Advancing Genomic Cancer Medicine in Rural and Underserved States.

This Viewpoint presents an organizational and social template for medical communities to provide contemporary care for patients with cancer in rural and underserved states.

Genome-matched treatments and patient outcomes in the Maine Cancer Genomics Initiative (MCGI).

Genomic tumor testing (GTT) is an emerging technology aimed at identifying variants in tumors that can be targeted with genomically matched drugs. Due to limited resources, rural patients receiving care in community oncology settings may be less likely to benefit from GTT. We analyzed GTT results and observational clinical outcomes data from patients enrolled in the Maine Cancer Genomics Initiative (MCGI), which provided access to GTTs; clinician educational resources; and genomic tumor boards in community practices in a predominantly rural state. 1603 adult cancer patients completed enrollment; 1258 had at least one potentially actionable variant identified. 206 (16.4%) patients received a total of 240 genome matched treatments, of those treatments, 64% were FDA-approved in the tumor type, 27% FDA-approved in a different tumor type and 9% were given on a clinical trial. Using Inverse Probability of Treatment Weighting to adjust for baseline characteristics, a Cox proportional hazards model demonstrated that patients who received genome matched treatment were 31% less likely to die within 1 year compared to those who did not receive genome matched treatment (HR: 0.69; 95% CI: 0.52-0.90; p-value: 0.006). Overall, GTT through this initiative resulted in levels of genome matched treatment that were similar to other initiatives, however, clinical trials represented a smaller share of treatments than previously reported, and "off-label" treatments represented a greater share. Although this was an observational study, we found evidence for a potential 1-year survival benefit for patients who received genome matched treatments. These findings suggest that when disseminated and implemented with a supportive infrastructure, GTT may benefit cancer patients in rural community oncology settings, with further work remaining on providing genome-matched clinical trials.

Sunitinib in Patients With Breast Cancer With FGFR1 or FGFR2 Amplifications or Mutations: Results From the Targeted Agent and Profiling Utilization Registry Study.

PURPOSE: The Targeted Agent and Profiling Utilization Registry Study is a phase II basket trial evaluating the antitumor activity of commercially available targeted agents in patients with advanced cancer and genomic alterations known to be drug targets. Results from cohorts of patients with metastatic breast cancer (BC) with FGFR1 and FGFR2 alterations treated with sunitinib are reported. METHODS: Eligible patients had measurable disease, Eastern Cooperative Oncology Group performance status 0-2, adequate organ function, and no standard treatment options. Simon's two-stage design was used with a primary end point of disease control (DC), defined as objective response (OR) or stable disease of at least 16 weeks duration (SD16+) according to RECIST v1.1. Secondary end points included OR, progression-free survival, overall survival, duration of response, duration of stable disease, and safety. RESULTS: Forty patients with BC with FGFR1 (N = 30; amplification only n = 26, mutation only n = 1, both n = 3) or FGFR2 (N = 10; amplification only n = 2, mutation only n = 6, both n = 2) alterations were enrolled. Three patients in the FGFR1 cohort were not evaluable for efficacy; all patients in the FGFR2 cohort were evaluable. For the FGFR1 cohort, two patients with partial response and four with SD16+ were observed for DC and OR rates of 27% (90% CI, 13 to 100) and 7% (95% CI, 1 to 24), respectively. The null hypothesis of 15% DC rate was not rejected (P = .169). No patients achieved DC in the FGFR2 cohort (P = 1.00). Thirteen of the 40 total patients across both cohorts had at least one grade 3-4 adverse event or serious adverse event at least possibly related to sunitinib. CONCLUSION: Sunitinib did not meet prespecified criteria to declare a signal of antitumor activity in patients with BC with either FGFR1 or FGFR2 alterations. Other treatments and clinical trials should be considered for these patient populations.

Feasibility and value of genomic profiling in cancer of unknown primary: real-world evidence from prospective profiling study.

Real-world evidence regarding the value of integrating genomic profiling (GP) in managing cancer of unknown primary (CUP) is limited. We assessed this clinical utility using a prospective trial of 158 patients with CUP (October 2016-September 2019) who underwent GP using next-generation sequencing designed to identify genomic alterations (GAs). Only 61 (38.6%) patients had sufficient tissue for successful profiling. GAs were seen in 55 (90.2%) patients of which GAs with US Food and Drug Administration-approved genomically matched therapy were seen in 25 (40.9%) patients. A change in therapy was recommended and implemented (primary endpoint of the study) in 16 (10.1%) and 4 (2.5%) patients of the entire study cohort, respectively. The most common reason for inability to implement the profiling-guided therapy was worsening of performance status (56.3%). Integrating GP in management of CUP is feasible but challenging because of paucity of tissue and aggressive natural history of the disease and requires innovative precision strategies.

