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The microbiome is now regarded as one of the hallmarks of cancer and several strategies to modify the gut microbiota to improve immune checkpoint inhibitor (ICI) activity are being evaluated in clinical trials. Preliminary data regarding the upper gastro-intestinal microbiota indicated that Helicobacter pylori seropositivity was associated with a negative prognosis in patients amenable to ICI. In 97 patients with advanced melanoma treated with ICI, we assessed the impact of H. pylori on outcomes and microbiome composition. We performed H. pylori serology and profiled the fecal microbiome with metagenomics sequencing. Among the 97 patients, 22% were H. pylori positive (Pos). H. pylori Pos patients had a significantly shorter overall survival (p = .02) compared to H. pylori negative (Neg) patients. In addition, objective response rate and progression-free survival were decreased in H. pylori Pos patients. Metagenomics sequencing did not reveal any difference in diversity indexes between the H. pylori groups. At the taxa level, Eubacterium ventriosum, Mediterraneibacter (Ruminococcus) torques, and Dorea formicigenerans were increased in the H. pylori Pos group, while Alistipes finegoldii, Hungatella hathewayi and Blautia producta were over-represented in the H. pylori Neg group. In a second independent cohort of patients with NSCLC, diversity indexes were similar in both groups and Bacteroides xylanisolvens was increased in H. pylori Neg patients. Our results demonstrated that the negative impact of H. pylori on outcomes seem to be independent from the fecal microbiome composition. These findings warrant further validation and development of therapeutic strategies to eradicate H. pylori in immuno-oncology arena.

Introduction: Immunotherapy is regarded as one of the major breakthroughs in cancer treatment. Despite its success, only a subset of patients responds-urging the quest for predictive biomarkers. We hypothesize that artificial intelligence (AI) algorithms can automatically quantify radiographic characteristics that are related to and may therefore act as noninvasive radiomic biomarkers for immunotherapy response.Patients and methods: In this study, we analyzed 1055 primary and metastatic lesions from 203 patients with advanced melanoma and non-small-cell lung cancer (NSCLC) undergoing anti-PD1 therapy. We carried out an AI-based characterization of each lesion on the pretreatment contrast-enhanced CT imaging data to develop and validate a noninvasive machine learning biomarker capable of distinguishing between immunotherapy responding and nonresponding. To define the biological basis of the radiographic biomarker, we carried out gene set enrichment analysis in an independent dataset of 262 NSCLC patients.Results: The biomarker reached significant performance on NSCLC lesions (up to 0.83 AUC, P < 0.001) and borderline significant for melanoma lymph nodes (0.64 AUC, P = 0.05). Combining these lesion-wide predictions on a patient level, immunotherapy response could be predicted with an AUC of up to 0.76 for both cancer types (P < 0.001), resulting in a 1-year survival difference of 24% (P = 0.02). We found highly significant associations with pathways involved in mitosis, indicating a relationship between increased proliferative potential and preferential response to immunotherapy.Conclusions: These results indicate that radiographic characteristics of lesions on standard-of-care imaging may function as noninvasive biomarkers for response to immunotherapy, and may show utility for improved patient stratification in both neoadjuvant and palliative settings.

The emergence of immunotherapies has definitely proven the tight relationship between malignant and immune cells, its impact on cancer outcome and its therapeutic potential. In this context, it is undoubtedly critical to decipher the transcriptional regulation of these complex interactions. Following early observations demonstrating the roles of NF-κB in cancer initiation and progression, a series of studies converge to establish NF-κB as a master regulator of immune responses to cancer. Importantly, NF-κB is a family of transcriptional activators and repressors that can act at different stages of cancer immunity. In this review, we provide an overview of the selective cell-intrinsic contributions of NF-κB to the distinct cell types that compose the tumor immune environment. We also propose a new view of NF-κB targeting drugs as a new class of immunotherapies for cancer.

Glioblastoma (GBM) continues to be the most aggressive cancer of the brain. The dismal prognosis is largely attributed to the microenvironment surrounding tumor cells. Astrocytes, the main component of the GBM microenvironment, play several fundamental physiological roles in the central nervous system. During the development of GBM, tumor-associated astrocytes (TAAs) directly contact GBM cells, which activate astrocytes to form reactive astrocytes, facilitating tumor progression, proliferation and migration through multiple well-understood signaling pathways. Notably, TAAs also influence GBM cell behaviors via suppressing immune responses and enhancing the chemoradiotherapy resistance of tumor cells. These new activities are closely linked with the treatment and prognosis of GBM. In this review, we discuss recent advances regarding new functions of reactive astrocytes, including TAA-cancer cell interactions, mechanisms involved in immunosuppressive regulation, and chemoradiotherapy resistance. It is expected that these updated experimental or clinical studies of TAAs may provide a promising approach for GBM treatment in the near future.

