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INTRODUCTION: Advances in understanding of tumor biology shed light on hallmarks of cancer development and progression that include dysregulated DNA damage repair (DDR) machinery. Leveraging underlying tumor genomic instability and tumor specific defects in DDR, Poly (ADP-ribose) polymerases (PARP) inhibitors (PARPi) induced DNA damage emerges as a novel non-chemotherapy therapeutic opportunity. PARPis are currently approved in multiple tumor types, with the largest benefit seen in tumors with homologous recombination repair (HRR) deficiency, including germline and somatic mutations in BRCA1/2 genes (BRCA) and other pathway members such as PALB2 and Rad51c. AREAS COVERED: This review article summarizes the current approval landscape and known and proposed mechanisms of resistance to PARPi. Further, therapeutic strategies to overcome PARPi resistance are discussed, including ongoing clinical trials. EXPERT OPINION: PARPi have proven to be a safe and effective therapy and represent a cornerstone treatment across multiple solid tumor types. Elucidating innate and acquired mechanisms of resistance, coupled with the emergence of novel therapeutic options to capitalize on the activity of PARPi and prevent or reverse the acquisition of resistance, provides an opportunity to further expand the role of PARPi in cancer therapy.
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Cancer cells with BRCA1/2 deficiencies are sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors. We evaluated the efficacy of talazoparib in DNA-Damage Repair (DDR)-altered patients. In this phase II trial, patients were enrolled onto one of four cohorts based on molecular alterations: (1) somatic BRCA1/2, (2) other homologous recombination repair pathway, (3) PTEN and (4) germline BRCA1/2. The primary endpoint was a clinical benefit rate (CBR): complete response, partial response or stable disease ≥24 weeks. 79 patients with a median of 4 lines of therapy were enrolled. CBR for cohorts 1-4 were: 32.5%, 19.7%, 9.4% and 30.6%, respectively. PTEN mutations correlated with reduced survival and a trend towards shorter time to progression.Talazoparib demonstrated clinical benefit in selected DDR-altered patients. PTEN mutations/loss patients derived limited clinical benefit. Further study is needed to determine whether PTEN is prognostic or predictive of response to PARP inhibitors.
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Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.
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Carcinoma Ductal Pancreático , Recombinação Homóloga , Macrófagos , Neoplasias Pancreáticas , Humanos , Carcinoma Ductal Pancreático/imunologia , Carcinoma Ductal Pancreático/genética , Carcinoma Ductal Pancreático/tratamento farmacológico , Carcinoma Ductal Pancreático/patologia , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/imunologia , Neoplasias Pancreáticas/tratamento farmacológico , Neoplasias Pancreáticas/patologia , Macrófagos/imunologia , Macrófagos/metabolismo , Inibidores de Poli(ADP-Ribose) Polimerases/farmacologia , Inibidores de Poli(ADP-Ribose) Polimerases/uso terapêutico , Microambiente Tumoral/imunologiaRESUMO
Case report of a HER2-expressed ovarian clear cell carcinoma with exceptional response to trastuzumab deruxtecan.
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Recidiva Local de Neoplasia , Neoplasias Ovarianas , Receptor ErbB-2 , Trastuzumab , Humanos , Feminino , Trastuzumab/uso terapêutico , Neoplasias Ovarianas/tratamento farmacológico , Neoplasias Ovarianas/genética , Receptor ErbB-2/genética , Recidiva Local de Neoplasia/tratamento farmacológico , Adenocarcinoma de Células Claras/tratamento farmacológico , Adenocarcinoma de Células Claras/patologia , Adenocarcinoma de Células Claras/genética , Antineoplásicos Imunológicos/uso terapêutico , Camptotecina/análogos & derivados , Camptotecina/uso terapêutico , Pessoa de Meia-Idade , Imunoconjugados/uso terapêuticoRESUMO
Although Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) have been approved in multiple diseases, including BRCA1/2 mutant breast cancer, responses are usually transient requiring the deployment of combination therapies for optimal efficacy. Here we thus explore mechanisms underlying sensitivity and resistance to PARPi using two intrinsically PARPi sensitive (T22) and resistant (T127) syngeneic murine breast cancer models in female mice. We demonstrate that tumor associated macrophages (TAM) potentially contribute to the differential sensitivity to PARPi. By single-cell RNA-sequencing, we identify a TAM_C3 cluster, expressing genes implicated in anti-inflammatory activity, that is enriched in PARPi resistant T127 tumors and markedly decreased by PARPi in T22 tumors. Rps19/C5aR1 signaling is selectively elevated in TAM_C3. C5aR1 inhibition or transferring C5aR1hi cells increases and decreases PARPi sensitivity, respectively. High C5aR1 levels in human breast cancers are associated with poor responses to immune checkpoint blockade. Thus, targeting C5aR1 may selectively deplete pro-tumoral macrophages and engender sensitivity to PARPi and potentially other therapies.
