HPV positive patients.

Conclusion

This is the first NMA study that aimed to indirectly compare anti-PD-1- and anti-PD-L1-based therapy in HNSCC patients. The results of our NMA could help define a profile of patient responder or resistant to specific classes of immune drugs and can be used to guide/design future studies in the novel scenario of precision immune-oncology.

Identification of uterine leiomyosarcoma-associated hub genes and immune cell infiltration pattern using weighted co-expression network analysis and CIBERSORT algorithm

BACKGROUND

While large-scale genomic analyses symbolize a precious attempt to decipher the molecular foundation of uterine leiomyosarcoma (ULMS), bioinformatics results associated with the occurrence of ULMS based totally on WGCNA and CIBERSORT have not yet been reported. This study aimed to screen the hub genes and the immune cell infiltration pattern in ULMS by bioinformatics methods.

METHODS

Firstly, the GSE67463 dataset, including 25 ULMS tissues and 29 normal myometrium (NL) tissues, was downloaded from the public database. The differentially expressed genes (DEGs) were screened by the 'limma' package and hub modules were identified by weighted gene co-expression network analysis (WGCNA). Subsequently, gene function annotations were performed to investigate the biological role of the genes from the intersection of two groups (hub module and DEGs). The above genes were calculated in the protein-protein interaction (PPI) network to select the hub genes further. The hub genes were validated using external data (GSE764 and GSE68295). In addition, the differential immune cell infiltration between UL and ULMS tissues was investigated using the CIBERSORT algorithm. Finally, we used western blot to preliminarily detect the hub genes in cell lines.

RESULTS

WGCNA analysis revealed a green-yellow module possessed the highest correlation with ULMS, including 1063 genes. A total of 172 DEGs were selected by thresholds set in the 'limma' package. The above two groups of genes were intersected to obtain 72 genes for functional annotation analysis. Interestingly, it indicated that 72 genes were mainly involved in immune processes and the Neddylation pathway. We found a higher infiltration of five types of cells (memory B cells, M0-type macrophages, mast cells activated, M1-type macrophages, and T cells follicular helper) in ULMS tissues than NL tissues, while the infiltration of two types of cells (NK cells activated and mast cells resting) was lower than in NL tissues. In addition, a total of five genes (KDR, CCL21, SELP, DPT, and DCN) were identified as the hub genes. Internal and external validation demonstrated that the five genes were over-expressed in NL tissues compared with USML tissues. Finally, the correlation analysis results indicate that NK cells activated and mast cells activated positively correlated with the hub genes. However, M1-type macrophages had a negative correlation with the hub genes. Moreover, only the DCN may be associated with the Neddylation pathway.

CONCLUSION

A series of evidence confirm that the five hub genes and the infiltration of seven types of immune cells are related to USML occurrence. These hub genes may affect the occurrence of USML through immune-related and Neddylation pathways, providing molecular evidence for the treatment of USML in the future.

Immunotherapy against programmed death-1/programmed death ligand 1 in hepatocellular carcinoma: Importance of molecular variations, cellular heterogeneity, and cancer stem cells

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy related to diverse etiological factors. Different oncogenic mechanisms and genetic variations lead to multiple HCC molecular classifications. Recently, an immune-based strategy using immune checkpoint inhibitors (ICIs) was presented in HCC therapy, especially with ICIs against the programmed death-1 (PD-1) and its ligand PD-L1. However, despite the success of anti-PD-1/PD-L1 in other cancers, a substantial proportion of HCC patients fail to respond. In this review, we gather current information on biomarkers of anti-PD-1/PD-L1 treatment and the contribution of HCC heterogeneity and hepatic cancer stem cells (CSCs). Genetic variations of PD-1 and PD-L1 are associated with chronic liver disease and progression to cancer. PD-L1 expression in tumoral tissues is differentially expressed in CSCs, particularly in those with a close association with the tumor microenvironment. This information will be beneficial for the selection of patients and the management of the ICIs against PD-1/PD-L1.

The Emerging Importance of Tumor Genomics in Operable Non-Small Cell Lung Cancer

During the last two decades, next-generation sequencing (NGS) has played a key role in enhancing non-small cell lung cancer treatment paradigms through the application of "targeted therapy" in advanced and metastatic disease. The use of specific tyrosine kinase inhibitors in patients with oncogenic driver alterations, such as EGFR, ALK, ROS1, BRAF V600E, MET, and NTRK mutations, among others, has changed treatment approaches and improved outcomes in patients with late-stage disease. Although NGS technology has mostly been used in the setting of systemic therapy to identify targets, response to therapy, and mechanisms of resistance, it has multiple potential applications for patients with earlier-stage disease, as well. In this review, we discuss the emerging role of NGS technologies to better understand tumor biology in patients with non-small cell lung cancer who are undergoing surgery with curative intent. In this patient cohort, we examine tumor heterogeneity, the underlying tumor genomics associated with lung adenocarcinoma subtypes, the prediction of recurrence after complete surgical resection, the use of plasma circulating tumor DNA for detection of early cancers and monitoring for minimal residual disease, the differentiation of separate primaries from intrapulmonary metastases, and the use of NGS to guide induction and adjuvant therapies.

Targeting Metastatic Colorectal Cancer with Immune Oncological Therapies

Metastatic colorectal cancer carries poor prognosis, and current therapeutic regimes convey limited improvements in survival and high rates of detrimental side effects in patients that may not stand to benefit. Immunotherapy has revolutionised cancer treatment by restoring antitumoural mechanisms. However, the efficacy in metastatic colorectal cancer, is limited. A literature search was performed using Pubmed (Medline), Web of Knowledge, and Embase. Search terms included combinations of immunotherapy and metastatic colorectal cancer, primarily focusing on clinical trials in humans. Analysis of these studies included status of MMR/MSS, presence of combination strategies, and disease control rate and median overall survival. Evidence shows that immune checkpoint inhibitors, such as anti-PD1 and anti-PD-L1, show efficacy in less than 10% of patients with microsatellite stable, MMR proficient colorectal cancer. In the small subset of patients with microsatellite unstable, MMR deficient cancers, response rates were 40-50%. Combination strategies with immunotherapy are under investigation but have not yet restored antitumoural mechanisms to permit durable disease regression. Immunotherapy provides the potential to offer additional strategies to established chemotherapeutic regimes in metastatic colorectal cancer. Further research needs to establish which adjuncts to immune checkpoint inhibition can unpick resistance, and better predict which patients are likely to respond to individualised therapies to not just improve response rates but to temper unwarranted side effects.

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

A patient's response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

Identification of a Competing Endogenous RNA Network Related to Immune Signature in Lung Adenocarcinoma

Background

The establishment of immunotherapy has led to a new era in oncotherapy. But the signature of immune-related genes (IRGs) in LUAD remains to be elucidated. Here we use integrated analysis to identify IRGs roles in immune signature and detect their relationship with competing endogenous RNA (ceRNA) networks in LUAD progression.

Methods

By analyzing the RNA-seq data from different platforms, we recognized the differentially expressed genes (DEGs) of each platform and screened out the top 20 hub IRGs related to immune responses. Then, we applied the CIBERSORT algorithm to explore the landscape of tumor-infiltrating immune cells (TILs) in LUAD and their connection with hub genes. Next, we predicted and validated the upstream miRNAs and lncRNAs according to their expression and prognostic roles. Finally, we constructed and validated an immune-related ceRNA network by co-expression analysis.

Results

A total of 71 IRGs were identified among 248 DEGs, which play key roles in immune responses. CIBERSORT analysis showed that six hub genes were closely related to TILs, such as SPP1 and naive B cells (R = −0.17), TEK and resting mast cells (R = 0.37). Stepwise prediction and validation from mRNA to lncRNA, including 6 hub genes, 5 miRNAs, and 9 lncRNAs, were applied to construct a ceRNA network. Ultimately, we confirmed the TMPO-AS1/miR-126-5p/SPP1 and CARD8-AS1/miR-21-5p/TEK as immune-related ceRNA networks in LUAD progression.

Conclusion

We elucidated two immune-related ceRNA networks in LUAD progression, which can be considered as immunotherapy targets for this disease.

