Biology subjects

Califano, A.

Publications and source records attributed to Califano, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Systematic Pan-cancer Functional Inference and Validation of Hyper, Hypo and Neomorphic Mutations

While the functional effects of many recurrent cancer mutations have been characterized, the TCGA repository comprises more than 10M non-recurrent events, whose function is unknown. We propose that the context specific activity of transcription factor (TF) proteins--as measured by expression of their transcriptional targets--provides a sensitive and accurate reporter assay to assess the functional role of oncoprotein mutations. Analysis of differentially active TFs in samples harboring mutations of unknown significance--compared to established gain (GOF/hypermorph) or loss (LOF/hypomorph) of function--helped functionally characterize 577,866 individual mutational events across TCGA cohorts, including identification of mutations that are either neomorphic (gain of novel function) or phenocopy other mutations (mutational mimicry). Validation using mutation knock-in assays confirmed 15 out of 15 predicted gain and loss of function mutations and 15 of 20 predicted neomorphic mutations. This could help determine targeted therapy in patients with mutations of unknown significance in established oncoproteins.

systems biology↗

bioRxiv2023

Ras-dependent activation of BMAL2 regulates hypoxic metabolism in pancreatic cancer

KRAS is the archetypal oncogenic driver of pancreatic cancer. To identify new modulators of KRAS activity in human pancreatic ductal adenocarcinoma (PDAC), we performed regulatory network analysis on a large collection of expression profiles from laser capture microdissected samples of PDAC and benign controls. We discovered that BMAL2, a member of the PAS family of transcription factors, promotes tumor initiation, progression, and post-resection survival, and is highly correlated with KRAS activity. Functional analysis of BMAL2 target genes suggested a role in regulating the hypoxia response, a hallmark of PDAC. Knockout of BMAL2 in multiple human PDAC cell lines reduced cancer cell viability, invasion, and glycolysis, leading to broad dysregulation of cellular metabolism, particularly under hypoxic conditions. We find that BMAL2 directly regulates hypoxia-responsive target genes and is necessary for the stabilization of HIF1A under low oxygen conditions, while simultaneously destabilizing HIF2A. Notably, in vivo xenograft studies demonstrated that BMAL2 loss significantly impairs tumor growth and reduces tumor volume, underscoring its functional importance in tumor progression. We conclude that BMAL2 is a master transcriptional regulator of hypoxia responses in PDAC that works downstream of KRAS signaling, possibly serving as a long-sought molecular switch that distinguishes HIF1A- and HIF2A-dependent modes of hypoxic metabolism. Statement of SignificanceWe annotate the landscape of KRAS-associated transcriptional drivers of pancreatic cancer initiation, progression, and overall survival, leading to the identification of BMAL2 as a novel regulator of hypoxic metabolism. BMAL2 helps execute the oncogenic transcriptional programs of KRAS and serves as a long-sought switch between HIF1A- and HIF2A-dependent modes of hypoxic metabolism.

cancer biology↗

bioRxiv2023

Tumor Explants Elucidate a Cascade of Paracrine SHH, WNT, and VEGF Signals Driving Pancreatic Cancer Angiosuppression

The sparse vascularity of Pancreatic Ductal Adenocarcinoma (PDAC) presents a mystery: what prevents this aggressive malignancy from undergoing neoangiogenesis to counteract hypoxia and better support growth? An incidental finding from prior work on paracrine communication between malignant PDAC cells and fibroblasts revealed that inhibition of the Hedgehog (HH) pathway partially relieved angiosuppression, increasing tumor vascularity through unknown mechanisms. Initial efforts to study this phenotype were hindered by difficulties replicating the complex interactions of multiple cell types in vitro. Here we identify a cascade of paracrine signals between multiple cell types that act sequentially to suppress angiogenesis in PDAC. Malignant epithelial cells promote HH signaling in fibroblasts, leading to inhibition of WNT signaling in fibroblasts and epithelial cells, thereby limiting VEGFR2-dependent activation of endothelial hypersprouting. This cascade was elucidated using human and murine PDAC explant models, which effectively retain the complex cellular interactions of native tumor tissues.

cancer biology↗

bioRxiv2023

Network-based elucidation of colon cancer drug resistance by phosphoproteomic time-series analysis

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. By leveraging progress in proteomic technologies and network-based methodologies, over the past decade, we developed VESPA--an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations--and used it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogation of tumor-specific enzyme/substrate interactions accurately inferred kinase and phosphatase activity, based on their inferred substrate phosphorylation state, effectively accounting for signal cross-talk and sparse phosphoproteome coverage. The analysis elucidated time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring that was experimentally confirmed by CRISPRko assays, suggesting broad applicability to cancer and other diseases.

systems biology↗

bioRxiv2022

Therapeutic modulation of the blood-brain barrier and ischemic stroke by a bioengineered FZD4-selective WNT surrogate

Derangements of the blood-brain barrier (BBB) or blood-retinal barrier (BRB) occur in disorders ranging from stroke, cancer, diabetic retinopathy, and Alzheimers disease. The Norrin/FZD4/TSPAN12 pathway activates WNT/{beta}-catenin signaling, which is essential for BBB and BRB function. However, systemic pharmacologic FZD4 stimulation is hindered by obligate palmitoylation and insolubility of native WNTs and suboptimal properties of the FZD4-selective ligand Norrin. Here, we developed L6-F4-2, a non-lipidated, FZD4-specific surrogate with significantly improved sub-picomolar affinity versus native Norrin. In Norrin knockout (NdpKO) mice, L6-F4-2 not only potently reversed neonatal retinal angiogenesis deficits, but also restored BRB and BBB function. In adult C57Bl/6J mice, post-stroke systemic delivery of L6-F4-2 strongly reduced BBB permeability, infarction, and edema, while improving neurologic score and capillary pericyte coverage. Our findings reveal systemic efficacy of a bioengineered FZD4-selective WNT surrogate during ischemic BBB dysfunction, with general applicability to adult CNS disorders characterized by an aberrant blood-brain barrier.

physiology↗

bioRxiv2022

Single-Cell RNAseq Analysis Reveals Robust Anti-PD-1-Mediated Increase of Immune Infiltrate in Metastatic Castration-Sensitive Prostate Cancer

Compared to other malignancies, the tumor microenvironment (TME) of primary and castration-resistant prostate cancer (CRPC) is relatively devoid of immune infiltrates. While androgen deprivation therapy (ADT) induces a complex immune infiltrate in localized prostate cancer, both in animal models and humans, the TME composition of metastatic, castration-sensitive prostate cancer (mCSPC) is relatively unknown and the effects of ADT and other treatments are poorly characterized in this context. To address this challenge, we analyzed metastatic sites from patients enrolled on a phase 2 clinical trial (NCT03951831), in which men were treated with standard-of-care chemo-hormonal therapy with anti-PD-1 immunotherapy, at the single cell level. Longitudinal protein activity-based analysis of TME subpopulations identified immune subpopulations conserved across multiple metastatic sites, their dynamic, treatment-mediated evolution, and associated clinical response features. Our study revealed a therapy-resistant, transcriptionally distinct tumor subpopulation, which comprises an increasing number of cells in treatment-refractory patients, and identified several druggable targets in both tumor and immune cells as candidates to advance treatment and improve outcomes for patients with mCSPC.

cancer biology↗

bioRxiv2022

Airway Basal Cells Show Regionally Distinct Potential to Undergo Metaplastic Differentiation

Basal cells are multipotent stem cells of a variety of organs, and in the lung are known as crucial components of the airway epithelium. However, it remains unclear how diverse basal cells are and whether distinct subpopulations respond differently to airway challenges. Using single cell RNA-sequencing and functional approaches, we report a significant and previously underappreciated degree of heterogeneity in the basal cell pool, leading to identification of six subpopulations in the murine trachea. Among these we found two major subpopulations comprising the most stem-like progenitor compartment, but with distinct signatures and ability to self-renew and differentiate. Notably, these occupy distinct ventral and dorsal tracheal niches and differ in their ability to initiate an aberrant program of differentiation in response to environmental perturbations in primary cultures and in injury mouse models in vivo. We found that such heterogeneity is acquired prenatally, when the basal cell pool and local niches are being established, and depends on the integrity of these niches, as supported by the altered basal cell phenotype of cartilage-deficient mouse mutants. Lastly, we show that key features that distinguish these progenitor subpopulations in murine airways are conserved in humans. Together, the data provide critical insights into the origin and impact of basal cell heterogeneity on the establishment of regionally distinct responses of the airway epithelium during injury-repair and in disease conditions.

developmental biology↗

bioRxiv2022

Isthmal stem cells sustain intestinal homeostasis and regeneration

The currently accepted intestinal epithelial cell organization model proposes that crypt base columnar (CBC) cells marked by high levels of Lgr5 expression represent the sole intestinal stem cell (ISC) compartment. However, previous studies have indicated that Lgr5+ cells are dispensable for intestinal regeneration, leading to two major hypotheses: one favoring the presence of a quiescent reserve stem cell population, the other calling for differentiated cell plasticity. To investigate these possibilities, we studied crypt epithelial cell organization, during homeostasis and regeneration, in unbiased fashion, via high-resolution single-cell profiling. These studies, combined with in vivo lineage tracing, show that Lgr5 is not a specific ISC marker and that stemness potential exists beyond the crypt base in the isthmus region, whose cells, contrary to differentiated cells, participate in tissue homeostasis and support intestinal regeneration. Our results provide a novel model of organization for the intestinal crypt epithelium in which stemness potential is not restricted to CBC cells and suggesting that neither de-differentiation nor reserve stem cell populations are drivers of intestinal regeneration.

developmental biology↗

bioRxiv2022

Integrative 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). While our understanding of the biology underlying immune checkpoint blockade in NSCLC is still incomplete, studies to date have established predictive roles for PD-L1 tumor expression and tumor mutational burden (TMB). 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 2 Cancer - Mark Foundation (SU2C-MARK) 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 (e.g., ATM altered), and unfavorable (e.g., TERT amplified) genomic subgroups, 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activation (favorable), and 3) a novel de-differentiated tumor-intrinsic subtype characterized by expression of endodermal lineage genes, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC.

genomics↗

bioRxiv2022

Case Study of Single-cell Protein Activity Based Drug Prediction for Precision Treatment of Cholangiocarcinoma

Cholangiocarcinoma is a rare, aggressive malignancy with limited treatment options, due to a paucity of actionable mutations and low response to immune checkpoint inhibitors. Furthermore, its extreme heterogeneity prevents identification of actionable dependencies from bulk-tissue profiles. To address these challenges, we introduce a highly generalizable, single-cell framework for the mechanism-based prioritization of drugs to treat rare, highly heterogeneous tumors. Analysis of transformed cells, accounting for only 10% of a cholangiocarcinoma patient biopsy revealed three molecularly-distinct subpopulations, predicted to be sensitive to four drugs by regulatory network-based analysis. Validation in a low-passage, patient-derived xenograft (PDX) from the same patient confirmed tumor growth rate control by two of these drugs (plicamycin and dacinostat) and further validated predicted subpopulation-specific effects, suggesting they may represent promising candidates for follow-up clinical trials, either alone or in combination with current standard-of-care chemotherapies. The proposed approach can be generalized to elucidate complementary dependencies of rare, heterogeneous tumors, at the single cell level.

cancer biology↗

bioRxiv2022

Systematic Elucidation and Pharmacological Targeting of Tumor-Infiltrating Regulatory T Cell Master Regulators