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Neoplasias da Mama , Resistencia a Medicamentos Antineoplásicos , Inibidores de Poli(ADP-Ribose) Polimerases , Receptor da Anafilatoxina C5a , Macrófagos Associados a Tumor , Animais , Feminino , Inibidores de Poli(ADP-Ribose) Polimerases/farmacologia , Inibidores de Poli(ADP-Ribose) Polimerases/uso terapêutico , Resistencia a Medicamentos Antineoplásicos/genética , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Camundongos , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Neoplasias da Mama/metabolismo , Humanos , Macrófagos Associados a Tumor/efeitos dos fármacos , Macrófagos Associados a Tumor/imunologia , Macrófagos Associados a Tumor/metabolismo , Linhagem Celular Tumoral , Receptor da Anafilatoxina C5a/antagonistas & inibidores , Receptor da Anafilatoxina C5a/metabolismo , Receptor da Anafilatoxina C5a/genética , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Transdução de Sinais/efeitos dos fármacos , Macrófagos/metabolismo , Macrófagos/efeitos dos fármacosRESUMO
High-quality data is crucial for accurate machine learning and actionable analytics, however, mislabeled or noisy data is a common problem in many domains. Distinguishing low- from high-quality data can be challenging, often requiring expert knowledge and considerable manual intervention. Data Valuation algorithms are a class of methods that seek to quantify the value of each sample in a dataset based on its contribution or importance to a given predictive task. These data values have shown an impressive ability to identify mislabeled observations, and filtering low-value data can boost machine learning performance. In this work, we present a simple alternative to existing methods, termed Data Valuation with Gradient Similarity (DVGS). This approach can be easily applied to any gradient descent learning algorithm, scales well to large datasets, and performs comparably or better than baseline valuation methods for tasks such as corrupted label discovery and noise quantification. We evaluate the DVGS method on tabular, image and RNA expression datasets to show the effectiveness of the method across domains. Our approach has the ability to rapidly and accurately identify low-quality data, which can reduce the need for expert knowledge and manual intervention in data cleaning tasks.
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There is now increasing recognition of the important role of androgen receptor (AR) in modulating immune function. To gain a comprehensive understanding of the effects of AR activity on cancer immunity, we employed a computational approach to profile AR activity in 33 human tumor types using RNA-Seq datasets from The Cancer Genome Atlas. Our pan-cancer analysis revealed that the genes most negatively correlated with AR activity across cancers are involved in active immune system processes. Importantly, we observed a significant negative correlation between AR activity and IFNγ pathway activity at the pan-cancer level. Indeed, using a matched biopsy dataset from subjects with prostate cancer before and after AR-targeted treatment, we verified that inhibiting AR enriches immune cell abundances and is associated with higher IFNγ pathway activity. Furthermore, by analyzing immunotherapy datasets in multiple cancers, our results demonstrate that low AR activity was significantly associated with a favorable response to immunotherapy. Together, our data provide a comprehensive assessment of the relationship between AR signaling and tumor immunity.
