Prognostic value of B cells in cutaneous melanoma

Background: Measures of the adaptive immune response have prognostic and predictive associations in melanoma and other cancer types. Specifically, intratumoral T cell density and function have considerable prognostic and predictive value in skin cutaneous melanoma (SKCM). Less is known about the significance of tumor-infiltrating B cells in SKCM. Our goal was to understand the prognostic and predictive value of B cell phenotypic subsets in SKCM using RNA sequencing. Methods: We used our previously published algorithm, V'DJer, to assemble B cell receptor (BCR) repertoires and estimate diversity from short-read RNA sequencing (RNA-seq). We applied machine learning-based cellular phenotype classifiers to measure relative similarity of bulk tumor sample gene expression profiles and different B cell phenotypes. We assessed these aspects of B cell biology in 473 SKCM from the Cancer Genome Atlas Project (TCGA) as well as in RNA-seq data corresponding to tumor samples procured from patients who received CTLA-4 and PD-1 inhibitors for metastatic SKCM. Results: We found that the BCR repertoire was associated with different clinical factors, such as tumor tissue site and sex. However, increased clonality of the BCR repertoire was favorably prognostic in SKCM and was prognostic even after first conditioning on various clinical factors. Mutation burden was not correlated with any BCR measurement, and no specific mutation had an altered BCR repertoire. Lack of an assembled BCR in pre-treatment tumor tissues was associated with a lack of anti-tumor response to a CTLA-4 inhibitor in metastatic SKCM. Conclusions: These findings suggest an important prognostic and predictive role for B cell characteristics in SKCM. This has implications for melanoma immunobiology and potential development of immunogenomics features to predict survival and response to immunotherapy

Identifying transcriptional profiles and evaluating prognostic biomarkers of HIV-associated diffuse large B-cell lymphoma from Malawi

Lymphoma incidence in sub-Saharan Africa (SSA) is increasing due to HIV and population aging. Diffuse Large B-cell lymphoma (DLBCL), the most common lymphoma in SSA and worldwide, is highly associated with HIV, but molecular studies of HIV-associated DLBCL are scarce globally. We describe profiling of DLBCL from Malawi, aiming to elucidate tumor biology and identify clinically meaningful biomarkers specifically for SSA. Between June 1, 2013 and June 1, 2016, 59 cases of DLBCL (32 HIV+/27 HIV−) enrolled in the Kamuzu Central Hospital Lymphoma Study were characterized, of which 54 (92%) were negative for Epstein–Barr virus. Gene expression profiling (GEP) by whole transcriptome sequencing was performed on the first 36 cases (22 HIV+/14 HIV−). Immunohistochemistry (IHC) and GEP results were compared with published data and correlated to clinical outcome and pathologic features. Unsupervised clustering strongly segregated DLBCL by HIV status (p = 0.0003, Chi-squared test), indicating a marked contribution of HIV to expression phenotype. Pathway analysis identified that HIV-associated tumors were enriched in hypoxia, oxidative stress, and metabolism related gene expression patterns. Cell-of-origin subtype, determined by sequencing and IHC, did not associate with differences in overall survival (OS), while Ki-67 proliferation index ≥80% was associated with inferior OS in HIV+ DLBCL only (p = 0.03) and cMYC/BCL2 co-expression by IHC was negatively prognostic across the entire cohort (p = 0.01). This study provides among the first molecular characterizations of DLBCL from SSA, demonstrates marked gene expression differences by HIV status, and identifies genomic and immunophenotypic characteristics that can inform future basic and clinical investigations

A Gene Expression Panel is Accurate for Diagnosis and Monitoring Treatment of Eosinophilic Esophagitis in Adults

Eosinophilic esophagitis (EoE) can be difficult to diagnose. We aimed to evaluate whether a gene expression score could differentiate adult EoE cases from non-EoE controls and to determine whether scores normalized after treatment for EoE

Molecular and clinical characterization of a claudin-low subtype of gastric cancer