The Maine Cancer Genomics Initiative: Implementing a Community Cancer Genomics Program Across an Entire Rural State.

PURPOSE: The Maine Cancer Genomics Initiative (MCGI) aimed to overcome patient- and provider-level barriers to using genomic tumor testing (GTT) in rural practices by providing genomic tumor boards (GTBs), clinician education, and access to comprehensive large-panel next-generation sequencing to all patients with cancer in Maine. This paper describes the successful implementation of the initiative and three key services made operative between 2016 and 2020. METHODS: A community-inclusive, hub-and-spoke approach was taken to implement the three program components: (1) a centralized GTB program; (2) a modular online education program, designed using an iterative approach with broad clinical stakeholders; and (3) GTT free of charge to clinicians and patients. Implementation timelines, participation metrics, and survey data were used to describe the rollout. RESULTS: The MCGI was launched over an 18-month period at all 19 oncology practices in the State. Seventy-nine physicians (66 medical oncologists, 5 gynecologic oncologists, 1 neuro-oncologist, and 7 pediatric oncologists) enrolled on the study, representing 100% of all practicing oncologists in Maine. Between July 2017 and September 2020, 1610 patients were enrolled. A total of 515 cases were discussed by 47 (73%) clinicians in 196 GTBs. Clinicians who participated in the GTBs enrolled significantly more patients on the study, stayed in Maine, and reported less time spent in clinical patient care. CONCLUSION: The MCGI was able to engage geographically and culturally disparate cancer care practices in a precision oncology program using a hub-and-spoke model. By facilitating access to GTT, structured education, and GTBs, we narrowed the gap in the implementation of precision oncology in one of the most rural states in the country.

Urban-Rural and Socioeconomic Differences in Patient Knowledge and Perceptions of Genomic Tumor Testing.

PURPOSE: Social determinants of health, such as rurality, income, and education, may widen health disparities by driving variation in patients' knowledge and perceptions of medical interventions. This effect may be greatest for medical technologies that are hard to understand and less accessible. This study explored whether knowledge and perceptions (expectations and attitudes) of patients with cancer toward large-panel genomic tumor testing (GTT), an emerging cancer technology, vary by patient rurality independent of other socioeconomic characteristics (education and income). METHODS: Patients with cancer enrolled in a large precision oncology initiative completed surveys measuring rurality, sociodemographic characteristics, and knowledge and perceptions of GTT. We used multivariable linear models to examine differences in GTT knowledge, expectations, and attitudes by patient rurality, education, and income level. Models controlled for age, sex and clinical cancer stage and type. RESULTS: Rural patients had significantly lower knowledge of GTT than urban patients using bivariate models (P = .025). However, this association disappeared when adjusting for education and income level: patients with lower educational attainment and lower income had lower knowledge and higher expectations (P ≤ .002), whereas patients with higher income had more positive attitudes (P = .005). Urban patients had higher expectations of GTT compared with patients living in large rural areas (P = .011). Rurality was not associated with attitudes. CONCLUSION: Patients' education and income level are associated with knowledge, expectations, and attitudes toward GTT, whereas rurality is associated with patient expectations. These findings suggest that efforts to promote adoption of GTT should focus on improving knowledge and awareness among individuals with low education and income. These differences may lead to downstream disparities in GTT utilization, which should be explored in future research.

Epistemic Beliefs: Relationship to Future Expectancies and Quality of Life in Cancer Patients.

