Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer.

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.

Protocol for bulk RNA sequencing of enriched human neutrophils from whole blood and estimation of sample purity.

Although neutrophils are the most abundant leukocyte in healthy individuals and impact outcomes of diseases ranging from sepsis to cancer, they remain understudied due to technical constraints of isolation, preservation, and sequencing. We present a modified Smart-Seq2 protocol for bulk RNA sequencing of neutrophils enriched from whole blood. We describe steps for neutrophil isolation, cDNA generation, library preparation, and sample purity estimation via a bioinformatic approach. Our approach permits the collection of large cohorts and enables detection of neutrophil transcriptomic subtypes. For complete details on the use and execution of this protocol, please refer to LaSalle et al. (2022)1 and Boribong et al. (2022).2.

In vivo CRISPR screens reveal the landscape of immune evasion pathways across cancer.

The immune system can eliminate tumors, but checkpoints enable immune escape. Here, we identify immune evasion mechanisms using genome-scale in vivo CRISPR screens across cancer models treated with immune checkpoint blockade (ICB). We identify immune evasion genes and important immune inhibitory checkpoints conserved across cancers, including the non-classical major histocompatibility complex class I (MHC class I) molecule Qa-1b/HLA-E. Surprisingly, loss of tumor interferon-γ (IFNγ) signaling sensitizes many models to immunity. The immune inhibitory effects of tumor IFN sensing are mediated through two mechanisms. First, tumor upregulation of classical MHC class I inhibits natural killer cells. Second, IFN-induced expression of Qa-1b inhibits CD8+ T cells via the NKG2A/CD94 receptor, which is induced by ICB. Finally, we show that strong IFN signatures are associated with poor response to ICB in individuals with renal cell carcinoma or melanoma. This study reveals that IFN-mediated upregulation of classical and non-classical MHC class I inhibitory checkpoints can facilitate immune escape.

Landscape of helper and regulatory antitumour CD4+ T cells in melanoma.

Within the tumour microenvironment, CD4+ T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules1,2, but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4+ T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4+ T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4+ T regulatory (TReg) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4+ TReg clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4+ T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4+ TReg cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma.

Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

Implementation of a prostate cancer-specific targeted sequencing panel for credentialing of patient-derived cell lines and genomic characterization of patient samples.

BACKGROUND: Primary and metastatic prostate cancers have low mutation rates and recurrent alterations in a small set of genes, enabling targeted sequencing of prostate cancer-associated genes as an efficient approach to characterizing patient samples (compared to whole-exome and whole-genome sequencing). For example, targeted sequencing provides a flexible, rapid, and cost-effective method for genomic assessment of patient-derived cell lines to evaluate fidelity to initial patient tumor samples. METHODS: We developed a prostate cancer-specific targeted next-generation sequencing (NGS) panel to detect alterations in 62 prostate cancer-associated genes as well as recurring gene fusions with ETS family members, representing the majority of common alterations in prostate cancer. We tested this panel on primary prostate cancer tissues and blood biopsies from patients with metastatic prostate cancer. We generated patient-derived cell lines from primary prostate cancers using conditional reprogramming methods and applied targeted sequencing to evaluate the fidelity of these cell lines to the original patient tumors. RESULTS: The prostate cancer-specific panel identified biologically and clinically relevant alterations, including point mutations in driver oncogenes and ETS family fusion genes, in tumor tissues from 29 radical prostatectomy samples. The targeted panel also identified genomic alterations in cell-free DNA and circulating tumor cells (CTCs) from patients with metastatic prostate cancer, and in standard prostate cancer cell lines. We used the targeted panel to sequence our set of patient-derived cell lines; however, no prostate cancer-specific mutations were identified in the tumor-derived cell lines, suggesting preferential outgrowth of normal prostate epithelial cells. CONCLUSIONS: We evaluated a prostate cancer-specific targeted NGS panel to detect common and clinically relevant alterations (including ETS family gene fusions) in prostate cancer. The panel detected driver mutations in a diverse set of clinical samples of prostate cancer, including fresh-frozen tumors, cell-free DNA, CTCs, and cell lines. Targeted sequencing of patient-derived cell lines highlights the challenge of deriving cell lines from primary prostate cancers and the importance of genomic characterization to credential candidate cell lines. Our study supports that a prostate cancer-specific targeted sequencing panel provides an efficient, clinically feasible approach to identify genetic alterations across a spectrum of prostate cancer samples and cell lines.

Genome-scale screens identify factors regulating tumor cell responses to natural killer cells.