Purpose Claudin-low molecular subtypes have been identified in breast and bladder cancers and are characterized by low expression of claudins, enrichment for epithelial-to-mesenchymal transition (EMT), and tumor-initiating cell (TIC) features. We evaluated whether the claudin-low subtype also exists in gastric cancer. Materials and Methods Four hundred fifteen tumors from The Cancer Genome Atlas (TCGA) gastric cancer mRNA data set were clustered on the claudin, EMT, and TIC gene sets to identify claudin-low tumors. We derived a 24-gene predictor that classifies gastric cancer into claudin-low and non-claudin-low subtypes. This predictor was validated with the Asian Cancer Research Group(ACRG)data set. We characterized molecular and clinical features of claudin-low tumors. Results We identified 46 tumors that had consensus enrichment for claudin-low features in TCGA data set. Claudin-low tumors were most commonly diffuse histologic type (82%) and originally classified as TCGA genomically stable(GS)subtype (78%). Compared with GS subtype, claudin-low subtype had significant activation in Rho family of GTPases signaling, which appears to play a key role in its EMT and TIC properties. In the ACRG data set, 28 of 300 samples were classified as claudin-low tumors by the 24-gene predictor and were phenotypically similar to the initially derived claudin-low tumors. Clinically, claudin-low subtype had the worst overall survival. Of note, the hazard ratios that compared claudin-low versus GS subtype were 2.10 (95% CI, 1.07 to 4.11) in TCGA and 2.32 (95% CI, 1.18 to 4.55) in the ACRG cohorts, with adjustment for age and pathologic stage. Conclusion We identified a gastric claudin-low subtype that carries a poor prognosis likely related to therapeutic resistance as a result of its EMT and TIC phenotypes

Machine-learning prediction of tumor antigen immunogenicity in the selection of therapeutic epitopes

Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and select for potential epitope targets. These algorithms do not predict for epitope immunogenicity using approaches modeled from tumor-specific antigen data. Here, we describe peptide-intrinsic biochemical features associated with neoantigen and minor histocompatibility mismatch antigen immunogenicity and present a gradient boosting algorithm for predicting tumor antigen immunogenicity. This algorithm was validated in two murine tumor models and demonstrated the capacity to select for therapeutically active antigens. Immune correlates of neoantigen immunogenicity were studied in a pan-cancer data set from The Cancer Genome Atlas and demonstrated an association between expression of immunogenic neoantigens and immunity in colon and lung adenocarcinomas. Lastly, we present evidence for expression of an out-of-frame neoantigen that was capable of driving antitumor cytotoxic T-cell responses. With the growing clinical importance of tumor vaccine therapies, our approach may allow for better selection of therapeutically relevant tumor-specific antigens, including nonclas-sic out-of-frame antigens capable of driving antitumor immunity

An Immunocompetent Mouse Model of HPV16(+) Head and Neck Squamous Cell Carcinoma

The incidence of human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) is increasing and implicated in more than 60% of all oropharyngeal carcinomas (OPSCCs). Although whole-genome, transcriptome, and proteome analyses have identified altered signaling pathways in HPV-induced HNSCCs, additional tools are needed to investigate the unique pathobiology of OPSCC. Herein, bioinformatics analyses of human HPV(+) HNSCCs revealed that all tumors express full-length E6 and identified molecular subtypes based on relative E6 and E7 expression levels. To recapitulate the levels, stoichiometric ratios, and anatomic location of E6/E7 expression, we generated a genetically engineered mouse model whereby balanced expression of E6/E7 is directed to the oropharyngeal epithelium. The addition of a mutant PIK3CAE545K allele leads to the rapid development of pre-malignant lesions marked by immune cell accumulation, and a subset of these lesions progress to OPSCC. This mouse provides a faithful immunocompetent model for testing treatments and investigating mechanisms of immunosuppression

Consequential considerations when mapping tRNA fragments

We examine several of the choices that went into the design of tDRmapper, a recently reported tool for identifying transfer RNA (tRNA) fragments in deep sequencing data, evaluate them in the context of currently available knowledge, and discuss their potential impact on the output that the tool generates