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Targeting tumor-associated macrophages (TAMs) is an emerging approach being tested in multiple clinical trials. TAMs, depending on their differentiation state, can exhibit pro- or antitumorigenic functions. For example, the M2-like phenotype represents a protumoral state that can stimulate tumor growth, angiogenesis, metastasis, therapy resistance, and immune evasion by expressing immune checkpoint proteins. In this issue of the JCI, Vaccaro and colleagues utilized an innovative drug screen approach to demonstrate that targeting driver oncogenic signaling pathways concurrently with anti-CD47 sensitizes tumor cells, causing them to undergo macrophage-induced phagocytosis. The combination treatment altered expression of molecules on the tumor cells that typically limit phagocytosis. It also reprogrammed macrophages to an M1-like antitumor state. Moreover, the approach was generalizable to tumor cells with different oncogenic pathways, opening the door to precision oncology-based rationale combination therapies that have the potential to improve outcomes for patients with oncogene-driven lung cancers and likely other cancer types.
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Antígeno CD47 , Macrófagos Associados a Tumor , Humanos , Macrófagos Associados a Tumor/metabolismo , Macrófagos Associados a Tumor/efeitos dos fármacos , Macrófagos Associados a Tumor/imunologia , Antígeno CD47/metabolismo , Antígeno CD47/antagonistas & inibidores , Animais , Fagocitose/efeitos dos fármacos , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Neoplasias/metabolismo , Macrófagos/metabolismo , Macrófagos/efeitos dos fármacos , Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/metabolismoRESUMO
Cyclic Immunofluorescence (CyCIF) can quantify multiple biomarkers, but panel capacity is limited by technical challenges. We propose a computational panel reduction approach that can impute the information content from 25 markers using only 9 markers, learning co-expression and morphological patterns while concurrently increasing speed and panel content and decreasing cost. We demonstrate strong correlations in predictions and generalizability across breast and colorectal cancer, illustrating applicability of our approach to diverse tissue types.
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Diagnóstico por Imagem , ImunofluorescênciaRESUMO
Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10Q144K mutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.
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Carcinoma Endometrioide , Hiperplasia Endometrial , Neoplasias do Endométrio , Preservação da Fertilidade , Proteogenômica , Humanos , Feminino , Progestinas/uso terapêutico , Antineoplásicos Hormonais , Hiperplasia Endometrial/tratamento farmacológico , Preservação da Fertilidade/métodos , Estudos Retrospectivos , Carcinoma Endometrioide/tratamento farmacológico , Carcinoma Endometrioide/genética , Carcinoma Endometrioide/patologia , Neoplasias do Endométrio/tratamento farmacológico , Neoplasias do Endométrio/genética , Neoplasias do Endométrio/patologiaRESUMO
Computational modeling of perturbation biology identifies relationships between molecular elements and cellular response, and an accurate understanding of these systems will support the full realization of precision medicine. Traditional deep learning, while often accurate in predicting response, is unlikely to capture the true sequence of involved molecular interactions. Our work is motivated by two assumptions: 1) Methods that encourage mechanistic prediction logic are likely to be more trustworthy, and 2) problem-specific algorithms are likely to outperform generic algorithms. We present an alternative to Graph Neural Networks (GNNs) termed Graph Structured Neural Networks (GSNN), which uses cell signaling knowledge, encoded as a graph data structure, to add inductive biases to deep learning. We apply our method to perturbation biology using the LINCS L1000 dataset and literature-curated molecular interactions. We demonstrate that GSNNs outperform baseline algorithms in several prediction tasks, including 1) perturbed expression, 2) cell viability of drug combinations, and 3) disease-specific drug prioritization. We also present a method called GSNNExplainer to explain GSNN predictions in a biologically interpretable form. This work has broad application in basic biological research and pre-clincal drug repurposing. Further refinement of these methods may produce trustworthy models of drug response suitable for use as clinical decision aids. Availability and implementation: Our implementation of the GSNN method is available at https://github.com/nathanieljevans/GSNN. All data used in this work is publicly available.