Tumor-infiltrating immune cells play a key role against cancer. However, malignant cells are able to evade the immune response and establish a very complex balance in which different immune subtypes may drive tumor progression, metastatization and resistance to therapy. New immunotherapeutic approaches aim at restoring the natural balance and increase immune response against cancer by different mechanisms. The complexity of these interactions and the heterogeneity of immune cell subpopulations are a real challenge when trying to develop new immunotherapeutics and evaluate or predict their efficacy in vivo. To this purpose, molecular imaging can offer non-invasive diagnostic tools like radiopharmaceuticals, contrast agents or fluorescent dyes. These agents can be useful for preclinical and clinical purposes and can overcome [18F]FDG limitations in discriminating between true-progression and pseudo-progression. This review provides a comprehensive overview of immune cells involved in microenvironment, available immunotherapies and imaging agents to highlight the importance of new therapeutic biomarkers and their in vivo evaluation to improve the management of cancer patients.

Background Cancer mutations generate novel (neo-)peptides recognised by T cells, but the determinants of recognition are not well characterised. The difference in predicted class I major histocompatibility complex (MHC-I) binding affinity between wild-type and corresponding mutant peptides (differential agretopicity index; DAI) may reflect clinically relevant cancer peptide immunogenicity. Our aim was to explore the relationship between DAI, measures of immune infiltration and patient outcomes in advanced cancer. Patients and methods Cohorts of patients with advanced non-small-cell lung cancer (NSCLC; LUAD, n = 66) and melanoma (SKCM, n = 72) were obtained from The Cancer Genome Atlas. Three additional cohorts of immunotherapy treated patients with advanced melanoma (total n = 131) and NSCLC (n = 31) were analysed. Neopeptides and their clonal status were defined using genomic data. MHC-I binding affinity was predicted for each neopeptide and DAI values summarised as the sample mean DAI. Correlations between mean DAI and markers of immune activity were evaluated using measures of lymphocyte infiltration and immune gene expression. Results In univariate and multivariate analyses, mean DAI significantly correlated with overall survival in 3/5 cohorts, with evidence of superiority over nonsynonymous mutational and neoantigen burden. In these cohorts, the effect was seen for mean DAI of clonal but not subclonal peptides. In SKCM, the association between mean DAI and survival bordered significance (P = 0.068), reaching significance in an immunotherapy-treated melanoma cohort (P = 0.003). Mean DAI but not mutational nor neoantigen burden was positively correlated with independently derived markers of immune infiltration in both SKCM (P = 0.027) and LUAD (P = 0.024). Conclusions The association between mean DAI, survival and measures of immune activity support the hypothesis that DAI is a determinant of cancer peptide immunogenicity. Investigation of DAI as a marker of immunologically relevant peptides in further datasets and future clinical studies of neoantigen based immunotherapies is warranted.

Alternative splicing (AS) tremendously increases the use of genetic information by generating protein isoforms that differ in protein–protein interactions, catalytic activity and/or subcellular localization. This review is not dedicated to AS in general, but rather we focus our attention on AS of P2RX7 pre-mRNA. Whereas P2RX7 mRNA is expressed by virtually all eukaryotic mammalian cells, the expression of this channel receptor is restrained to certain cells. When expressed at the cell membrane, P2RX7 controls downstream events including release of inflammatory molecules, phagocytosis, cell proliferation and death and metabolic events. Therefore, P2RX7 is an important actor of health and diseases. In this review, we summarize the general mechanisms leading to AS. Further, we recapitulate our current knowledge concerning the functional regions in P2RX7, identified at the genetic or exonic levels, and how AS may affect the expression of these regions. Finally, the potential of P2RX7 splice variants to control the fate of cancer cells is discussed. Keywords: Purinergic signaling, P2X7, ATP, Onco-immunology