Due to their immunosuppressive role, tumor-infiltrating regulatory T cells (TI-Tregs) represent attractive therapeutic targets. Analysis of TI vs. peripheral Tregs (P-Tregs) from 36 patients, across four malignancies, identified 17 candidate Master Regulators (MRs), predicted to mechanistically regulate TI-Tregs transcriptional state. In vivo, pooled CRISPR-KO screening, using a hematopoietic stem cell transplant model, confirmed essentiality of 7 of 17 MRs in TI-Treg recruitment and/or retention to the TME, without affecting other T cell subtypes, while individual knockout of the most significant MR (TRPS1) significantly reduced tumor allograft growth. TI-Treg drug perturbation profile analysis identified drugs capable of inverting the TI-Treg-specific MR activity signature at low concentration. Low dose treatment with gemcitabine (top prediction) inhibited tumor growth in immunocompetent but not immunocompromised allografts, increased PD-1 inhibitor efficacy, and depleted TI-Tregs in vivo. The study provides key insight into Treg infiltration mechanism and a gene reporter assay to identify additional small molecule inhibitors. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=140 HEIGHT=200 SRC="FIGDIR/small/481404v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1cca60borg.highwire.dtl.DTLVardef@a93ce6org.highwire.dtl.DTLVardef@dd2aa2org.highwire.dtl.DTLVardef@1a2c98_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

The OncoLoop network-based precision oncology framework

At present, prioritizing cancer treatments at the individual patient level remains challenging, and performing co-clinical studies using patient-derived models in real-time is often not feasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict and validate drug sensitivity in human tumors and their pre-existing high-fidelity (cognate) model(s) by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer (PCa) using a series of genetically-engineered mouse models (GEMMs) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of published cohorts using Master Regulator (MR) conservation analysis revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one cognate patient-derived xenograft (PDX). OncoLoop is a highly generalizable framework that can be extended to other cancers and potentially other diseases. Significance StatementOncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround co-clinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available.

cancer biology↗

bioRxiv2021

Identification and validation of a non-genetically encoded vulnerability to XPO1 inhibition in malignant rhabdoid tumors - expanding patient-driven discovery beyond the Nof1.

Malignant rhabdoid tumors (MRTs) are rare, aggressive pediatric solid tumors, characterized by a 22q11 deletion that inactivates the SMARCB1 gene. Outcomes remain poor despite multimodality treatment. MRTs are among the most genomically stable cancers and lack therapeutically targetable genetic mutations. We utilized metaVIPER, an extension of the Virtual Inference of Protein-activity by Enriched Regulon (VIPER) algorithm, to computationally infer activated druggable proteins in the tumor of an eight month old patient and then expanded the analysis to TCGA and TARGET cohorts. In vitro studies were performed on a panel of MRT and atypical teratoid/rhabdoid tumor cell lines. Two patient-derived xenograft (PDX) mouse models of MRT were used for in vivo efficacy studies. MetaVIPER analysis from the patients tumor identified significantly high inferred activity of nuclear export protein Exportin-1 (XPO1). Expanded metaVIPER analysis of TCGA and TARGET cohorts revealed consistent elevations in XPO1 inferred activity in MRTs compared to other cancer types. All MRT cell lines demonstrated baseline activation of XPO1. MRT cell lines demonstrated in vitro sensitivity to the XPO1 inhibitor, selinexor which led to cell cycle arrest and induction of apoptosis. Targeted inhibition of XPO1 in patient-derived xenograft models of MRT using selinexor resulted in abrogation of tumor growth. Selinexor demonstrates efficacy in preclinical models of MRT. These results support investigation of selinexor in a phase II study in children with MRT and illustrate the importance of an N-of-1 approach in driving discovery beyond the single patient. Statement of Translational RelevanceWe describe the patient-driven discovery of XPO1 activation as a non-genetically encoded vulnerability in MRTs. The application of metaVIPER analysis to tumors lacking actionable oncogenic alterations represents a novel approach for identifying potential therapeutic targets and biomarkers of response. Our preclinical validation of selinexor confirms XPO1 inhibition as a promising therapeutic strategy for the treatment of MRT.

cancer biology↗

bioRxiv2021

An Information Theoretic Framework for Protein Activity Measurement

Nonparametric analytical Rank-based Enrichment Analysis (NaRnEA) is a novel gene set analysis method which leverages an analytical null model derived under the Principle of Maximum Entropy. NaRnEA critically improves over two widely used methods - Gene Set Enrichment Analysis (GSEA) and analytical Rank-based Enrichment Analysis (aREA) - as shown by differential activity measurement of ~2,500 transcriptional regulatory proteins across three cohorts in The Cancer Genome Atlas (TCGA) based on the enrichment of their transcriptional targets in differentially expressed genes. Phenotype-matched proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) was used to evaluate measurement accuracy. We show that the sample-shuffling empirical null models leveraged by GSEA and aREA are overly conservative, a shortcoming that is critically addressed by NaRnEAs optimal analytical null model.