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The venetoclax BCL2 inhibitor in combination with hypomethylating agents represents a cornerstone of induction therapy for older AML patients, unfit for intensive chemotherapy. Like other targeted therapies, venetoclax-based therapies suffer from innate and acquired resistance. While several mechanisms of resistance have been identified, the heterogeneity of resistance mechanism across patient populations is poorly understood. Here we utilized integrative analysis of transcriptomic and ex-vivo drug response data in AML patients to identify four transcriptionally distinct VEN resistant clusters (VR_C1-4), with distinct phenotypic, genetic and drug response patterns. VR_C1 was characterized by enrichment for differentiated monocytic- and cDC-like blasts, transcriptional activation of PI3K-AKT-mTOR signaling axis, and energy metabolism pathways. They showed sensitivity to mTOR and CDK inhibition. VR_C2 was enriched for NRAS mutations and associated with distinctive transcriptional suppression of HOX expression. VR_C3 was characterized by enrichment for TP53 mutations and higher infiltration by cytotoxic T cells. This cluster showed transcriptional expression of erythroid markers, suggesting tumor cells mimicking erythroid differentiation, activation of JAK-STAT signaling, and sensitivity to JAK inhibition, which in a subset of cases synergized with venetoclax. VR_C4 shared transcriptional similarities with venetoclax-sensitive patients, with modest over-expression of interferon signaling. They were also characterized by high rates of DNMT3A mutations. Finally, we projected venetoclax-resistance states onto single cells profiled from a patient who relapsed under venetoclax therapy capturing multiple resistance states in the tumor and shifts in their abundance under venetoclax selection, suggesting that single tumors may consist of cells mimicking multiple VR_Cs contributing to intra-tumor heterogeneity. Taken together, our results provide a strategy to evaluate inter- and intra-tumor heterogeneity of venetoclax resistance mechanisms and provide insights into approaches to navigate further management of patients who failed therapy with BCL2 inhibitors.
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Defects in homologous recombination DNA repair (HRD) both predispose to cancer development and produce therapeutic vulnerabilities, making it critical to define the spectrum of genetic events that cause HRD. However, we found that mutations in BRCA1/2 and other canonical HR genes only identified 10%-20% of tumors that display genomic evidence of HRD. Using a networks-based approach, we discovered that over half of putative genes causing HRD originated outside of canonical DNA damage response genes, with a particular enrichment for RNA-binding protein (RBP)-encoding genes. These putative drivers of HRD were experimentally validated, cross-validated in an independent cohort, and enriched in cancer-associated genome-wide association study loci. Mechanistic studies indicate that some RBPs are recruited to sites of DNA damage to facilitate repair, whereas others control the expression of canonical HR genes. Overall, this study greatly expands the repertoire of known drivers of HRD, with implications for basic biology, genetic screening, and therapy stratification.
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Proteína BRCA1 , Neoplasias , Humanos , Proteína BRCA1/genética , Estudo de Associação Genômica Ampla , Proteína BRCA2/genética , Recombinação Homóloga/genética , Proteínas de Ligação a RNA/genéticaRESUMO
Single-cell whole-genome sequencing (scWGS) enables the assessment of genome-level molecular differences between individual cells with particular relevance to genetically diverse systems like solid tumors. The application of scWGS was limited due to a dearth of accessible platforms capable of producing high-throughput profiles. We present a technique that leverages nucleosome disruption methodologies with the widely adopted 10× Genomics ATAC-seq workflow to produce scWGS profiles for high-throughput copy-number analysis without new equipment or custom reagents. We further demonstrate the use of commercially available indexed transposase complexes from ScaleBio for sample multiplexing, reducing the per-sample preparation costs. Finally, we demonstrate that sequential indexed tagmentation with an intervening nucleosome disruption step allows for the generation of both ATAC and WGS data from the same cell, producing comparable data to the unimodal assays. By exclusively utilizing accessible commercial reagents, we anticipate that these scWGS and scWGS+ATAC methods can be broadly adopted by the research community.