The tumor microenvironments of paired primary lung cancers and brain metastases are significantly different, such that many of the metastases lose PD-L1 expression, lymphocyte infiltration or both with greater discrepancies over time. The spatial and temporal heterogeneity of PD-L1 expression may limit its use as a tissue-based predictive biomarker in lung cancer., Background The dynamics of PD-L1 expression may limit its use as a tissue-based predictive biomarker. We sought to expand our understanding of the dynamics of PD-L1 expression and tumor-infiltrating lymphocytes (TILs) in patients with lung cancer-related brain metastases. Experimental design Paired primary lung cancers and brain metastases were identified and assessed for PD-L1 and CD3 expression by immunohistochemistry. Lesions with 5% or greater PD-L1 expression were considered positive. Agreement statistics and the χ2 or Fisher's exact test were used for analysis. Results We analyzed 146 paired lesions from 73 cases. There was disagreement of tumor cell PD-L1 expression in 10 cases (14%, κ = 0.71), and disagreement of TIL PD-L1 expression in 19 cases (26%, κ = 0.38). Most paired lesions with discordant tumor cell expression of PD-L1 were obtained 6 or more months apart. When specimens were categorized using a proposed tumor microenvironment categorization scheme based on PD-L1 expression and TILs, there were significant changes in the classifications because many of the brain metastases lacked either PD-L1 expression, tumor lymphocyte infiltration or both even when they were present in the primary lung cancer specimens (P = 0.009). Conclusions We identified that there are significant differences between the tumor microenvironment of paired primary lung cancers and brain metastases. When physicians decide to treat patients with lung cancer with a PD-1 or PD-L1 inhibitor, they must do so in the context of the spatial and temporal heterogeneity of the tumor microenvironment.

Cancer immunotherapy is aimed at stimulating tumor-specific cytotoxic T lymphocytes and their subsequent trafficking so that they may reach, and persist in, the tumor microenvironment, recognizing and eliminating malignant target cells. Thus, characterization of the phenotype and effector functions of CD8+ T lymphocytes infiltrating human solid tumors is essential for better understanding and manipulating the local antitumor immune response, and for defining their contribution to the success of current cancer immunotherapy approaches. Accumulating evidence indicates that a substantial subpopulation of CD3+CD8+ tumor-infiltrating lymphocytes are tissue resident memory T (TRM) cells, and is emerging as an activated tumor-specific T-cell subset. These TRM cells accumulate in various human cancer tissues, including non-small-cell lung carcinoma (NSCLC), ovarian and breast cancers, and are defined by expression of CD103 [αE(CD103)β7] and/or CD49a [α1(CD49a)β1] integrins, along with C-type lectin CD69, which most likely contribute to their residency characteristic. CD103 binds to the epithelial cell marker E-cadherin, thereby promoting retention of TRM cells in epithelial tumor islets and maturation of cytotoxic immune synapse with specific cancer cells, resulting in T-cell receptor (TCR)-dependent target cell killing. Moreover, CD103 integrin triggers bidirectional signaling events that cooperate with TCR signals to enable T-cell migration and optimal cytokine production. Remarkably, TRM cells infiltrating human NSCLC tumors also express inhibitory receptors such as programmed cell death-1, the neutralization of which, with blocking antibodies, enhances CD103-dependent TCR-mediated cytotoxicity toward autologous cancer cells. Thus, accumulation of TRM cells at the tumor site explains the more favorable clinical outcome, and might be associated with the success of immune checkpoint blockade in a fraction of cancer patients.

Background Nivolumab 3 mg/kg every 2 weeks (Q2W) has shown benefit versus the standard of care in melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, flat dosing is expected to shorten preparation time and improve ease of administration. With knowledge of nivolumab safety, efficacy, and pharmacokinetics across a wide dose range in body weight (BW) dosing, assessment of the benefit–risk profile of a 240-mg flat dose relative to the approved 3-mg/kg dose was approached by quantitative clinical pharmacology. Patients and methods A flat dose of 240 mg was selected based on its equivalence to the 3-mg/kg dose at the median BW of ∼80 kg in patients in the nivolumab program. The benefit–risk profile of nivolumab 240 mg was evaluated by comparing exposures at 3 mg/kg Q2W and 240 mg Q2W across BW and tumor types; clinical safety at 3 mg/kg Q2W by BW and exposure quartiles in melanoma, NSCLC, and RCC; and safety and efficacy at 240 mg Q2W relative to 3 mg/kg Q2W in melanoma, NSCLC, and RCC. Results The median nivolumab exposure and its distribution at 240 mg Q2W were similar to 3 mg/kg Q2W in the simulated population. Safety analyses did not demonstrate a clinically meaningful relationship between BW or nivolumab exposure quartiles and frequency or severity of adverse events. The predicted safety and efficacy were similar across nivolumab exposure ranges achieved with 3 mg/kg Q2W or 240 mg Q2W flat dose. Conclusion Based on population pharmacokinetic modeling, established flat exposure–response relationships for efficacy and safety, and clinical safety, the benefit–risk profile of nivolumab 240 mg Q2W was comparable to 3 mg/kg Q2W. The quantitative clinical pharmacology approach provided evidence for regulatory decision-making on dose modification, obviating the need for an independent clinical study.