Venetoclax and Cobimetinib in Relapsed/Refractory AML: A Phase 1b Trial.

BACKGROUND: Therapies for relapsed/refractory acute myeloid leukemia remain limited and outcomes poor, especially amongst patients who are ineligible for cytotoxic chemotherapy or targeted therapies. PATIENTS AND METHODS: This phase 1b trial evaluated venetoclax, a B-cell lymphoma-2 (BCL-2) inhibitor, plus cobimetinib, a MEK1/2 inhibitor, in patients with relapsed/refractory acute myeloid leukemia, ineligible for cytotoxic chemotherapy. Two-dimensional dose-escalation was performed for venetoclax dosed daily, and for cobimetinib dosed on days 1-21 of each 28-day cycle. RESULTS: Thirty patients (median [range] age: 71.5 years [60-84]) received venetoclax-cobimetinib. The most common adverse events (AEs; in ≥40.0% of patients) were diarrhea (80.0%), nausea (60.0%), vomiting (40.0%), febrile neutropenia (40.0%), and fatigue (40.0%). Overall, 66.7% and 23.3% of patients experienced AEs leading to dose modification/interruption or treatment withdrawal, respectively. The composite complete remission (CRc) rate (complete remission [CR] + CR with incomplete blood count recovery + CR with incomplete platelet recovery) was 15.6%; antileukemic response rate (CRc + morphologic leukemia-free state/partial remission) was 18.8%. For the recommended phase 2 dose (venetoclax: 600 mg; cobimetinib: 40 mg), CRc and antileukemic response rates were both 12.5%. Failure to achieve an antileukemic response was associated with elevated baseline phosphorylated ERK and MCL-1 levels, but not BCL-xL. Baseline mutations in ≥1 signaling gene or TP53 were noted in nonresponders and emerged on treatment. Pharmacodynamic biomarkers revealed inconsistent, transient inhibition of the mitogen-activated protein kinase (MAPK) pathway. CONCLUSION: Venetoclax-cobimetinib showed limited preliminary efficacy similar to single-agent venetoclax, but with added toxicity. Our findings will inform future trials of BCL-2/MAPK pathway inhibitor combinations.

Immune heterogeneity in small-cell lung cancer and vulnerability to immune checkpoint blockade.

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.

Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM.

Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.

Safety and efficacy of zinpentraxin alfa as monotherapy or in combination with ruxolitinib in myelofibrosis: stage I of a phase II trial.

Pentraxin 2 (PTX-2; serum amyloid P component), a circulating endogenous regulator of the inflammatory response to tissue injury and fibrosis, is reduced in patients with myelofibrosis (MF). Zinpentraxin alfa (RO7490677, PRM-151) is a recombinant form of PTX-2 that has shown preclinical antifibrotic activity and no dose-limiting toxicities in phase I trials. We report results from stage 1 of a phase II trial of zinpentraxin alfa in patients with intermediate-1/2 or high-risk MF. Patients (n=27) received intravenous zinpentraxin α weekly (QW) or every 4 weeks (Q4W), as monotherapy or an additional therapy for patients on stable-dose ruxolitinib. The primary endpoint was overall response rate (ORR; investigatorassessed) adapted from International Working Group-Myeloproliferative Neoplasms Research and Treatment criteria. Secondary endpoints included modified Myeloproliferative Neoplasm-Symptom Assessment Form Total Symptom Score (MPN-SAF TSS) change, bone marrow (BM) MF grade reduction, pharmacokinetics, and safety. ORR at week 24 was 33% (n=9/27) and varied across individual cohorts (QW: 38% [3/8]; Q4W: 14% [1/7]; QW+ruxolitinib: 33% [2/6]; Q4W+ruxolitinib: 50% [3/6]). Five of 18 evaluable patients (28%) experienced a ≥50% reduction in MPN-SAF TSS, and six of 17 evaluable patients (35%) had a ≥1 grade improvement from baseline in BM fibrosis at week 24. Most treatment-emergent adverse events (AE) were grade 1-2, most commonly fatigue. Among others, anemia and thrombocytopenia were infrequent (n=3 and n=1, respectively). Treatment-related serious AE occurred in four patients (15%). Overall, zinpentraxin alfa showed evidence of clinical activity and tolerable safety as monotherapy and in combination with ruxolitinib in this open-label, non-randomized trial (clinicaltrials gov. Identifier: NCT01981850).

Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial.

PURPOSE: To explore whether patients with BRCA1/2-mutated or homologous recombination deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. PATIENTS AND METHODS: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. Programmed death-ligand 1 (PD-L1) status of tumor-infiltrating immune cells (IC) was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥ 16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. RESULTS: Among biomarker-evaluable samples, 22% (234/1,050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1,024) had TMB ≥10 mut/Mb, and 0.3% (3/1,022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on ICs) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. CONCLUSIONS: Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors. See related commentary by Al-Rawi et al., p. 1645.

CD8+ T cell-intrinsic IL-6 signaling promotes resistance to anti-PD-L1 immunotherapy.

Although immune checkpoint inhibitors (ICIs) are established as effective cancer therapies, overcoming therapeutic resistance remains a critical challenge. Here we identify interleukin 6 (IL-6) as a correlate of poor response to atezolizumab (anti-PD-L1) in large clinical trials of advanced kidney, breast, and bladder cancers. In pre-clinical models, combined blockade of PD-L1 and the IL-6 receptor (IL6R) causes synergistic regression of large established tumors and substantially improves anti-tumor CD8+ cytotoxic T lymphocyte (CTL) responses compared with anti-PD-L1 alone. Circulating CTLs from cancer patients with high plasma IL-6 display a repressed functional profile based on single-cell RNA sequencing, and IL-6-STAT3 signaling inhibits classical cytotoxic differentiation of CTLs in vitro. In tumor-bearing mice, CTL-specific IL6R deficiency is sufficient to improve anti-PD-L1 activity. Thus, based on both clinical and experimental evidence, agents targeting IL-6 signaling are plausible partners for combination with ICIs in cancer patients.

Tetramer-aided sorting and single-cell RNA sequencing facilitate transcriptional profiling of antigen-specific CD8+ T cells.

BACKGROUND: Recent advances in single-cell technologies and an improved understanding of tumor antigens have empowered researchers to investigate tumor antigen-specific CD8+ T cells at the single-cell level. Peptide-MHC I tetramers are often utilized to enrich antigen-specific CD8+ T cells, which however, introduces the undesired risk of altering their clonal distribution or their transcriptional state. This study addresses the feasibility of utilizing tetramers to enrich antigen-specific CD8+ T cells for single-cell analysis. METHODS: HLA-A*02:01-restricted human cytomegalovirus (CMV) pp65 peptide-specific CD8+ T cells were used as a model for analyzing antigen-specific CD8+ T cells. Single-cell RNA sequencing and TCR sequencing were performed to compare the frequency and gene expression profile of pp65-specific TCR clones between tetramer-sorted, unstimulated- and tetramer-stimulated total CD8+ T cells. RESULTS: The relative frequency of pp65-specific TCR clones and their transcriptional profile remained largely unchanged following tetramer-based sorting. In contrast, tetramer-mediated stimulation of CD8+ T cells resulted in significant gene expression changes in pp65-specific CD8+ T cells. An Antigen-Specific Response (ASR) gene signature was derived from tetramer-stimulated pp65-specific CD8+ T cells. The ASR signature had a predictive value and was significantly associated with progression free survival in lung cancer patients treated with anti-PD-L1, anti-VEGF, chemotherapy combination (NCT02366143). The predictive power of the ASR signature was independent of the conventional CD8 effector signature. CONCLUSIONS: Our findings validate the approach of enriching antigen-specific CD8+ T cells through tetramer-aided Fluorescence-Activated Cell Sorting (FACS) sorting for single-cell analysis and also identifies an ASR gene signature that has value in predicting response to cancer immunotherapy.

Cobimetinib Alone and Plus Venetoclax With/Without Atezolizumab in Patients With Relapsed/Refractory Multiple Myeloma.