CONTEXT: Expectations about the future (future expectancies) are important determinants of psychological well-being among cancer patients, but the strategies patients use to maintain positive and cope with negative expectancies are incompletely understood. OBJECTIVES: To obtain preliminary evidence on the potential role of one strategy for managing future expectancies: the adoption of "epistemic beliefs" in fundamental limits to medical knowledge. METHODS: A sample of 1307 primarily advanced-stage cancer patients participating in a genomic tumor testing study in community oncology practices completed measures of epistemic beliefs, positive future expectancies, and mental and physical health-related quality of life (HRQOL). Descriptive and linear regression analyses were conducted to assess the relationships between these factors and test two hypotheses: 1) epistemic beliefs affirming fundamental limits to medical knowledge ("fallibilistic epistemic beliefs") are associated with positive future expectancies and mental HRQOL, and 2) positive future expectancies mediate this association. RESULTS: Participants reported relatively high beliefs in limits to medical knowledge (M = 2.94, s.d.=.67) and positive future expectancies (M = 3.01, s.d.=.62) (range 0-4), and relatively low mental and physical HRQOL. Consistent with hypotheses, fallibilistic epistemic beliefs were associated with positive future expectancies (b = 0.11, SE=.03, P< 0.001) and greater mental HRQOL (b = 0.99, SE=.34, P = 0.004); positive expectancies also mediated the association between epistemic beliefs and mental HRQOL (Sobel Z=4.27, P<0.001). CONCLUSIONS: Epistemic beliefs in limits to medical knowledge are associated with positive future expectancies and greater mental HRQOL; positive expectancies mediate the association between epistemic beliefs and HRQOL. More research is needed to confirm these relationships and elucidate their causal mechanisms.

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.

Community oncologists' perceptions and utilization of large-panel genomic tumor testing.

PURPOSE: Large-panel genomic tumor testing (GTT) is an emerging technology with great promise but uncertain clinical value. Previous research has documented variability in academic oncologists' perceptions and use of GTT, but little is known about community oncologists' perceptions of GTT and how perceptions relate to clinicians' intentions to use GTT. METHODS: Community oncology physicians (N = 58) participating in a statewide initiative aimed at improving access to large-panel GTT completed surveys assessing their confidence in using GTT, attitudes regarding the value of GTT, perceptions of barriers to GTT implementation, and future intentions to use GTTs. Descriptive and multivariable regression analyses were conducted to characterize these perceptions and to explore the relationships between them. RESULTS: There was substantial variability in clinicians' perceptions of GTT. Clinicians generally had moderate confidence in their ability to use GTT, but lower confidence in patients' ability to understand test results and access targeted treatment. Clinicians had positive attitudes regarding the value of GTT. Clinicians' future intentions to use GTT were associated with greater confidence in using GTT and greater perceived barriers to implementing GTT, but not with attitudes about the value of GTT. CONCLUSIONS: Community oncologists' perceptions of large-panel genomic tumor testing are variable, and their future intentions to use GTT are associated with both their confidence in and perceived barriers to its use, but not with their attitudes towards GTT. More research is needed to understand other factors that determine how oncologists perceive and use GTT in clinical practice.

Patients' Expectations of Benefits From Large-Panel Genomic Tumor Testing in Rural Community Oncology Practices.

Large-panel genomic tumor testing (GTT) is an emerging technology that promises to make cancer treatment more precise. Because GTT is novel and complex, patients may have unrealistic expectations and limited knowledge of its benefits. These problems may limit the clinical value of GTT, but their prevalence and associated factors have not been explored. METHODS: Patients with cancer enrolled in a large initiative to disseminate GTT in community oncology practices completed surveys assessing their expectations, knowledge, and attitudes about GTT. The study sample (N = 1,139) consisted of patients with a range of cancer types (22% gynecologic, 14% lung, 10% colon, 10% breast, and 46% other malignancies) and cancer stages (4% stage I, 3% stage II, 15% stage III, and 74% stage IV). Mean age was 64 years (standard deviation = 11); 668 (59%) were women; 71% had no college degree; 57% came from households with less than $50,000 US dollars household income; and 73% lived in a rural area. RESULTS: Generally, patients had high expectations that they would benefit from GTT (M = 2.81 on 0-4 scale) and positive attitudes toward it (M = 2.98 on 0-4 scale). Patients also had relatively poor knowledge about GTT (48% correct answers on an objective test of GTT knowledge). Greater expectations for GTT were associated with lower knowledge (b = -0.46; P < .001), more positive attitudes (b = 0.40; P < .001), and lower education (b = -0.53; P < .001). CONCLUSION: This research suggests patients have high expectations that they will benefit from GTT, which is associated with low knowledge, positive attitudes, and low education. More research is needed to understand the concordance between expectations and actual clinical outcomes.

The influence of uncertainty and uncertainty tolerance on attitudes and self-efficacy about genomic tumor testing.

Novel medical technologies, like large-panel genomic tumor testing (GTT), offer great promise but also substantial uncertainty regarding their clinical value and appropriate use. The goal of this study was to understand how clinicians' perceived uncertainty about GTT, and uncertainty tolerance (UT), a construct that describes trait-level differences in individuals' responses to uncertainty, influence attitudes and self-efficacy regarding GTT. Community-based oncologists participating in a study of large-panel GTT completed surveys assessing their perceptions of uncertainty about GTT, and their attitudes and self-efficacy regarding GTT. Multivariable regression analyses examined the relationship between oncologists' perceived uncertainty of GTT and their GTT-related attitudes and self-efficacy, and the potential moderating effect of individual differences in UT. Fifty-seven oncologists completed surveys. Greater perceived uncertainty about GTT was associated with more negative attitudes towards it. This association was moderated by UT, such that lower UT was associated with a stronger negative relationship between perceived uncertainty and attitudes. That is, oncologists who perceive GTT as uncertain, tended to have more negative attitudes, particularly if they were low in the trait of uncertainty tolerance. More research is warranted to understand how uncertainty and uncertainty tolerance influence clinicians' responses to GTT and other novel medical interventions.

Differences in cancer patients' and clinicians' preferences for disclosure of uncertain genomic tumor testing results.

OBJECTIVE: To compare clinicians' and patients' preferences for disclosure of genomic tumor testing (GTT) results; to determine the sensitivity of these disclosure preferences to uncertainty about the actionability of results; and to explore factors associated with disclosure preferences. METHODS: Community-based oncology clinicians (n = 94) and patients (n = 1121) were surveyed about their preferences for disclosing GTT results with varying levels of uncertainty (Tiers 1, 2, 3). Descriptive and multivariable regression analyses were used to compare clinicians' and patients' disclosure preferences and their sensitivity to uncertainty, and to explore associations between disclosure preferences and sociodemographic, clinical, and psychological factors. RESULTS: Relatively more patients than clinicians preferred disclosure, and their preferences were less sensitive to the uncertainty of GTT results. For patients and clinicians, lower uncertainty sensitivity was associated with positive GTT attitudes; for patients it was also associated with greater uncertainty tolerance and knowledge of uncertainty in GTT. CONCLUSION: Relatively more cancer patients than clinicians prefer disclosure of GTT results, and their preferences are less sensitive to result uncertainty. Uncertainty sensitivity in disclosure preferences is associated with GTT-related attitudes and uncertainty tolerance. PRACTICE IMPLICATIONS: Differences in cancer patients' and clinicians' preferences for disclosure of uncertain GTT results warrant greater attention in cancer care.

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's primary cancer remains fundamental to their treatment, CUP patients are significantly disadvantaged and most have a poor survival outcome. Developing robust and accessible diagnostic methods for resolving cancer tissue of origin, therefore, has significant value for CUP patients. METHODS: We developed an RNA-based classifier called CUP-AI-Dx that utilizes a 1D Inception convolutional neural network (1D-Inception) model to infer a tumor's primary tissue of origin. CUP-AI-Dx was trained using the transcriptional profiles of 18,217 primary tumours representing 32 cancer types from The Cancer Genome Atlas project (TCGA) and International Cancer Genome Consortium (ICGC). Gene expression data was ordered by gene chromosomal coordinates as input to the 1D-CNN model, and the model utilizes multiple convolutional kernels with different configurations simultaneously to improve generality. The model was optimized through extensive hyperparameter tuning, including different max-pooling layers and dropout settings. For 11 tumour types, we also developed a random forest model that can classify the tumour's molecular subtype according to prior TCGA studies. The optimised CUP-AI-Dx tissue of origin classifier was tested on 394 metastatic samples from 11 tumour types from TCGA and 92 formalin-fixed paraffin-embedded (FFPE) samples representing 18 cancer types from two clinical laboratories. The CUP-AI-Dx molecular subtype was also independently tested on independent ovarian and breast cancer microarray datasets FINDINGS: CUP-AI-Dx identifies the primary site with an overall top-1-accuracy of 98.54% in cross-validation and 96.70% on a test dataset. When applied to two independent clinical-grade RNA-seq datasets generated from two different institutes from the US and Australia, our model predicted the primary site with a top-1-accuracy of 86.96% and 72.46% respectively. INTERPRETATION: The CUP-AI-Dx predicts tumour primary site and molecular subtype with high accuracy and therefore can be used to assist the diagnostic work-up of cancers of unknown primary or uncertain origin using a common and accessible genomics platform. FUNDING: NIH R35 GM133562, NCI P30 CA034196, Victorian Cancer Agency Australia.