To systematically define molecular features in human tumor cells that determine their degree of sensitivity to human allogeneic natural killer (NK) cells, we quantified the NK cell responsiveness of hundreds of molecularly annotated 'DNA-barcoded' solid tumor cell lines in multiplexed format and applied genome-scale CRISPR-based gene-editing screens in several solid tumor cell lines, to functionally interrogate which genes in tumor cells regulate the response to NK cells. In these orthogonal studies, NK cell-sensitive tumor cells tend to exhibit 'mesenchymal-like' transcriptional programs; high transcriptional signature for chromatin remodeling complexes; high levels of B7-H6 (NCR3LG1); and low levels of HLA-E/antigen presentation genes. Importantly, transcriptional signatures of NK cell-sensitive tumor cells correlate with immune checkpoint inhibitor (ICI) resistance in clinical samples. This study provides a comprehensive map of mechanisms regulating tumor cell responses to NK cells, with implications for future biomarker-driven applications of NK cell immunotherapies.

Modeling clonal structure over narrow time frames via circulating tumor DNA in metastatic breast cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) offers minimally invasive means to repeatedly interrogate tumor genomes, providing opportunities to monitor clonal dynamics induced by metastasis and therapeutic selective pressures. In metastatic cancers, ctDNA profiling allows for simultaneous analysis of both local and distant sites of recurrence. Despite the promise of ctDNA sampling, its utility in real-time genetic monitoring remains largely unexplored. METHODS: In this exploratory analysis, we characterize high-frequency ctDNA sample series collected over narrow time frames from seven patients with metastatic triple-negative breast cancer, each undergoing treatment with Cabozantinib, a multi-tyrosine kinase inhibitor (NCT01738438, https://clinicaltrials.gov/ct2/show/NCT01738438 ). Applying orthogonal whole exome sequencing, ultra-low pass whole genome sequencing, and 396-gene targeted panel sequencing, we analyzed 42 plasma-derived ctDNA libraries, representing 4-8 samples per patient with 6-42 days between samples. Integrating tumor fraction, copy number, and somatic variant information, we model tumor clonal dynamics, predict neoantigens, and evaluate consistency of genomic information from orthogonal assays. RESULTS: We measured considerable variation in ctDNA tumor faction in each patient, often conflicting with RECIST imaging response metrics. In orthogonal sequencing, we found high concordance between targeted panel and whole exome sequencing in both variant detection and variant allele frequency estimation (specificity = 95.5%, VAF correlation, r = 0.949), Copy number remained generally stable, despite resolution limitations posed by low tumor fraction. Through modeling, we inferred and tracked distinct clonal populations specific to each patient and built phylogenetic trees revealing alterations in hallmark breast cancer drivers, including TP53, PIK3CA, CDK4, and PTEN. Our modeling revealed varied responses to therapy, with some individuals displaying stable clonal profiles, while others showed signs of substantial expansion or reduction in prevalence, with characteristic alterations of varied literature annotation in relation to the study drug. Finally, we predicted and tracked neoantigen-producing alterations across time, exposing translationally relevant detection patterns. CONCLUSIONS: Despite technical challenges arising from low tumor content, metastatic ctDNA monitoring can aid our understanding of response and progression, while minimizing patient risk and discomfort. In this study, we demonstrate the potential for high-frequency monitoring of evolving genomic features, providing an important step toward scalable, translational genomics for clinical decision making.

The Lipogenic Regulator SREBP2 Induces Transferrin in Circulating Melanoma Cells and Suppresses Ferroptosis.

Circulating tumor cells (CTC) are shed by cancer into the bloodstream, where a viable subset overcomes oxidative stress to initiate metastasis. We show that single CTCs from patients with melanoma coordinately upregulate lipogenesis and iron homeostasis pathways. These are correlated with both intrinsic and acquired resistance to BRAF inhibitors across clonal cultures of BRAF-mutant CTCs. The lipogenesis regulator SREBP2 directly induces transcription of the iron carrier Transferrin (TF), reducing intracellular iron pools, reactive oxygen species, and lipid peroxidation, thereby conferring resistance to inducers of ferroptosis. Knockdown of endogenous TF impairs tumor formation by melanoma CTCs, and their tumorigenic defects are partially rescued by the lipophilic antioxidants ferrostatin-1 and vitamin E. In a prospective melanoma cohort, presence of CTCs with high lipogenic and iron metabolic RNA signatures is correlated with adverse clinical outcome, irrespective of treatment regimen. Thus, SREBP2-driven iron homeostatic pathways contribute to cancer progression, drug resistance, and metastasis. SIGNIFICANCE: Through single-cell analysis of primary and cultured melanoma CTCs, we have uncovered intrinsic cancer cell heterogeneity within lipogenic and iron homeostatic pathways that modulates resistance to BRAF inhibitors and to ferroptosis inducers. Activation of these pathways within CTCs is correlated with adverse clinical outcome, pointing to therapeutic opportunities.This article is highlighted in the In This Issue feature, p. 521.