A Novel Intronic Single Nucleotide Polymorphism in the Myosin heavy polypeptide 4 Gene Is Responsible for the Mini-Muscle Phenotype Characterized by Major Reduction in Hind-Limb Muscle Mass in Mice

Replicated artificial selection for high levels of voluntary wheel running in an outbred strain of mice favored an autosomal recessive allele whose primary phenotypic effect is a 50% reduction in hind-limb muscle mass. Within the High Runner (HR) lines of mice, the numerous pleiotropic effects (e.g., larger hearts, reduced total body mass and fat mass, longer hind-limb bones) of this hypothesized adaptive allele include functional characteristics that facilitate high levels of voluntary wheel running (e.g., doubling of mass-specific muscle aerobic capacity, increased fatigue resistance of isolated muscles, longer hind-limb bones). Previously, we created a backcross population suitable for mapping the responsible locus. We phenotypically characterized the population and mapped the Minimsc locus to a 2.6-Mb interval on MMU11, a region containing ∼100 known or predicted genes. Here, we present a novel strategy to identify the genetic variant causing the mini-muscle phenotype. Using high-density genotyping and whole-genome sequencing of key backcross individuals and HR mice with and without the mini-muscle mutation, from both recent and historical generations of the HR lines, we show that a SNP representing a C-to-T transition located in a 709-bp intron between exons 11 and 12 of the Myosin heavy polypeptide 4 (Myh4) skeletal muscle gene (position 67,244,850 on MMU11; assembly, December 2011, GRCm38/mm10; ENSMUSG00000057003) is responsible for the mini-muscle phenotype, Myh4Minimsc. Using next-generation sequencing, our approach can be extended to identify causative mutations arising in mouse inbred lines and thus offers a great avenue to overcome one of the most challenging steps in quantitative genetics

FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease

Mechanisms driving tumor progression from less aggressive subtypes to more aggressive states represent key targets for therapy. We identified a subset of luminal A primary breast tumors that give rise to HER2-enriched (HER2E) subtype metastases, but remain clinically HER2 negative (cHER2-). By testing the unique genetic and transcriptomic features of these cases, we developed the hypothesis that FGFR4 likely participates in this subtype switching. To evaluate this, we developed 2 FGFR4 genomic signatures using a patient-derived xenograft (PDX) model treated with an FGFR4 inhibitor, which inhibited PDX growth in vivo. Bulk tumor gene expression analysis and single-cell RNA sequencing demonstrated that the inhibition of FGFR4 signaling caused molecular switching. In the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohort, FGFR4-induced and FGFR4-repressed signatures each predicted overall survival. Additionally, the FGFR4-induced signature was an independent prognostic factor beyond subtype and stage. Supervised analysis of 77 primary tumors with paired metastases revealed that the FGFR4-induced signature was significantly higher in luminal/ER+ tumor metastases compared with their primaries. Finally, multivariate analysis demonstrated that the FGFR4- induced signature also predicted site-specific metastasis for lung, liver, and brain, but not for bone or lymph nodes. These data identify a link between FGFR4-regulated genes and metastasis, suggesting treatment options for FGFR4-positive patients, whose high expression is not caused by mutation or amplification

Combating subclonal evolution of resistant cancer phenotypes

Metastatic breast cancer remains challenging to treat, and most patients ultimately progress on therapy. This acquired drug resistance is largely due to drug-refractory sub-populations (subclones) within heterogeneous tumors. Here, we track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment, including enhanced mesenchymal and growth factor signaling, which may promote drug resistance, and decreased antigen presentation and TNF-α signaling, which may enable immune system avoidance. Some of these phenotypes pre-exist in pre-treatment subclones that become dominant after chemotherapy, indicating selection for resistance phenotypes. Post-chemotherapy cancer cells are effectively treated with drugs targeting acquired phenotypes. These findings highlight cancer's ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves