Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma.

Background: Pharmacogenomics is crucial for individualized drug therapy and plays an increasingly vital role in precision medicine decision-making. However, pharmacogenomics-based molecular subtypes and their potential clinical significance remain primarily unexplored in lung adenocarcinoma (LUAD). Methods: A total of 2065 samples were recruited from eight independent cohorts. Pharmacogenomics data were generated from the profiling of relative inhibition simultaneously in mixtures (PRISM) and the genomics of drug sensitivity in cancer (GDSC) databases. Multiple bioinformatics approaches were performed to identify pharmacogenomics-based subtypes and find subtype-specific properties. Results: Three reproducible molecular subtypes were found, which were independent prognostic factors and highly associated with stage, survival status, and accepted molecular subtypes. Pharmacogenomics-based subtypes had distinct molecular characteristics: S-Ⅰ was inflammatory, proliferative, and immune-evasion; S-Ⅱ was proliferative and genetics-driven; S-III was metabolic and methylation-driven. Finally, our study provided subtype-guided personalized treatment strategies: Immune checkpoint blockers (ICBs), doxorubicin, tipifarnib, AZ628, and AZD6244 were for S-Ⅰ; Cisplatin, camptothecin, roscovitine, and A.443654 were for S-Ⅱ; Docetaxel, paclitaxel, vinorelbine, and BIBW2992 were for S-III. Conclusion: We provided a novel molecular classification strategy and revealed three pharmacogenomics-based subtypes for LUAD patients, which uncovered potential subtype-related and patient-specific therapeutic strategies.

Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes.

Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.

Characterization of the liver immune microenvironment in liver biopsies from patients with chronic HBV infection.

BACKGROUND & AIMS: We aim to describe the liver immune microenvironment by analyzing liver biopsies from patients with chronic HBV infection (CHB). Host immune cell signatures and their corresponding localization were characterized by analyzing the intrahepatic transcriptome in combination with a custom multiplex immunofluorescence panel. METHOD: Matching FFPE and fresh frozen liver biopsies were collected from immune active patients within the open-label phase IV study GS-US-174-0149. RNA-Seq was conducted on 53 CHB liver biopsies from 46 patients. Twenty-eight of the 53 samples had matched FFPE biopsies and were stained with a 12-plex panel including cell segmentation, immune and viral biomarkers. Corresponding serum samples were screened using the MSD Human V-plex Screen Service to identify peripheral correlates for the immune microenvironment. RESULTS: Using unsupervised clustering of the transcriptome, we reveal two unique liver immune signatures classified as immune high and immune low based on the quantification of the liver infiltrate gene signatures. Multiplex immunofluorescence analysis demonstrated large periportal lymphoid aggregates in immune high samples consisting of CD4 and CD8 T cells, B cells and macrophages. Differentiation of the high and low immune microenvironments was independent of HBeAg status and peripheral viral antigen levels. In addition, longitudinal analysis indicates that treatment and normalization of ALT correlates with a decrease in liver immune infiltrate and inflammation. Finally, we screened a panel of peripheral biomarkers and identified ICAM-1 and CXCL10 as biomarkers that strongly correlate with these unique immune microenvironments. CONCLUSION: These data provide a description of immune phenotypes in patients with CHB and show that immune responses are downregulated in the liver following nucleotide analogue treatment. This may have important implications for both the safety and efficacy of immune modulator programs aimed at HBV cure. LAY SUMMARY: Liver biopsies from patients with chronic hepatitis B were submitted to RNA-Seq and multiplex immunofluorescence and identified two different liver immune microenvironments: immune high and immune low. Immune high patients showed elevated immune pathways, including interferon signaling pathways, and increase presence of immune cells. Longitudinal analysis of biopsies from treatment experienced patients showed that treatment correlates with a marked decrease in inflammation and these findings may have important implications for both safety and efficacy of immune modulator programs for HBV cure.

Discovery of tumor immune infiltration-related snoRNAs for predicting tumor immune microenvironment status and prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a high mortality rate and is difficult to diagnose and treat in its early stage. Previous studies have demonstrated that small nucleolar RNAs (snoRNAs) play a critical role in tumor immune infiltration and the development of a variety of solid tumors. However, there have been no studies on the correlation between tumor-infiltrating immune-related snoRNAs (TIISRs) and LUAD. In this study, we filtered six immune-related snoRNAs based on the tissue specificity index (TSI) and expression profile of all snoRNAs between all LUAD cell lines from the Cancer Cell Line Encyclopedia and 21 types of immune cells from the Gene Expression Omnibus database. Further, we performed real-time quantitative polymerase chain reaction (RT-qPCR) to validate the expression status of these snoRNAs on peripheral blood mononuclear cells (PBMCs) and lung cancer cell lines. Next, we developed a TIISR signature based on the expression profiles of snoRNAs from 479 LUAD patients filtered by the random survival forest algorithm. We then analyzed the value of this TIISR signature (TIISR risk score) for assessing tumor immune infiltration, immune checkpoint inhibitor (ICI) treatment response, and the prognosis of LUAD between groups with high and low TIISR risk score. Further, we found that the TIISR risk score groups showed significant differences in biological characteristics and that the risk score could be used to assess the level of tumor immune cell infiltration, thereby predicting prognosis and responsiveness to immunotherapy in LUAD patients.

Identification of subtypes correlated with tumor immunity and immunotherapy in cutaneous melanoma.

Because immune checkpoint inhibitors (ICIs) are effective for a subset of melanoma patients, identification of melanoma subtypes responsive to ICIs is crucial. We performed clustering analyses to identify immune subtypes of melanoma based on the enrichment levels of 28 immune cells using transcriptome datasets for six melanoma cohorts, including four cohorts not treated with ICIs and two cohorts treated with ICIs. We identified three immune subtypes (Im-H, Im-M, and Im-L), reproducible in these cohorts. Im-H displayed strong immune signatures, low stemness and proliferation potential, genomic stability, high immunotherapy response rate, and favorable prognosis. Im-L showed weak immune signatures, high stemness and proliferation potential, genomic instability, low immunotherapy response rate, and unfavorable prognosis. The pathways highly enriched in Im-H included immune, MAPK, apoptosis, calcium, VEGF, cell adhesion molecules, focal adhesion, gap junction, and PPAR. The pathways highly enriched in Im-L included Hippo, cell cycle, and ErbB. Copy number alterations correlated inversely with immune signatures in melanoma, while tumor mutation burden showed no significant correlation. The molecular features correlated with favorable immunotherapy response included immune-promoting signatures and pathways of PPAR, MAPK, VEGF, calcium, and glycolysis/gluconeogenesis. Our data recapture the immunological heterogeneity in melanoma and provide clinical implications for the immunotherapy of melanoma.

MicroRNA-regulated transcriptome analysis identifies four major subtypes with prognostic and therapeutic implications in prostate cancer.

MicroRNA (miRNA) deregulation plays a critical role in the heterogeneous development of prostate cancer (PCa) by tuning mRNA levels. Herein, we aimed to characterize the molecular features of PCa by clustering the miRNA-regulated transcriptome with non-negative matrix factorization. Using 478 PCa samples from The Cancer Genome Atlas, four molecular subtypes (S-I, S-II, S-III, and S-IV) were identified and validated in two merged microarray and RNAseq datasets with 656 and 252 samples, respectively. Interestingly, the four subtypes showed distinct clinical and biological features after comprehensive analyses of clinical features, multiomic profiles, immune infiltration, and drug sensitivity. S-I is basal/stem/mesenchymal-like and immune-excluded with marked transforming growth factor ß, epithelial-mesenchymal transition and hypoxia signals, increased sensitivity to olaparib, and intermediate prognosis. S-II is luminal/metabolism-active and responsive to androgen deprivation therapy with frequent TMPRSS2-ERG fusion and a good prognosis. S-III is characterized by moderate proliferative and metabolic activity, sensitivity to taxane-based chemotherapy, and intermediate prognosis. S-IV is highly proliferative with moderate EMT and stemness, frequent deletions of TP53, PTEN and RB, and the poorest prognosis; it is also immune-inflamed and sensitive to anti-PD-L1 therapy. Overall, based on miRNA-regulated gene profiles, this study identified four distinct PCa subtypes that could improve risk stratification at diagnosis and provide therapeutic guidance.

Correlate the TP53 Mutation and the HRAS Mutation with Immune Signatures in Head and Neck Squamous Cell Cancer.

Although immunotherapy has emerged as an effective therapeutic strategy for various cancers including head and neck squamous cell carcinomas (HNSCCs), only a subset of patients can benefit from such therapy. Hence, it is pressing to discover predictive biomarkers for cancer immunotherapy response. TP53 and HRAS mutations frequently occur in HNSCC and correlate with a worse prognosis in HNSCC. We extensively characterized the associations of TP53 mutations and HRAS mutations with HNSCC immunity based on multiple cancer genomics datasets. We compared the enrichment levels of 20 immune signatures between TP53-mutated and TP53-wildtype HNSCCs, and between HRAS-mutated and HRAS-wildtype HNSCCs, and found that TP53 mutations were associated with depressed immune signatures while HRAS mutations were associated with enhanced immune signatures in HNSCC. Moreover, we found multiple p53- and RAS-mediated pathways showing significant correlations with HNSCC immunity. Furthermore, we demonstrated that the association between TP53 mutation and tumor immunity was independent of the human papillomavirus (HPV) infection and smoking status in HNSCC. These data suggest that p53 and RAS may play important roles in regulating HNSCC immunity and that the TP53 and HRAS mutation status could be useful biomarkers for stratifying HNSCC patients responsive to immunotherapy.