KIR3DL3 Is an Inhibitory Receptor for HHLA2 that Mediates an Alternative Immunoinhibitory Pathway to PD1.

Blockade of the PD1 pathway is a broadly effective cancer therapy, but additional immune-inhibitory pathways contribute to tumor immune evasion. HERV-H LTR-associating 2 (HHLA2; also known as B7H5 and B7H7) is a member of the B7 family of immunoregulatory ligands that mediates costimulatory effects through its interaction with the CD28 family member transmembrane and immunoglobulin domain containing 2 (TMIGD2). However, HHLA2 has also been known to have inhibitory effects on T cells. Here, we report that we have identified killer cell immunoglobulin-like receptor, three immunoglobulin domains and long cytoplasmic tail 3 (KIR3DL3) as an inhibitory receptor for HHLA2 in T cells and natural killer (NK) cells and have generated HHLA2 and KIR3DL3 antibodies that block the immune-inhibitory activity of HHLA2, preserving the costimulatory signal. It is known that HHLA2 is frequently expressed in several tumor types, including clear cell renal cell carcinoma (ccRCC). We found that HHLA2 expression was nonoverlapping with PDL1 expression in ccRCC, suggesting that HHLA2 mediates a mechanism of tumor immune evasion that is independent from PDL1. Blockade of both the PD1 and KIR3DL3 pathways may be a more effective way to reverse tumor immune evasion.See related Spotlight on p. 128.

Distinct evolutionary paths in chronic lymphocytic leukemia during resistance to the graft-versus-leukemia effect.

Leukemic relapse remains a major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis for relapse of advanced lymphoid malignancies remains incompletely understood and may involve escape from the graft-versus-leukemia (GvL) effect. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features influence transplant outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic, and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics. Early relapses after allo-HSCT exhibited notable genetic stability; single CLL cell transcriptional analysis demonstrated a cellular heterogeneity that was static over time. In contrast, CLL cells relapsing late after allo-HSCT displayed notable genetic evolution and evidence of neoantigen depletion, consistent with marked single-cell transcriptional shifts that were unique to each patient. We observed a greater rate of epigenetic change for late relapses not seen in early relapses or relapses after chemotherapy alone, suggesting that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for human leukocyte antigen (HLA) loss was observed, even when present in pretransplant subpopulations. Gain of stem cell modules was a common signature associated with leukemia relapse regardless of posttransplant relapse kinetics. These data elucidate the biological pathways that underlie GvL resistance and posttransplant relapse.

Y-box binding protein 1 acts as a negative regulator of stearoyl CoA desaturase 1 in clear cell renal cell carcinoma.

Y-box binding protein 1 (YB-1) is a regulatory protein associated with oncogenesis and poor prognosis in patients with cancer. In the cell, YB-1 functions as a DNA and RNA binding protein that promotes or suppresses expression of target genes. The cancer-promoting activity of YB-1 is mediated through its activation of oncogenes and repression of tumor suppressor genes. Lipogenic enzyme stearoyl-CoA desaturase (SCD1) drives the production of endogenous monounsaturated fatty acids (MUFAs) in cells and protects against toxic buildup of saturated fatty acids. Clear cell renal cell carcinoma (ccRCC) is often characterized by aberrantly high SCD1 expression and cytosolic accumulation of unsaturated fatty acids. In the present study, a proteomics screen of cells treated with inhibitors of SCD1 supported a potential relationship between YB-1 and SCD1. It was revealed that the presence of MUFAs led to increased protein synthesis and increased expression of high molecular weight forms of YB-1 in ccRCC cells, but not in non-tumorigenic cells. Ectopic expression of YB-1 led to decreased expression levels of SCD1 protein and mRNA in ccRCC cell lines. Conversely, targeted knockdown of YB-1 increased SCD1 mRNA abundance. Analysis of ccRCC patient data from The Cancer Proteome Atlas database showed YB-1 expression was negatively associated with survival, whereas SCD1 was associated with improved survival. These data suggested an antagonistic relationship between YB-1 and SCD1 that may influence survival of patients with ccRCC.

Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer.

