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Non-small cell lung cancer (NSCLC) is known to carry heavy mutation load. Besides smoking, cytidine deaminase APOBEC3B plays a key role in the mutation process of NSCLC. APOBEC3B is also reported to be upregulated and predicts bad prognosis in NSCLC. However, targeting APOBEC3B high NSCLC is still a big challenge. Here we show that APOBEC3B upregulation is significantly associated with immune gene expression, and APOBEC3B expression positively correlates with known immunotherapy response biomarkers, including: PD-L1 expression and T-cell infiltration in NSCLC. Importantly, APOBEC mutational signature is specifically enriched in NSCLC patients with durable clinical benefit after immunotherapy and APOBEC mutation count can be better than total mutation in predicting immunotherapy response. In together, this work provides evidence that APOBEC3B upregulation and APOBEC mutation count can be used as novel predictive markers in guiding NSCLC checkpoint blockade immunotherapy.

Immunotherapy, represented by immune checkpoint inhibitors (ICI), is transforming the treatment of cancer. However, only a small percentage of patients show response to ICI, and there is an unmet need for biomarkers that will identify patients who are more likely to respond to immunotherapy. The fundamental basis for ICI response is the immunogenicity of a tumor, which is primarily determined by tumor antigenicity and antigen presentation efficiency. Here, we propose a method to measure tumor immunogenicity score (TIGS), which combines tumor mutational burden (TMB) and an expression signature of the antigen processing and presenting machinery (APM). In both correlation with pan-cancer ICI objective response rates (ORR) and ICI clinical response prediction for individual patients, TIGS consistently showed improved performance compared to TMB and other known prediction biomarkers for ICI response. This study suggests that TIGS is an effective tumor-inherent biomarker for ICI-response prediction. In the last decade a new kind of cancer therapy, called immunotherapy, has changed how doctors treat cancer patients. These therapies mean that previously incurable cancers, including some skin and lung cancers, can now sometimes be cured. Immunotherapy does this by activating the patient’s own immune system so that it will attack the cancer cells. But for this to work, the cancer cells, much like invading bacteria or viruses, need to be recognized as foreign. Cancer cells contain many DNA mutations that cause the cell to make mutated proteins it would not normally make. These proteins betray the cancer cells as foreign to the immune system. The extent to which cancer cells make mutated proteins – also called the ‘tumor mutational burden’ – can sometimes predict whether a patient will respond to immunotherapy. In general, patients with a high mutational burden respond well to immunotherapy, but overall fewer than one in five cancer patients are cured by this treatment. An important question is whether there are better ways of predicting if a cancer patient will respond to immunotherapy. Wang et al. have addressed this problem by adding a second variable to the prediction. Not only do cancer cells have to make mutated proteins, but these proteins also have to be ‘seen’ by immune cells. Cancer cells, like normal cells, have mechanisms to present protein fragments to immune cells. Wang et al. hypothesized that patients with a high mutational burden would not respond to immunotherapy if they were lacking the machinery required for presenting protein fragments. The experiments revealed that measuring both tumor mutational burden and the levels of the machinery that presents protein fragments resulted in better predictions of patients’ responses to immunotherapy than measuring tumor mutational burden alone. Additionally, this new way of predicting responses to immunotherapy was successful across many different cancer types. The combined measurement of these two variables could be applied in clinical practice as a way to predict cancer patients’ response to immunotherapy. This should allow doctors to determine which course of treatment will work best for a specific patient. The results also suggest that inducing tumor cells to produce more of the machinery that presents protein fragments to the immune system could increase their responsiveness to immunotherapy. In the future, predicting how well a patient will respond to immunotherapy could become even more accurate by incorporating additional variables.

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool “sigminer” has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis.

Lymph nodes metastases are common in patients with lung cancer. Additionally, those patients are often at a higher risk for death from lung tumor than those with tumor-free lymph nodes. Somatic DNA alterations are key drivers of cancer, and copy number alterations (CNAs) are major types of DNA alteration that promote lung cancer progression. Here, we performed genome-wide DNA copy number analysis, and identified a novel lung-cancer-metastasis-related gene, EFNA4. The EFNA4 genome locus was significantly amplified, and EFNA4 mRNA expression was significantly up-regulated in lung cancer compared with normal lung tissue, and also in lung cancer with lymph node metastases compared with lung cancer without metastasis. EFNA4 encodes Ephrin A4, which is the ligand for Eph receptors. The function of EFNA4 in human lung cancer remains largely unknown. Through cell line experiments we showed that EFNA4 overexpression contributes to lung tumor cells growth, migration and adhesion. Conversely, EFNA4 knockdown or knockout led to the growth suppression of cells and tumor xenografts in mice. Lung cancer patients with EFNA4 overexpression have poor prognosis. Together, by elucidating a new layer of the role of EFNA4 in tumor proliferation and migration, our study demonstrates a better understanding of the function of the significantly amplified and overexpressed gene EFNA4 in lung tumor metastasis, and suggests EFNA4 as a potential target in metastatic lung cancer therapy.

