Androgen receptor activity inversely correlates with immune cell infiltration and immunotherapy response across multiple cancer lineages.

There is now increasing recognition of the important role of androgen receptor (AR) in modulating immune function. To gain a comprehensive understanding of the effects of AR activity on cancer immunity, we employed a computational approach to profile AR activity in 33 human tumor types using RNA-Seq datasets from The Cancer Genome Atlas. Our pan-cancer analysis revealed that the genes most negatively correlated with AR activity across cancers are involved in active immune system processes. Importantly, we observed a significant negative correlation between AR activity and IFNγ pathway activity at the pan-cancer level. Indeed, using a matched biopsy dataset from subjects with prostate cancer before and after AR-targeted treatment, we verified that inhibiting AR enriches immune cell abundances and is associated with higher IFNγ pathway activity. Furthermore, by analyzing immunotherapy datasets in multiple cancers, our results demonstrate that low AR activity was significantly associated with a favorable response to immunotherapy. Together, our data provide a comprehensive assessment of the relationship between AR signaling and tumor immunity.

Pharmacologic targeting of Nedd8-activating enzyme reinvigorates T-cell responses in lymphoid neoplasia.

Neddylation is a sequential enzyme-based process which regulates the function of E3 Cullin-RING ligase (CRL) and thus degradation of substrate proteins. Here we show that CD8+ T cells are a direct target for therapeutically relevant anti-lymphoma activity of pevonedistat, a Nedd8-activating enzyme (NAE) inhibitor. Pevonedistat-treated patient-derived CD8+ T cells upregulated TNFα and IFNγ and exhibited enhanced cytotoxicity. Pevonedistat induced CD8+ T-cell inflamed microenvironment and delayed tumor progression in A20 syngeneic lymphoma model. This anti-tumor effect lessened when CD8+ T cells lost the ability to engage tumors through MHC class I interactions, achieved either through CD8+ T-cell depletion or genetic knockout of B2M. Meanwhile, loss of UBE2M in tumor did not alter efficacy of pevonedistat. Concurrent blockade of NAE and PD-1 led to enhanced tumor immune infiltration, T-cell activation and chemokine expression and synergistically restricted tumor growth. shRNA-mediated knockdown of HIF-1α, a CRL substrate, abrogated the in vitro effects of pevonedistat, suggesting that NAE inhibition modulates T-cell function in HIF-1α-dependent manner. scRNA-Seq-based clinical analyses in lymphoma patients receiving pevonedistat therapy demonstrated upregulation of interferon response signatures in immune cells. Thus, targeting NAE enhances the inflammatory T-cell state, providing rationale for checkpoint blockade-based combination therapy.

Supervised learning of high-confidence phenotypic subpopulations from single-cell data.

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCILs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

Pevonedistat, a Nedd8-activating enzyme inhibitor, in combination with ibrutinib in patients with relapsed/refractory B-cell non-Hodgkin lymphoma.

Pevonedistat (TAK924) is a Nedd8-activating enzyme inhibitor with preclinical activity in non-Hodgkin lymphoma (NHL). This open-label, Phase I, multicenter, investigator-sponsored study enrolled patients with relapsed/refractory (R/R) NHL and chronic lymphocytic leukemia (CLL). The primary objective was safety. Pevonedistat was given intravenously on days 1, 3, 5 of a 21-day cycle for 8 cycles at five dose levels (15 to 50 mg/m2); ibrutinib was administered at 420 or 560 mg orally daily continuously. Eighteen patients with NHL were enrolled, including 8 patients with mantle cell lymphoma (MCL) and 4 patients with CLL. One dose-limiting toxicity (mediastinal hemorrhage) occurred at 50 mg/m2 of pevonedistat which is the estimated maximum tolerated dose. Bruising and diarrhea were the most common adverse events (56% and 44%). Atrial fibrillation occurred in 3 patients (17%). Grade ≥3 toxicities included arthralgia, atrial fibrillation, bone pain, diarrhea, hypertension, and mediastinal hemorrhage (one patient each). The overall response rate (ORR) was 65% (100% ORR in MCL). Pevonedistat disposition was not modified by ibrutinib. scRNA-Seq analysis showed that pevonedistat downregulated NFκB signaling in malignant B-cells in vivo. Thus, pevonedistat combined with ibrutinib demonstrated safety and promising early efficacy in NHL and CLL. NAE inhibition downregulated NFκB signaling in vivo.

Identification of prostate cancer subtypes based on immune signature scores in bulk and single-cell transcriptomes.