INTRODUCTION: Mitogen-activated protein kinase pathway mutations are present in >50% of patients with relapsed/refractory (R/R) multiple myeloma (MM). MEK inhibitors show limited single-agent activity in R/R MM; combination with B-cell lymphoma-2 (BCL-2) and programmed death-ligand 1 inhibition may improve efficacy. This phase Ib/II trial (NCT03312530) evaluated safety and efficacy of cobimetinib (cobi) alone and in combination with venetoclax (ven) with/without atezolizumab (atezo) in patients with R/R MM. PATIENTS AND METHODS: Forty-nine patients were randomized 1:2:2 to cobi 60 mg/day on days 1-21 (n = 6), cobi 40 mg/day on days 1-21 + ven 800 mg/day on days 1-28 with/without atezo 840 mg on days 1 and 15 of 28-day cycles (cobi-ven, n = 22; cobi-ven-atezo, n = 21). Safety run-in cohorts evaluated cobi-ven and cobi-ven-atezo dose levels. RESULTS: Any-grade common adverse events (AEs) with cobi, cobi-ven, and cobi-ven-atezo, respectively, included diarrhea (33.3%, 81.8%, 90.5%) and nausea (16.7%, 50.0%, 66.7%); common grade ≥3 AEs included anemia (0%, 22.7%, 23.8%), neutropenia (0%, 13.6%, 38.1%), and thrombocytopenia (0%, 18.2%, 23.8%). The overall response rate for all-comers was 0% (cobi), 27.3% (cobi-ven), and 28.6% (cobi-ven-atezo), and 0%, 50.0%, and 100%, respectively, in patients with t(11;14)+. Biomarker analysis demonstrated non-t(11;14) patient selection with NRAS/KRAS/BRAF mutation or high BCL-2/BCL-2-L1 ratio (>52% of the study population) could enrich for responders to the cobi-ven combination. CONCLUSIONS: Cobi-ven and cobi-ven-atezo demonstrated manageable safety with moderate activity in all-comers, and higher activity in patients with t(11;14)+ MM, supporting a biomarker-driven approach for ven in MM.

Immune microenvironment characteristics in multiple myeloma progression from transcriptome profiling.

Multiple myeloma (MM) is characterized by clonal expansion of malignant plasma cells in the bone marrow (BM). Despite the significant advances in treatment, relapsed and refractory MM has not yet been completely cured due to the immune dysfunction in the tumor microenvironment (TME). In this study, we analyzed the transcriptome data from patients with newly diagnosed (ND) and relapsed/refractory (R/R) MM to characterize differences in the TME and further decipher the mechanism of tumor progression in MM. We observed highly expressed cancer testis antigens and immune suppressive cell infiltration, such as Th2 and M2 cells, are associated with MM progression. Furthermore, the TGF-ß signature contributes to the worse outcome of patients with R/R MM. Moreover, patients with ND MM could be classified into immune-low and immune-high phenotypes. Immune-high patients with higher IFN-g signatures are associated with MHC-II-mediated CD4+ T-cell response through CIITA stimulation. The baseline TME status could potentially inform new therapeutic choices for the ND MM who are ineligible for autologous stem cell transplantation and may help predict the response to CAR-T for patients with R/R MM. Our study demonstrates how integrating tumor transcriptome and clinical information to characterize MM immune microenvironment and elucidate potential mechanisms of tumor progression and immune evasion, which will provide insights into MM treatment selection.

Molecular classification of hormone-sensitive and castration-resistant prostate cancer, using nonnegative matrix factorization molecular subtyping of primary and metastatic specimens.