systems biology↗

bioRxiv2021

Network-based identification and pharmacological targeting of host cell master regulators induced by SARS-CoV-2 infection

Precise characterization and targeting of host cell transcriptional machinery hijacked by SARS-CoV-2 remains challenging. To identify therapeutically targetable mechanisms that are critical for SARS-CoV-2 infection, here we elucidated the Master Regulator (MR) proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2. The analysis revealed coordinated inactivation of MR-proteins linked to regulatory programs potentiating efficiency of viral replication (detrimental host MR-signature) and activation of MR-proteins governing innate immune response programs (beneficial MR-signature). To identify MR-inverting compounds capable of rescuing activity of inactivated host MR-proteins, with-out adversely affecting the beneficial MR-signature, we developed the ViroTreat algorithm. Overall, >80% of drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 infection, without affecting cell viability. ViroTreat is fully generalizable and can be extended to identify drugs targeting the host cell-based MR signatures induced by virtually any pathogen.

microbiology↗

bioRxiv2021

Interrogation of genome-wide, experimentally dissected gene regulatory networks reveals mechanisms underlying dynamic cellular state control

Pooled CRISPRi-mediated silencing of >1,000 transcriptional regulators expressed in single colorectal adenocarcinoma cells, followed by single-cell RNA-seq profiling at two timepoints, 1 day and 4 days, allowed reverse engineering the underlying tumor context-specific, causal regulatory network. Furthermore, the availability of experimentally derived, highly multiplexed gene reporter assays for each regulator, as identified by this analysis, allowed accurate assessment of differential protein activity following silencing of each regulator, thus providing proof-of-concept for generating comprehensive, tissue-specific networks of transcriptional and post-translational interactions. Analysis of this causal network allowed elucidation of complex autoregulatory mechanisms that have eluded previous computational approaches and supported systematic elucidation of cooperative mechanisms, where one regulatory protein can modulate the activity of another regulatory protein, as well as transcriptional mimicry, where one regulatory protein can phenocopy others.

systems biology↗

bioRxiv2021

PISCES: A pipeline for the Systematic, Protein Activity-based Analysis of Single Cell RNA Sequencing Data

While single-cell RNA sequencing provides a remarkable window on pathophysiologic tissue biology and heterogeneity, its high gene-dropout rate and low signal-to-noise ratio challenge quantitative analyses and mechanistic understanding. To address this issue, we developed PISCES, a platform for the network-based, single-cell analysis of mammalian tissue. PISCES accurately estimates the mechanistic contribution of regulatory and signaling proteins to cell state implementation and maintenance, based on the expression of their lineage-specific transcriptional targets, thus supporting discovery and visualization of Master Regulators of cell state and cell state transitions. Experimental validation assays, including by assessing concordance with antibody and CITE-Seq-based measurements, show significant improvement in the ability to identify rare subpopulations and to elucidate key lineage markers, compared to gene expression analysis. Systematic analysis of single cell profiles in the Human Protein Atlas (HPA) produced a comprehensive resource for human tissue studies, supporting fine-grain stratification of distinct cell states, molecular determinants, and surface markers.

systems biology↗

bioRxiv2020

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

The Columbia Cancer Target Discovery and Development (CTD2) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection of dose-response curves and perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, developed to study tumor-specific drug mechanism of action, was instrumental in hosting a DREAM Challenge to assess computational models for de novo drug polypharmacology prediction. Dose-response and perturbational profiles for 32 kinase inhibitors were provided to 21 participating teams, who did not know the identity or nature of the compounds, and they were asked to predict high-affinity binding among ~1,300 possible protein targets. Best performing methods leveraged both gene expression profile similarity analysis, and deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessment of context-specific drug mechanism of action.

cancer biology↗