Prostate cancer (PC) is heterogeneous in the tumor immune microenvironment (TIME). Subtyping of PC based on the TIME could provide new insights into intratumor heterogeneity and its correlates of clinical features. Based on the enrichment scores of 28 immune cell types in the TIME, we performed unsupervised clustering to identify immune-specific subtypes of PC. The clustering analysis was performed in ten different bulk tumor transcriptomic datasets and in a single-cell RNA-Seq (scRNA-seq) dataset, respectively. We identified two PC subtypes: PC immunity high (PC-ImH) and PC immunity low (PC-ImL), consistently in these datasets. Compared to PC-ImL, PC-ImH displayed stronger immune signatures, worse clinical outcomes, higher epithelial-mesenchymal transition (EMT) signature, tumor stemness, intratumor heterogeneity (ITH) and genomic instability, and lower incidence of TMPRSS2-ERG fusion. Tumor mutation burden (TMB) showed no significant difference between PC-ImH and PC-ImL, while copy number alteration (CNA) was more significant in PC-ImL than in PC-ImH. PC-ImH could be further divided into two subgroups, which had significantly different immune infiltration levels and clinical features. In conclusion, "hot" PCs have stronger anti-tumor immune response, while worse clinical outcomes versus "cold" PCs. CNA instead of TMB plays a crucial role in the regulation of TIME in PC. TMPRSS2-ERG fusion correlates with decreased anti-tumor immune response while better disease-free survival in PC. The identification of immune-specific subtypes has potential clinical implications for PC immunotherapy.

The mutation in splicing factor genes correlates with unfavorable prognosis, genomic instability, anti-tumor immunosuppression and increased immunotherapy response in pan-cancer.

Splicing abnormality resulting from somatic mutations in key splicing factor genes (SFG) has been detected in various cancers. Hence, an in-depth study of splicing factor genes mutations' impact on pan-cancer is meaningful. This study investigated associations of splicing factor genes mutations with clinical features, tumor progression phenotypes, genomic integrity, anti-tumor immune responses, and immunotherapy response in 12 common cancer types from the TCGA database. Compared to SFG-wildtype cancers, SFG-mutated cancers displayed worse survival prognosis, higher tumor mutation burden and aneuploidy levels, higher expression of immunosuppressive signatures, and higher levels of tumor stemness, proliferation potential, and intratumor heterogeneity (ITH). However, splicing factor genes-mutated cancers showed higher response rates to immune checkpoint inhibitors than splicing factor genes-wildtype cancers in six cancer cohorts. Single-cell data analysis confirmed that splicing factor genes mutations were associated with increased tumor stemness, proliferation capacity, PD-L1 expression, intratumor heterogeneity, and aneuploidy levels. Our data suggest that the mutation in key splicing factor genes correlates with unfavorable clinical outcomes and disease progression, genomic instability, anti-tumor immunosuppression, and increased immunotherapy response in pan-cancer. Thus, the splicing factor genes mutation is an adverse prognostic factor and a positive marker for immunotherapy response in cancer.

Pan-Cancer Analysis Reveals That E1A Binding Protein p300 Mutations Increase Genome Instability and Antitumor Immunity.

E1A binding protein p300 (EP300) is mutated in diverse cancers. Nevertheless, a systematic investigation into the associations of EP300 mutations with genome instability and antitumor immunity in pan-cancer remains lacking. Using the datasets from The Cancer Genome Atlas, we analyzed the correlations between EP300 mutations and genome instability and antitumor immune response in 11 cancer types. Compared to EP300-wild-type cancers, EP300-mutated cancers had significantly higher tumor mutation burden (TMB) in 10 cancer types. EP300-mutated cancers harbored a much higher fraction of microsatellite instable cancers in the colon and gastric cancers. EP300 was co-mutated with genes involved in DNA damage repair pathways in multiple cancers. Furthermore, compared to EP300-wild-type cancers, EP300-mutated cancers had significantly higher immune cytolytic activity scores and ratios of immune-stimulatory over immune-inhibitory signatures in diverse cancers. Also, EP300-mutated cancers showed significantly higher programmed death-ligand 1 (PD-L1) expression levels than EP300-wild-type cancers. The increased TMB, antitumor immune activity, and PD-L1 expression indicated a favorable response to immune checkpoint inhibitors (ICIs) in EP300-mutated cancers, as evident in three cancer cohorts treated with ICIs. Thus, the EP300 mutation could be a predictive biomarker for the response to immunotherapy.

The spliceosome pathway activity correlates with reduced anti-tumor immunity and immunotherapy response, and unfavorable clinical outcomes in pan-cancer.