BACKGROUND: Despite the rapidly evolving therapeutic landscape, immunotherapy has demonstrated limited activity in prostate cancer. A greater understanding of the molecular landscape, particularly the expression of immune-related pathways, will inform future immunotherapeutic strategies. Consensus nonnegative matrix factorization (cNMF) is a novel model of molecular classification analyzing gene expression data, focusing on biological interpretation of metagenes and selecting meaningful clusters. OBJECTIVE: We aimed to identify molecular subtypes of prostate cancer using cNMF and correlate these with existing biomarkers to inform future immunotherapeutic strategies. METHODS: A cohort of archival tumor specimens from hormone-sensitive and castration-resistant disease was studied. Whole transcriptomic profiles were generated using TruSeq RNA Access technology and subjected to cNMF. Comprehensive genomic profiling was performed with the FoundationOne assay. NMF subtypes were characterized by gene expression pathways, genomic alterations and correlated with clinical data, then applied to The Cancer Genome Atlas data set. RESULTS: We studied 164 specimens, including 52 castration-resistant and 13 paired primary/metastatic specimens. cNMF identified four distinct subtypes. NMF1 (19%) is enriched for immune-related and stromal-related pathways with transforming growth factor ß (TGFß) signature. NMF2 (36%) is associated with FOXO-mediated transcription signature and AKT signaling, NMF3 (26%) is enriched for ribosomal RNA processing, while NMF4 (19%) is enriched for cell cycle and DNA-repair pathways. The most common gene alterations included TMPRSS22 (42%), TP53 (23%), and DNA-repair genes (19%), occurring across all subtypes. NMF4 is significantly enriched for MYC and Wnt-signaling gene alterations. TMB, CD8 density, and PD-L1 expression were low overall. NMF1 and NMF4 were NMF2 was associated with superior overall survival. CONCLUSIONS: Using cNMF, we identified four molecularly distinct subtypes which may inform treatment selection. NMF1 demonstrates the most inflammatory signature with asuppressive TGFß signature, suggesting potential benefit with immunotherapy combination strategies targeting TGFß and PD-(L)1. Prospective studies are required to evaluate the use of this novel model to molecularly stratify patients for optimal treatment selection.

A phase-II study of atezolizumab in combination with obinutuzumab or rituximab for relapsed or refractory mantle cell or marginal zone lymphoma or Waldenström's macroglobulinemia.

We report efficacy, safety and biomarker data from a phase-II study evaluating atezolizumab (eight 21-day cycle as induction therapy) in combination with obinutuzumab in patients with relapsed/refractory mantle cell lymphoma (MCL, n = 30) or Waldenström's macroglobulinemia (WM, n = 4), and in combination with rituximab in patients with marginal zone lymphoma (MZL, n = 21). All patients received atezolizumab monotherapy as maintenance for ≤10 cycles. Objective response rates at end of induction were 16.7% (MCL) and 42.9% (MZL), with no responses in WM. Median duration of response was 6.8 months (range 5.7-not estimable) for MCL and not reached for MZL. Treatment-emergent adverse events (TEAEs) occurred in 93.3%, 95.2% and 100% of MCL, MZL and WM patients, respectively. One fatal TEAE (pneumonia) occurred in each of the MCL and MZL groups. Biomarker analysis highlighted the importance of characterizing the immune environment to optimize efficacy of immunotherapy regimens.Trial registration details: EudraCT: 2016-003579-22.

Final Overall Survival and Molecular Analysis in IMmotion151, a Phase 3 Trial Comparing Atezolizumab Plus Bevacizumab vs Sunitinib in Patients With Previously Untreated Metastatic Renal Cell Carcinoma.