PURPOSE: To identify clinically relevant mechanisms of resistance to ER-directed therapies in ER+ breast cancer. EXPERIMENTAL DESIGN: We conducted a genome-scale functional screen spanning 10,135 genes to investigate genes whose overexpression confer resistance to selective estrogen receptor degraders. In parallel, we performed whole-exome sequencing in paired pretreatment and postresistance biopsies from 60 patients with ER+ metastatic breast cancer who had developed resistance to ER-targeted therapy. Furthermore, we performed experiments to validate resistance genes/pathways and to identify drug combinations to overcome resistance. RESULTS: Pathway analysis of candidate resistance genes demonstrated that the FGFR, ERBB, insulin receptor, and MAPK pathways represented key modalities of resistance. The FGFR pathway was altered via FGFR1, FGFR2, or FGF3 amplifications or FGFR2 mutations in 24 (40%) of the postresistance biopsies. In 12 of the 24 postresistance tumors exhibiting FGFR/FGF alterations, these alterations were acquired or enriched under the selective pressure of ER-directed therapy. In vitro experiments in ER+ breast cancer cells confirmed that FGFR/FGF alterations led to fulvestrant resistance as well as cross-resistance to the CDK4/6 inhibitor palbociclib. RNA sequencing of resistant cell lines demonstrated that FGFR/FGF induced resistance through ER reprogramming and activation of the MAPK pathway. The resistance phenotypes were reversed by FGFR inhibitors, a MEK inhibitor, and/or a SHP2 inhibitor. CONCLUSIONS: Our results suggest that FGFR pathway is a distinct mechanism of acquired resistance to ER-directed therapy that can be overcome by FGFR and/or MAPK pathway inhibitors.

Discovery of a heme-binding domain in a neuronal voltage-gated potassium channel.

The EAG (ether-à-go-go) family of voltage-gated K+ channels are important regulators of neuronal and cardiac action potential firing (excitability) and have major roles in human diseases such as epilepsy, schizophrenia, cancer, and sudden cardiac death. A defining feature of EAG (Kv10-12) channels is a highly conserved domain on the N terminus, known as the eag domain, consisting of a Per-ARNT-Sim (PAS) domain capped by a short sequence containing an amphipathic helix (Cap domain). The PAS and Cap domains are both vital for the normal function of EAG channels. Using heme-affinity pulldown assays and proteomics of lysates from primary cortical neurons, we identified that an EAG channel, hERG3 (Kv11.3), binds to heme. In whole-cell electrophysiology experiments, we identified that heme inhibits hERG3 channel activity. In addition, we expressed the Cap and PAS domain of hERG3 in Escherichia coli and, using spectroscopy and kinetics, identified the PAS domain as the location for heme binding. The results identify heme as a regulator of hERG3 channel activity. These observations are discussed in the context of the emerging role for heme as a regulator of ion channel activity in cells.

Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer.

PURPOSE: Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing. EXPERIMENTAL DESIGN: We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ER+/HER2- metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples. RESULTS: Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median = 57; range = 2-346). Clinical sensitivity was 81% (n = 13/16) in newly diagnosed MBC, 23% (n = 7/30) at postoperative and 19% (n = 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR = 20.8; 95% confidence interval, 7.3-58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4-39.2 months). CONCLUSIONS: Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track.

Genomic and immune profiling of pre-invasive lung adenocarcinoma.

Adenocarcinoma in situ and minimally invasive adenocarcinoma are the pre-invasive forms of lung adenocarcinoma. The genomic and immune profiles of these lesions are poorly understood. Here we report exome and transcriptome sequencing of 98 lung adenocarcinoma precursor lesions and 99 invasive adenocarcinomas. We have identified EGFR, RBM10, BRAF, ERBB2, TP53, KRAS, MAP2K1 and MET as significantly mutated genes in the pre/minimally invasive group. Classes of genome alterations that increase in frequency during the progression to malignancy are revealed. These include mutations in TP53, arm-level copy number alterations, and HLA loss of heterozygosity. Immune infiltration is correlated with copy number alterations of chromosome arm 6p, suggesting a link between arm-level events and the tumor immune environment.

The Cancer Genome Atlas Expression Subtypes Stratify Response to Checkpoint Inhibition in Advanced Urothelial Cancer and Identify a Subset of Patients with High Survival Probability.

Analysis of the IMvigor 210 trials involving patients with platinum-refractory or cisplatin-ineligible urothelial carcinoma who were treated with the PD-L1 inhibitor atezolizumab identified a resistance signature as an immune biomarker. Transcriptome profiling of 368 tumor samples from this trial revealed that the "genomically unstable" Lund subtype classification was associated with the best response. We developed and applied a novel single-patient subtype classifier based on The Cancer Genome Atlas 2017 expression-based molecular subtypes. We identified 11 patients with a neuronal subtype, with a 100% response rate in eight confirmed cases (2 complete response, 6 partial response), and 72% overall, including 3/11 patients with an unconfirmed response. The survival probability was extraordinarily high for the neuronal subtype, which represents a high-risk cohort with advanced disease, and may be secondary to low levels of TGFß expression and high mutation/neoantigen burden. PATIENT SUMMARY: We describe a methodology for genomic classification of an individual patient's bladder cancer tumor and have identified a subtype that is associated with a high response rate to immunotherapy. This is an important step forward in identifying the right treatment for the right patient, which is the goal of personalized precision medicine.