Evaluation of 30 DNA damage response and 6 mismatch repair gene mutations as biomarkers for immunotherapy outcomes across multiple solid tumor types

OBJECTIVE

DNA damage response (DDR) genes have low mutation rates, which may restrict their clinical applications in predicting the outcomes of immune checkpoint inhibitor (ICI) treatment. Thus, a systemic analysis of multiple DDR genes is needed to identify potential biomarkers of ICI efficacy.

METHODS

A total of 39,631 patients with mutation data were selected from the cBioPortal database. A total of 155 patients with mutation data were obtained from the Fudan University Shanghai Cancer Center (FUSCC). A total of 1,660 patients from the MSK-IMPACT cohort who underwent ICI treatment were selected for survival analysis. A total of 249 patients who underwent ICI treatment from the Dana-Farber Cancer Institute (DFCI) cohort were obtained from a published dataset. The Cancer Genome Atlas (TCGA) level 3 RNA-Seq version 2 RSEM data for gastric cancer were downloaded from cBioPortal.

RESULTS

Six MMR and 30 DDR genes were included in this study. Six MMR and 20 DDR gene mutations were found to predict the therapeutic efficacy of ICI, and most of them predicted the therapeutic efficacy of ICI, in a manner dependent on TMB, except for 4 combined DDR gene mutations, which were associated with the therapeutic efficacy of ICI independently of the TMB. Single MMR/DDR genes showed low mutation rates; however, the mutation rate of all the MMR/DDR genes associated with the therapeutic efficacy of ICI was relatively high, reaching 10%-30% in several cancer types.

CONCLUSIONS

Coanalysis of multiple MMR/DDR mutations aids in selecting patients who are potential candidates for immunotherapy.

Effect of Sintilimab combined with Chemotherapy on Tumor Markers and Immune Function of advanced non-small cell lung cancer

Objective

To evaluate the effect of sintilimab combined with chemotherapy on tumor markers and immune function in advanced non-small cell lung cancer.

Methods

The study was conducted at Xi'an Medical University, China. The 120 patients with advanced NSCLC who were treated in our hospital from January 2016 to January 2020 were randomly divided into two groups, with 60 cases in each group. Patients in the control group received conventional GP chemotherapy, while those in the experimental group received intravenous injection of sindilimab on the basis of conventional GP chemotherapy. The changes of serum tumor markers CYFRA211, CEA, CA125 and T lymphocyte subsets CD3+, CD4+, CD8+, CD4+/CD8+ in the two groups prior to and after treatment were compared and analyzed. At the same time, the clinical efficacy at six months was compared between the two groups.

Results

The serum tumor markers CYFRA211, CEA and CA125 in the two groups after treatment were lower than those before treatment, and the difference was statistically significant (P=0.00). Specifically, the above-mentioned markers in the experimental group decreased more significantly than those in the control group, and the difference was statistically significant (CYFRA211, CA125, p=0.00; CEA, p=0.01; the levels of CD3+ and CD4+ in the experimental group were higher than those in the control group after treatment, with statistical significance (CD3+, p=0.00; CD4+, p=0.01)). No significant change can be seen in CD8+ (p=0.14), and the level of CD4+/CD8+ in the experimental group was higher than that in the control group, with a significant difference (p=0.02). The complete remission rate (CR) was 22% in the experimental group and 8% in the control group (P=0.04), which was statistically significant. The progress rate (PD) of the experimental group was significantly lower than that of the control group, with statistical significance (p=0.02). The overall response rate (RR) of the experimental group was more advantageous than that of the control group, with a statistically significant difference (p=0.01).

Conclusion

Compared with chemotherapy alone, significant therapeutic effects can be obtained in the treatment of advanced non-small cell lung cancer with sintilimab combined with chemotherapy. With this combination regimen, the level of serum tumor markers can be significantly reduced, the cellular immune function of patients can be improved, with the overall response rate of treatment increased, and the risk of progressive disease of patients reduced.