Molecular profiling of gynecologic cancers for treatment and management of disease - demonstrating clinical significance using the AMP/ASCO/CAP guidelines for interpretation and reporting of somatic variants.

Molecular features of gynecologic cancers have been investigated in comprehensive studies, but correlation of these molecular signatures with clinical significance for precision medicine is yet to be established. Towards this end, we evaluated 95 gynecologic cancer cases submitted for testing using The JAX ActionSeq™ NGS panel. Molecular profiles were studied and compared to TCGA datasets to identify similarities and distinguishing features among subtypes. We identified 146 unique clinically significant variants (Tier I and II) across 45 of the 212 genes (21%), in 87% (83/95) of cases. TP53, PTEN, ARID1A, PIK3CA and ATM were the most commonly mutated genes; CCNE1 and ERBB2 amplifications were the most frequently detected copy-number alterations. PARP inhibitors were among the most commonly reported drug class with clinical trials, consistent with the frequency of DNA damage-response pathway mutations in our cohort. Overall, our study provides additional insight into the molecular profiles of gynecologic cancers, highlighting regulatory pathways involved, raising the potential implications for targeted therapeutic options currently available.

Molecular profiling of CNS tumors for the treatment and management of disease.

The World Health Organization (WHO) has defined more than 130 distinct central nervous system (CNS) tumor entities, of which glioblastoma is the most fatal primary brain tumor. However, the correlation of the molecular signatures of glioblastoma with clinical significance for precision medicine is not well-known. How, and to what extent these variants may affect clinical decision making remains uncertain. Here, we evaluate 48 glioblastomas submitted for testing using the JAX ActionSeq™ Next-generation sequencing (NGS) panel. We identified 131 clinically significant variants (Tier I and II) across 30 of the 212 genes (14%). TP53, EGFR, PTEN, IDH1 were the most commonly mutated genes; EGFR, CDK4 amplifications, and CDKN2A deletion were the most frequently detected copy-number alterations. CDK4/6 and PI3K inhibitors were among the most commonly reported drug class with FDA approved therapies and investigational therapies, which is consistent with the frequencies of these genes in our cohort. Overall, our study established the molecular profiles of glioblastoma based on the 2017 joint consensus guidelines by AMP/ASCO/CAP and provides the potential implications for targeted therapeutic options currently available.

Umbralisib in combination with ibrutinib in patients with relapsed or refractory chronic lymphocytic leukaemia or mantle cell lymphoma: a multicentre phase 1-1b study.

BACKGROUND: Patients with relapsed or refractory high-risk chronic lymphocytic leukaemia or mantle cell lymphoma often do not derive durable benefit from ibrutinib monotherapy. We hypothesised that dual B-cell receptor pathway blockade would be tolerable and efficacious. We investigated a next-generation phosphoinositide-3-kinase-δ inhibitor (PI3K-δi), umbralisib, plus a Bruton tyrosine kinase inhibitor (BTKi), ibrutinib, in relapsed or refractory chronic lymphocytic leukaemia and mantle cell lymphoma. METHODS: We did an investigator-initiated, multicentre, phase 1-1b study of patients from five sites in the USA (academic and community sites). Patients were 18 years and older with relapsed or refractory chronic lymphocytic leukaemia or mantle cell lymphoma, with an Eastern Cooperative Oncology Group performance status of 2 or less, and were given umbralisib orally once daily (400 mg, 600 mg, or 800 mg) and ibrutinib orally once daily (420 mg for chronic lymphocytic leukaemia or 560 mg for mantle cell lymphoma) until disease progression or unacceptable toxicity. The phase 1 dose-escalation cohorts for each histology escalated independently in a standard 3 × 3 design. The primary endpoints were intention-to-treat assessment of maximum-tolerated dose, safety, and dose-limiting toxicities. This trial is ongoing and is registered with ClinicalTrials.gov, number NCT02268851. FINDINGS: Between Dec 5, 2014, and March 7, 2018, we enrolled 44 patients, of which 42 were given at least one dose of study drug (chronic lymphocytic leukaemia, n=21; mantle cell lymphoma, n=21). Patients had a median age of 68 years (range 48-85) and had a median of two (IQR 1-3) previous therapies. No dose-limiting toxicities were observed and the maximum-tolerated dose of umbralisib was not reached. The recommended phase 2 dose of umbralisib when given in combination with ibrutinib was 800 mg once daily. The most frequent adverse events included diarrhoea (22 [52%] patients, 10% of whom had grade 3), infection (21 [50%], 17% grade 3-4), and transaminitis (ten [24%], 2% grade 3). Serious adverse events occurred in 12 (29%) patients and included lipase elevation, atrial fibrillation, hypophosphataemia, adrenal insufficiency, transaminitis, and infections. INTERPRETATION: Umbralisib plus ibrutinib is well tolerated and active in relapsed or refractory chronic lymphocytic leukaemia and mantle cell lymphoma, with a recommended phase 2 dose of umbralisib 800 mg once daily. To the best of our knowledge, these are the first clinical data on a BTKi and PI3K-δi doublet in B-cell malignancies, and the results suggest that this approach is feasible and worthy of further study. FUNDING: TG Therapeutics, Leukemia and Lymphoma Society Therapy Accelerator Program.