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Cromatina , Nucleossomos , Cromatina/genética , Nucleossomos/genética , Análise de Sequência de DNA/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , GenomaRESUMO
Several alterations in fibroblast growth factor receptor (FGFR) genes have been found in breast cancer; however, they have not been well characterized as therapeutic targets. Futibatinib (TAS-120; Taiho) is a novel, selective, pan-FGFR inhibitor that inhibits FGFR1-4 at nanomolar concentrations. We sought to determine futibatinib's efficacy in breast cancer models. Nine breast cancer patient-derived xenografts (PDXs) with various FGFR1-4 alterations and expression levels were treated with futibatinib. Antitumor efficacy was evaluated by change in tumor volume and time to tumor doubling. Alterations indicating sensitization to futibatinib in vivo were further characterized in vitro. FGFR gene expression between patient tumors and matching PDXs was significantly correlated; however, overall PDXs had higher FGFR3-4 expression. Futibatinib inhibited tumor growth in 3 of 9 PDXs, with tumor stabilization in an FGFR2-amplified model and prolonged regression (> 110 days) in an FGFR2 Y375C mutant/amplified model. FGFR2 overexpression and, to a greater extent, FGFR2 Y375C expression in MCF10A cells enhanced cell growth and sensitivity to futibatinib. Per institutional and public databases, FGFR2 mutations and amplifications had a population frequency of 1.1%-2.6% and 1.5%-2.5%, respectively, in breast cancer patients. FGFR2 alterations in breast cancer may represent infrequent but highly promising targets for futibatinib.
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Neoplasias da Mama , Animais , Humanos , Feminino , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Receptores de Fatores de Crescimento de Fibroblastos/metabolismo , Receptor Tipo 2 de Fator de Crescimento de Fibroblastos/metabolismo , Pirazóis , Pirimidinas/farmacologia , Pirróis , Receptor Tipo 1 de Fator de Crescimento de Fibroblastos/genética , Modelos Animais de DoençasRESUMO
Cervical squamous cell carcinoma (CSCC) exhibits a limited response to immune-checkpoint blockade. Here we conducted a multiomic analysis encompassing single-cell RNA sequencing, spatial transcriptomics and spatial proteomics, combined with genetic and pharmacological perturbations to systematically develop a high-resolution and spatially resolved map of intratumoral expression heterogeneity in CSCC. Three tumor states (epithelial-cytokeratin, epithelial-immune (Epi-Imm) and epithelial senescence), recapitulating different stages of squamous differentiation, showed distinct tumor immune microenvironments. Bidirectional interactions between epithelial-cytokeratin malignant cells and immunosuppressive cancer-associated fibroblasts form an immune exclusionary microenvironment through transforming growth factor ß pathway signaling mediated by FABP5. In Epi-Imm tumors, malignant cells interact with natural killer and T cells through interferon signaling. Preliminary analysis of samples from a cervical cancer clinical trial ( NCT04516616 ) demonstrated neoadjuvant chemotherapy induces a state transition to Epi-Imm, which correlates with pathological complete remission following treatment with immune-checkpoint blockade. These findings deepen the understanding of cellular state diversity in CSCC.
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Carcinoma de Células Escamosas , Neoplasias do Colo do Útero , Feminino , Humanos , Carcinoma de Células Escamosas/tratamento farmacológico , Carcinoma de Células Escamosas/genética , Neoplasias do Colo do Útero/genética , Inibidores de Checkpoint Imunológico , Relevância Clínica , Ecossistema , Multiômica , Queratinas/metabolismo , Queratinas/uso terapêutico , Microambiente Tumoral/genética , Proteínas de Ligação a Ácido Graxo/uso terapêuticoRESUMO
CyCIF can quantify multiple biomarkers, but panel capacity is limited by technical challenges. We propose a computational panel reduction approach that can impute the information content from 25 markers using only 9 markers, learning co-expression and morphological patterns while concurrently increasing speed and panel content and decreasing cost. We demonstrate strong correlations in predictions and generalizability across breast and colorectal cancer, illustrating applicability of our approach to diverse tissue types.