Alterations in the spliceosome pathway (SP) have been associated with diverse human cancers. In this study, we explored associations of the SP activity with various clinical features, anti-tumor immune signatures, tumor immunity-related genomic and molecular features, and the response to immunotherapies and targeted therapies in 29 cancer types from The Cancer Genome Atlas (TCGA) database. We showed that the SP activity was an oncogenic signature, as evidenced by its hyperactivation in cancer and invasive cancer subtypes and correlations with unfavorable clinical outcomes and anti-tumor immunosuppression in various cancers. The SP activity showed positive correlations with tumor mutation burden (TMB) and aneuploidy in diverse cancers, suggesting its association with genomic instability. However, the negative association between the SP activity and anti-tumor immune response was independent of its associations with aneuploidy and TMB. Furthermore, we supported that the SP activity had a negative correlation with immunotherapy response in four cancer cohorts treated by immune checkpoint inhibitors. Moreover, elevated SP activity is correlated with increased drug sensitivity for a broad spectrum of anti-tumor targeted therapies. In conclusion, the SP activity is a negative biomarker for anti-tumor immune response, prognosis, and the response to immunotherapeutic and targeted drugs in pan-cancer.

DITHER: an algorithm for Defining IntraTumor Heterogeneity based on EntRopy.

Intratumor heterogeneity (ITH) is associated with tumor development, prognosis, immune evasion and therapeutic effects. We proposed the Defining ITH based on EntRopy (DITHER) algorithm for evaluating ITH. We first evaluated the entropies of somatic mutation profiles and copy number alteration (CNA) profiles in a tumor, respectively, and defined their average as the ITH level for the tumor. Using DITHER, we analyzed 33 cancer types from The Cancer Genome Atlas (TCGA) program. We demonstrated that the ITH defined by DITHER had the typical properties of ITH, namely its strong correlations with tumor progression, unfavorable phenotype, genomic instability and immune evasion. Compared with two other ITH evaluation methods: MATH and PhyloWGS, the DITHER ITH had more prominent characteristics of ITH. Moreover, different from MATH and PhyloWGS, DITHER scores were positively correlated with tumor purity, suggesting that DITHER tends to capture the ITH between tumor cells. Interestingly, microsatellite instability (MSI)-high tumors had significantly lower DITHER scores than microsatellite stability (MSS)/MSI-low tumors, although the former had significantly higher tumor mutation loads than the latter. It suggests that the hypermutability of MSI is homogeneous between different cellular populations in bulk tumors. The DITHER ITH may provide novel insights into tumor biology and potential clinical applications.

Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach.

The COVID-19 virus has infected more than 38 million people and resulted in more than one million deaths worldwide as of October 14, 2020. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, economic inequality enhanced the risk of COVID-19 transmission. The per capita hospital beds correlated negatively with COVID-19 deaths. Blood types B and AB were protective factors for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV and influenza and pneumonia was associated with reduced COVID-19 risk. Increased intake of vegetables, edible oil, protein, vitamin D, and vitamin K was associated with reduced COVID-19 risk, while increased intake of alcohol was associated with increased COVID-19 risk. Other factors included age, sex, temperature, humidity, social distancing, smoking, health investment, urbanization level, and race. High temperature is a more compelling factor mitigating COVID-19 transmission than low temperature. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread.

KALRN mutations promote antitumor immunity and immunotherapy response in cancer.

BACKGROUND: kalirin RhoGEF kinase (KALRN) is mutated in a wide range of cancers. Nevertheless, the association between KALRN mutations and the pathogenesis of cancer remains unexplored. Identification of biomarkers for cancer immunotherapy response is crucial because immunotherapies only show beneficial effects in a subset of patients with cancer. METHODS: We explored the correlation between KALRN mutations and antitumor immunity in 10 cancer cohorts from The Cancer Genome Atlas program by the bioinformatics approach. Moreover, we verified the findings from the bioinformatics analysis with in vitro and in vivo experiments. We explored the correlation between KALRN mutations and immunotherapy response in five cancer cohorts receiving immune checkpoint blockade therapy. RESULTS: Antitumor immune signatures were more enriched in KALRN-mutated than KALRN-wildtype cancers. Moreover, KALRN mutations displayed significant correlations with increased tumor mutation burden and the microsatellite instability or DNA damage repair deficiency genomic properties, which may explain the high antitumor immunity in KALRN-mutated cancers. Also, programmed cell death 1 ligand (PD-L1) expression was markedly upregulated in KALRN-mutated versus KALRN-wildtype cancers. The increased antitumor immune signatures and PD-L1 expression in KALRN-mutated cancers may favor the response to immune checkpoint blockade therapy in this cancer subtype, as evidenced in five cancer cohorts receiving antiprogrammed cell death protein 1 (PD-1)/PD-L1/cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) immunotherapy. Furthermore, the significant association between KALRN mutations and increased antitumor immunity was associated with the fact that KALRN mutations compromised the function of KALRN in targeting Rho GTPases for the regulation of DNA damage repair pathways. In vitro and in vivo experiments validated the association of KALRN deficiency with antitumor immunity and the response to immune checkpoint inhibitors. CONCLUSIONS: The KALRN mutation is a useful biomarker for predicting the response to immunotherapy in patients with cancer.