Receptor-interacting protein kinase 2 (RIPK2) has emerged as a promising drug target in various cancers, including prostate cancer (PC). However, the absence of reliable biomarkers to assess RIPK2 activity limits both patient selection for anti-RIPK2 therapies and treatment monitoring. To address this gap, we performed RNA-Seq analysis on PC cell lines (22Rv1, DU145, and PC3) with CRISPR/Cas9-mediated knockout ( -KO) using two independent guide RNAs. This analysis identified 13 candidate RIPK2-regulated genes, of which eight were validated by reverse transcription quantitative PCR (RT-qPCR). Furthermore, treatment with two distinct RIPK2 inhibitors significantly reduced RIPK2 signature scores in five independent PC cell lines in a dose- and/or time-dependent manner. Clinical association analyses revealed that high RIPK2 signature scores correlate with metastasis and worse biochemical recurrence-free, progression-free, disease-free, and overall survival, outperforming RIPK2 mRNA levels as a prognostic biomarker. This study establishes, for the first time, a RIPK2-regulated gene signature as a potential biomarker for RIPK2 activity and PC prognosis, warranting further validation in clinical specimens to provide a much-needed tool for patient stratification and response monitoring in RIPK2-targeted therapies.

Lymph nodes metastases are common in patients with lung cancer. And those patients are often at a higher risk for death from lung tumor than those with tumor-free lymph nodes. So-matic DNA alterations are key drivers of cancer, and copy number alterations (CNAs) are a major type of DNA alteration that promotes lung cancer progression. Here, we performed genome-wide DNA copy number analysis, and identified a novel lung cancer metastasis related gene, EFNA4. EFNA4 genome locus was significantly amplified and EFNA4 mRNA expression was significantly up-regulated in lung cancer compared with normal lung tissue, and also in lung cancer with lymph node metastases compared with lung cancer without metastasis. EFNA4 encodes Ephrin A4, which is the ligand for Eph receptors. The function of EFNA4 in human lung cancer remains largely unknown. Through cell line experiments we showed that EFNA4 overexpression contributes to lung tumor cells growth, migration and adhesion. Conversely, EFNA4 knockdown or knockout led to the growth suppression of cells and tumor xenografts in mice. Lung cancer patients with EFNA4 over-expression have poor prognosis. Together, by elucidating a new layer of the role of EFNA4 in tumor proliferation and migration, our study demonstrates a better understanding of the function of the significantly amplified and overexpressed gene EFNA4 in lung tumor metastasis and suggests EFNA4 as a potential target in metastatic lung cancer therapy. Lymph nodes are likely to be the first stop for lung cancer metastasis. To further investigate the mechanism of lung cancer lymph node metastasis, we performed cancer genome analysis and found that EFNA4, a member of the ephrin (EPH) family, is amplified and up-regulated in lung tumor patients, especially in patients with lymph node metastases. In vitro and in vivo experiments show that overexpression of EFNA4 promotes lung tumor cell proliferation and migration, while knockdown or knockout of EFNA4 inhibits cell proliferation and migration. Altogether, our results suggest that the DNA amplification of EFNA4 genome locus could play an oncogenic function in promoting lung cancer lymph node metastasis.

GGCT encodes γ-glutamyl cyclotransferase enzyme activity, and its expression is up-regulated in various human cancers. γ-glutamyl cyclotransferase enzyme activity was originally purified from human red blood cells (RBCs), however physiological function of GGCT in RBCs is still not clear. Here we reported that Ggct deletion in mouse leads to splenomegaly and progressive anemia phenotypes, due to elevated oxidative damage and shortened life span of Ggct−/− RBCs. Ggct−/− RBCs have increased reactive oxygen species (ROS), and are more sensitive to H2O2 induced damage compared to control RBCs. Glutathione (GSH) and GSH synthesis precursor L-cysteine are decreased in Ggct−/− RBCs. Our study suggests a critical function of Ggct in RBC redox balance and life span maintenance through regulating GSH metabolism.

This study is arising from Van den Eynden J. et al. Nature Genetics. Lack of detectable neoantigen depletion signals in the untreated cancer genome. Van den Eynden J. et al. tried to address a very important scientific question: could the immune system eliminate cancer cells with immunogenic mutations in untreated situation? Van den Eynden J. et al. first annotated the human exome into \"HLA-binding regions\" and \"non HLA-binding regions\" based on the predicted binding affinity of nonapeptides translated from the un-mutated reference coding genome with type I HLA alleles. They hypothesized that if neoantigen depletion signal exist, the nonsynonymous mutations in \"HLA-binding regions\" will be negatively selected during cancer evolution, while nonsynonymous mutation in \"non HLA-binding regions\" will not be negatively selected. This will lead to decreased nonsynonymous vs synonymous mutation ratio (n/s) in \"HLA-binding regions\" compared with \"non HLA-binding regions\". They defined HLA-binding mutation ratio (HBMR) as the ratio of n/s in \"HLA-binding regions\" to \"non HLA-binding regions\", and reported that HBMRs are close to 1 in different types of cancer after background corrections, meaning neoantigen depletion signals are not detectable in different types of cancer. The fundamental problem of their hypothesis lies in that the actual neoantigens with immunogenicity do not overlap with their defined \"HLA-binding regions\". Actually, most neoantigens with immunogenicity are not located in \"HLA-binding regions\", when dissimilarity between mutant and wild type peptide are considered. It is the neoantigen with immunogenicity, but not nonsynonymous mutation in their defined \"HLA-binding regions\" undergo immunoediting based negative selection. Thus the results reported in that study are fundamentally flawed, and at this current stage we could not draw a solid conclusion as to whether the neoantigen depletion signal exists or not. Competing Interest Statement The authors have declared no competing interest.