IMPORTANCE: Interim analyses of the IMmotion151 trial (A Study of Atezolizumab in Combination With Bevacizumab Versus Sunitinib in Participants With Untreated Advanced Renal Cell Carcinoma) reported improved progression-free survival (PFS) for patients with programmed death ligand 1-positive (PD-L1+) metastatic renal cell carcinoma (mRCC) receiving the PD-L1 inhibitor atezolizumab plus the vascular endothelial growth factor (VEGF) inhibitor bevacizumab vs the receptor tyrosine kinase inhibitor sunitinib. Overall survival (OS) results were immature at interim analyses. OBJECTIVE: To report the final OS results, safety, and exploratory biomarker analyses of the association of transcriptomic subgroups with OS in the IMmotion151 trial. DESIGN, SETTING, AND PARTICIPANTS: IMmotion151 was a multicenter, open-label, phase 3 randomized clinical trial that compared the efficacy and safety of atezolizumab plus bevacizumab vs sunitinib in patients with untreated mRCC. IMmotion151 included patients from 152 academic medical centers and community oncology practices in 21 countries. Adult patients with mRCC with components of clear cell or sarcomatoid histologic features, measurable disease (according to Response Evaluation Criteria in Solid Tumors, version 1.1), adequate performance status, hematologic and end organ function, and tumor tissue available for PD-L1 testing were included. IMmotion151 was initiated on May 20, 2015, and the study is ongoing. This final analysis was performed from May 20, 2015, to February 14, 2020. INTERVENTIONS: Receipt of 1200 mg of intravenous (IV) atezolizumab every 3 weeks and 15 mg/kg of IV bevacizumab every 3 weeks or 50 mg orally once daily of sunitinib (4 weeks on and 2 weeks off). MAIN OUTCOMES AND MEASURES: The coprimary end points were PFS (previously reported) in patients with PD-L1+ disease and OS in the intention-to-treat population. Additional exploratory outcomes included OS in the PD-L1+ population, association with transcriptomic subgroups, and safety. RESULTS: The IMmotion151 trial assessed 915 patients with metastatic renal cell carcinoma. Mean (IQR) age was 62 (56-69) years for patients receiving atezolizumab plus bevacizumab and 60 (54-66) years for patients receiving sunitinib; 669 (73.1%) were male and 246 (26.9%) were female. The final analysis showed similar median OS in patients receiving atezolizumab plus bevacizumab vs sunitinib in the intention-to-treat (36.1 vs 35.3 months) and PD-L1+ (38.7 vs 31.6 months) populations. No new safety signals were reported. The additional exploratory outcome of atezolizumab plus bevacizumab vs sunitinib showed improved median OS trends in patients whose tumors were characterized by T-effector/proliferative, proliferative, or small nucleolar RNA transcriptomic profiles (35.4 vs 21.2 months; hazard ratio, 0.70; 95% CI, 0.50-0.98). CONCLUSIONS AND RELEVANCE: The primary end point of PFS was met at interim analyses, although no improvement in OS was observed with atezolizumab plus bevacizumab at the final analysis. Biomarker analyses provided insight into which patients with mRCC may benefit from combined anti-PD-L1 and anti-VEGF therapy. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02420821.

Quantification of Glomerular Structural Lesions: Associations With Clinical Outcomes and Transcriptomic Profiles in Nephrotic Syndrome.

RATIONALE & OBJECTIVE: The current classification system for focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) does not fully capture the complex structural changes in kidney biopsies nor the clinical and molecular heterogeneity of these diseases. STUDY DESIGN: Prospective observational cohort study. SETTING & PARTICIPANTS: 221 MCD and FSGS patients enrolled in the Nephrotic Syndrome Study Network (NEPTUNE). EXPOSURE: The NEPTUNE Digital Pathology Scoring System (NDPSS) was applied to generate scores for 37 glomerular descriptors. OUTCOME: Time from biopsy to complete proteinuria remission, time from biopsy to kidney disease progression (40% estimated glomerular filtration rate [eGFR] decline or kidney failure), and eGFR over time. ANALYTICAL APPROACH: Cluster analysis was used to group patients with similar morphologic characteristics. Glomerular descriptors and patient clusters were assessed for associations with outcomes using adjusted Cox models and linear mixed models. Messenger RNA from glomerular tissue was used to assess differentially expressed genes between clusters and identify genes associated with individual descriptors driving cluster membership. RESULTS: Three clusters were identified: X (n = 56), Y (n = 68), and Z (n = 97). Clusters Y and Z had higher probabilities of proteinuria remission (HRs of 1.95 [95% CI, 0.99-3.85] and 3.29 [95% CI, 1.52-7.13], respectively), lower hazards of disease progression (HRs of 0.22 [95% CI, 0.08-0.57] and 0.11 [95% CI, 0.03-0.45], respectively), and lower loss of eGFR over time compared with X. Cluster X had 1,920 genes that were differentially expressed compared with Y+Z; these reflected activation of pathways of immune response and inflammation. Six descriptors driving the clusters individually correlated with clinical outcomes and gene expression. LIMITATIONS: Low prevalence of some descriptors and biopsy at a single time point. CONCLUSIONS: The NDPSS allows for categorization of FSGS/MCD patients into clinically and biologically relevant subgroups, and uncovers histologic parameters associated with clinical outcomes and molecular signatures not included in current classification systems.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Molecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade.

Integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients identifies molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis reveals seven molecular subsets with distinct angiogenesis, immune, cell-cycle, metabolism, and stromal programs. While sunitinib and atezolizumab + bevacizumab are effective in subsets with high angiogenesis, atezolizumab + bevacizumab improves clinical benefit in tumors with high T-effector and/or cell-cycle transcription. Somatic mutations in PBRM1 and KDM5C associate with high angiogenesis and AMPK/fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations associate with increased cell-cycle and anabolic metabolism. Sarcomatoid tumors exhibit lower prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade versus antiangiogenics alone, and develop personalized therapies in RCC and other indications.

Systems Biology and Kidney Disease.

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

An integrative systems biology approach for precision medicine in diabetic kidney disease.

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Systems biology approaches to identify disease mechanisms and facilitate targeted therapy in the management of glomerular disease.

PURPOSE OF REVIEW: Current clinical pathological classifications of glomerular diseases are inadequate at predicting patient disease progression or response to therapy. With the advent of precision medicine and its successes in oncology, it is important to understand if similar approaches in glomerular diseases can improve patient management. The purpose of this review is to summarize approaches to obtain comprehensive molecular profiles from human biopsies and utilize them to define the pathophysiology of glomerular failure. RECENT FINDINGS: Multicenter research networks have provided the framework to capture both prospective clinical disease course and patterns of end organ damage in biopsy cohorts. With these sample and data sets in hand, efforts are progressing towards molecular disease characterization, identification of novel prognostic marker, development of more precise clinical trials and discovery of predictive biomarkers to more effectively stratify patients to appropriate treatment regiments. Partnerships between academia, public funding agencies and private companies seek to improve timelines and maximize resources while also leveraging domain expertise in an integrated framework to holistically understand disease. SUMMARY: The application of system biology techniques within team science frameworks across disciplines and continents will seek to realize the impact of precision medicine to bring urgently needed novel therapeutic options to patients with glomerular disease.

Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes.

Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these early studies, a fraction of samples that did not fit well into the four subtype classifications were excluded. Therefore, we sought to systematically determine the concordance of transcriptomic HGSC subtypes across populations without removing any samples. We created a bioinformatics pipeline to independently cluster the five largest mRNA expression datasets using k-means and nonnegative matrix factorization (NMF). We summarized differential expression patterns to compare clusters across studies. While previous studies reported four subtypes, our cross-population comparison does not support four. Because these results contrast with previous reports, we attempted to reproduce analyses performed in those studies. Our results suggest that early results favoring four subtypes may have been driven by the inclusion of serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.

Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures.

BACKGROUND: It is unclear whether the transcriptional subtypes of high grade serous ovarian cancer (HGSOC) apply to high grade clear cell (HGCCOC) or high grade endometrioid ovarian cancer (HGEOC). We aim to delineate transcriptional profiles of HGCCOCs and HGEOCs. METHODS: We used Agilent microarrays to determine gene expression profiles of 276 well annotated ovarian cancers (OCs) including 37 HGCCOCs and 66 HGEOCs. We excluded low grade OCs as these are known to be distinct molecular entities. We applied the prespecified TCGA and CLOVAR gene signatures using consensus non-negative matrix factorization (NMF). RESULTS: We confirm the presence of four TCGA transcriptional subtypes and their significant prognostic relevance (p<0.001) across all three histological subtypes (HGSOC, HGCCOC and HGEOCs). However, we also demonstrate that 22/37 (59%) HGCCOCs and 30/67 (45%) HGEOCs form 2 additional separate clusters with distinct gene signatures. Importantly, of the HGCCOC and HGEOCs that clustered separately 62% and 65% were early stage (FIGO I/II), respectively. These finding were confirmed using the reduced CLOVAR gene set for classification where most early stage HGCCOCs and HGEOCs formed a distinct cluster of their own. When restricting the analysis to the four TCGA signatures (ssGSEA or NMF with CLOVAR genes) most early stage HGCCOCs and HGEOC were assigned to the differentiated subtype. CONCLUSIONS: Using transcriptional profiling the current study suggests that HGCCOCs and HGEOCs of advanced stage group together with HGSOCs. However, HGCCOCs and HGEOCs of early disease stages may have distinct transcriptional signatures similar to those seen in their low grade counterparts.