Genomic Profiling of Two Histologically Distinct Rare Urothelial Cancers in a Clinical Setting to Identify Potential Therapeutic Options for Treatment and Management of Disease.

Molecular profiling of urothelial cancers for therapeutic and prognostic potential has been very limited due to the absence of cancer-specific targeted therapies. We describe here 2 clinical cases with a histological diagnosis of an invasive sarcomatoid and a poorly differentiated carcinoma favoring urothelial with some neuroendocrine differentiation, two of the rarer types of urothelial cancers, which were evaluated for mutations in 212 genes for single-nucleotide variants and copy-number variants and 53 genes for fusions associated with solid tumors. In both cases, we identified variants in 2 genes, ARID1A and CDKN2A, indicative of the role of dysregulation of chromatin remodeling and cell cycle control as being common features of bladder cancer, consistent with the proposed model of tumorigenesis in these rare, highly aggressive pathological subtypes. The presence of a KRAS mutation in the poorly differentiated cancer and a TP53 mutation in the sarcomatoid tumor is indicative of a distinctive profile and adds a potential layer of molecular stratification to these rarer histological subtypes. We present a comparative analysis of the histological, clinical, and molecular profile of both cases and discuss the potential to delineate these tumors at the molecular level keeping in mind the possible therapeutic implications.

Additive and synergistic inhibition of mantle cell lymphoma cell growth by combining olaparib with ibrutinib.

Mantle cell lymphoma (MCL) presents a therapeutic challenge. The B cell targeting agent, ibrutinib, is currently one of the most effective second-line therapies for MCL, but frequently leads to development of drug resistance, and short overall survival time upon relapse. Olaparib targets tumor cells with deficiencies in single-strand DNA break repair and thus may slow the development of genetic drug resistance. We found that the olaparib-ibrutinib combination significantly inhibits cell culture growth compared to either drug alone in two genetically distinct MCL cell lines. Moreover, these inhibitory effects are either additive or synergistic, depending on genetic background. Culture growth is inhibited due to increases in apoptosis, cell death, and cell cycle arrest, and the magnitude of each is cell line dependent. The additive and synergistic inhibition of this combination additionally supports a therapeutic strategy involving lower dosing of each drug to reduce potential side effects.

Local endothelial complement activation reverses endothelial quiescence, enabling t-cell homing, and tumor control during t-cell immunotherapy.

Cancer immunotherapy relies upon the ability of T cells to infiltrate tumors. The endothelium constitutes a barrier between the tumor and effector T cells, and the ability to manipulate local vascular permeability could be translated into effective immunotherapy. Here, we show that in the context of adoptive T cell therapy, antitumor T cells, delivered at high enough doses, can overcome the endothelial barrier and infiltrate tumors, a process that requires local production of C3, complement activation on tumor endothelium and release of C5a. C5a, in turn, acts on endothelial cells promoting the upregulation of adhesion molecules and T-cell homing. Genetic deletion of C3 or the C5a receptor 1 (C5aR1), and pharmacological blockade of C5aR1, impaired the ability of T cells to overcome the endothelial barrier, infiltrate tumors, and control tumor progression in vivo, while genetic chimera mice demonstrated that C3 and C5aR1 expression by tumor stroma, and not leukocytes, governs T cell homing, acting on the local endothelium. In vitro, endothelial C3 and C5a expressions were required for endothelial activation by type 1 cytokines. Our data indicate that effective immunotherapy is a consequence of successful homing of T cells in response to local complement activation, which disrupts the tumor endothelial barrier.