Next-Generation Sequencing Reveals High Uncommon EGFR Mutations and Tumour Mutation Burden in a Subgroup of Lung Cancer Patients

Xuanwei County in Southwest China shows the highest incidence and mortality rate of lung cancer in China. Although studies have reported distinct clinical characteristics of patients from Xuanwei, the molecular features of these patients with non-small cell lung cancer (NSCLC) remain unclear. Here, we comprehensively characterised such cases using next-generation sequencing (NGS). Formalin-fixed, paraffin-embedded tumour samples from 146 patients from Xuanwei with NSCLC were collected for an NGS-based target panel assay; their features were compared with those of reference Chinese and The Cancer Genome Atlas (TCGA) cohorts. Uncommon EGFR mutations, defined as mutations other than L858R, exon 19del, exon 20ins, and T790M, were the predominant type of EGFR mutations in the Xuanwei cohort. Patients harbouring uncommon EGFR mutations were more likely to have a family history of cancer (p = 0.048). A higher frequency of KRAS mutations and lower frequency of rearrangement alterations were observed in the Xuanwei cohort (p < 0.001). Patients from Xuanwei showed a significantly higher tumour mutation burden than the reference Chinese and TCGA cohorts (p < 0.001). Our data indicates that patients from Xuanwei with NSCLC harbouring G719X/S768I co-mutations may benefit from treatment with EGFR-tyrosine kinase inhibitors. Our comprehensive molecular profiling revealed unique genomic features of patients from Xuanwei with NSCLC, highlighting the potential for improvement in targeted therapy and immunotherapy.

Validation of a radiomic approach to decipher NSCLC immune microenvironment in surgically resected patients

BACKGROUND

Radiomics has emerged as a noninvasive tool endowed with the potential to intercept tumor characteristics thereby predicting clinical outcome. In a recent study on resected non-small cell lung cancer (NSCLC), we identified highly prognostic computed tomography (CT)-derived radiomic features (RFs), which in turn were able to discriminate hot from cold tumor immune microenvironment (TIME). We aimed at validating a radiomic model capable of dissecting specific TIME profiles bearing prognostic power in resected NSCLC.

METHODS

The validation cohort included 31 radically resected NSCLCs clinicopathologically matched with the training set (n = 69). TIME was classified in hot and cold according to a multiparametric immunohistochemical analysis involving PD-L1 score and incidence of immune effector phenotypes among tumor infiltrating lymphocytes (TILs). High-throughput radiomic features (n = 841) extracted from CT images were correlated to TIME parameters to ultimately define prognostic classes.

RESULTS

We confirmed PD-1 to CD8 ratio as best predictor of clinical outcome among TIME characteristics. Significantly prolonged overall survival (OS) was observed in patients carrying hot (median OS not reached) vs cold (median OS 22 months; hazard ratio 0.28, 95% confidence interval 0.09-0.82; p = 0.015) immune background, thus validating the prognostic impact of these two TIME categories in resected NSCLC. Importantly, in the validation setting, three out of eight previously identified RFs sharply distinguishing hot from cold TIME were endorsed. Among signature-related RFs, Wavelet-HHH_gldm_HighGrayLevelEmphasis highly performed as descriptor of hot immune contexture (area under the receiver operating characteristic curve 0.94, 95% confidence interval 0.81-1.00; p = 0.01).

CONCLUSION

Radiomics may decipher specific TIME profiles providing a noninvasive prognostic approach in resected NSCLC and an exploitable predictive strategy in advanced cases.

Overcoming Resistance to Immune Checkpoint Inhibitors in Head and Neck Squamous Cell Carcinomas

Preclinical data suggest that head and neck squamous cell carcinomas (HNSCC) may evade immune surveillance and induce immunosuppression. One mechanism of immune evasion involves the expression of programmed death ligand-1 (PD-L1) in tumor and immune cells, which is, to date, the only biomarker routinely used in clinical practice to select patients with advanced HNSCCs more likely to benefit from anti-PD-1 therapy. Nonetheless, PD-L1 expression alone incompletely captures the degree of sensitivity of HNSCCs to PD-1 inhibitors. Most patients exposed to anti-PD-1 antibodies do not respond to therapy, suggesting the existence of mechanisms of de novo resistance to immunotherapy. Furthermore, patients that initially respond to PD-1 inhibitors will eventually develop acquired resistance to immunotherapy through mechanisms that have not yet been completely elucidated. In this article, we will provide an overview of the immune landscape of HNSCCs. We will briefly describe the clinical activity of inhibitors of the PD-1/PD-L1 axis in this disease, as well as biomarkers of benefit from these agents that have been identified so far. We will review pre-clinical and clinical work in cancers in general, and in HNSCCs specifically, that have characterized the mechanisms of de novo and acquired resistance to immunotherapy. Lastly, we will provide insights into novel strategies under investigation to overcome resistance to immune checkpoint inhibitors.

Prognostic Implications of the Complement Protein C1Q and Its Correlation with Immune Infiltrates in Osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most widespread bone tumour among childhood cancers, and distant metastasis is the dominant factor in poor prognosis for patients with OS. Therefore, it is necessary to identify new prognostic biomarkers for identifying patients with aggressive disease.

METHODS

Two OS datasets (GSE21257 and GSE33383) were downloaded from the Gene Expression Omnibus (GEO) and subsequently subjected to weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis (DGE) to screen candidate genes. A prognostic model was constructed using OS data derived from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program to further screen key genes and perform gene ontology (GO) analysis. The prognostic values of key genes were assessed using the Kaplan-Meier (KM) plotter. The GEO dataset was used for immune infiltration analysis and association analysis of key genes. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the expression levels of potentially crucial genes in OS cell lines.

RESULTS

In the present study, we found 114 genes with a highly significant correlation in the module and 44 downregulated genes; 25 candidate genes overlapped in the two parts of the genes. Among these, three key genes, C1QA, C1QB, and C1QC, were the most significant hub genes, which had the highest node degrees, were clustered into one group, and implicated in most significant biological processes (regulation of immune effector process). Moreover, these three key genes were negatively associated with the prognosis of OS and positively associated with three immune cells (follicular helper T cells, memory B cells, and CD8 T cells). Additionally, compared to non-metastatic OS cell lines, the expression of three key genes was significantly downregulated in metastatic OS cell lines.

CONCLUSION

Our results revealed that three key genes (C1QA, C1QB, and C1QC) were implicated in tumour immune infiltration and may be promising biomarkers for predicting metastasis and prognosis of patients with OS.

KRAS G12C Mutation Is Associated with Increased Risk of Recurrence in Surgically Resected Lung Adenocarcinoma

PURPOSE

KRAS ^G12C is the most common KRAS mutation in primary lung adenocarcinoma. Phase I clinical trials have demonstrated encouraging clinical activity of KRAS ^G12C inhibitors in the metastatic setting. We investigated disease-free survival (DFS) and tumor genomic features in patients with surgically resected KRAS ^G12C-mutant lung adenocarcinoma.

EXPERIMENTAL DESIGN

Patients who underwent resection of stage I-III lung adenocarcinoma and next-generation sequencing (NGS) were evaluated. Exclusion criteria were receipt of induction therapy, incomplete resection, and low-quality NGS. Mutations were classified as KRAS wild-type (KRAS ^wt), G12C (KRAS ^G12C), or non-G12C (KRAS ^other). DFS was compared between groups using the log-rank test; factors associated with DFS were assessed using Cox regression. Mutual exclusivity and cooccurrence, tumor clonality, and mutational signatures were assessed.

RESULTS

In total, 604 patients were included: 374 KRAS ^wt (62%), 95 KRAS ^G12C (16%), and 135 KRAS ^other (22%). Three-year DFS was not different between KRAS-mutant and KRAS ^wt tumors. However, 3-year DFS was worse in patients with KRAS ^G12C than KRAS ^other tumors (log-rank P = 0.029). KRAS ^G12C tumors had more lymphovascular invasion (51% vs. 37%; P = 0.032) and higher tumor mutation burden [median (interquartile range), 7.0 (5.3-10.8) vs. 6.1 (3.5-9.7); P = 0.021], compared with KRAS ^other tumors. KRAS ^G12C mutation was independently associated with worse DFS on multivariable analysis. Our DFS findings were externally validated in an independent The Cancer Genome Atlas cohort.

CONCLUSIONS

KRAS ^G12C mutations are associated with worse DFS after complete resection of stage I-III lung adenocarcinoma. These tumors harbor more aggressive clinicopathologic and genomic features than other KRAS-mutant tumors. We identified a high-risk group for whom KRAS ^G12C inhibitors may be investigated to improve survival.