Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations

Although patient-derived xenografts (PDXs) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and access to a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

Targeting DNA2 overcomes metabolic reprogramming in multiple myeloma

DNA damage resistance is a major barrier to effective DNA-damaging therapy in multiple myeloma (MM). To discover mechanisms through which MM cells overcome DNA damage, we investigate how MM cells become resistant to antisense oligonucleotide (ASO) therapy targeting Interleukin enhancer binding factor 2 (ILF2), a DNA damage regulator that is overexpressed in 70% of MM patients whose disease has progressed after standard therapies have failed. Here, we show that MM cells undergo adaptive metabolic rewiring to restore energy balance and promote survival in response to DNA damage activation. Using a CRISPR/Cas9 screening strategy, we identify the mitochondrial DNA repair protein DNA2, whose loss of function suppresses MM cells' ability to overcome ILF2 ASO-induced DNA damage, as being essential to counteracting oxidative DNA damage. Our study reveals a mechanism of vulnerability of MM cells that have an increased demand for mitochondrial metabolism upon DNA damage activation.

Effect of the peripartum depressive symptoms on the Internet use disorder of their offspring in late childhood: retrospective longitudinal study

Internet use disorder (IUD) is an emerging social and mental health concern. This study aimed to analyze the relative risk of IUD in late childhood among children whose mothers experienced peripartum depressive symptoms. This study included 762 participants (397 boys and 365 girls) and was conducted in 2017 (aged 9) and 2019 (aged 11). We analyzed the adjusted relative risk of being at high risk for IUD based on whether the mother experienced depressive symptoms during pregnancy or one month after delivery. We also considered the persistence of depressed mood for 4 months after delivery and the severity of peripartum depressive symptoms. From 2017, 20.7% of boys and 14.0% of girls were at high risk of developing IUD. Compared to the non-peripartum depressive group, girls whose mothers experienced peripartum depressive symptoms and those that persisted for 4 months were 1.084 and 1.124 times more likely to be at high risk of IUD (95% confidence interval = 1.005-1.170 and 1.013-1.248), respectively. There were no statistically significant differences among boys. Peripartum depressed mood could be one of risk factors of IUD. IUD needs to be monitored in children whose mothers experienced peripartum depressive symptoms.

Efficacy of futibatinib, an irreversible fibroblast growth factor receptor inhibitor, in FGFR-altered breast cancer

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.

3-Phosphoinositide-dependent kinase 1 drives acquired resistance to osimertinib

Osimertinib sensitive and resistant NSCLC NCI-H1975 clones are used to model osimertinib acquired resistance in humanized and non-humanized mice and delineate potential resistance mechanisms. No new EGFR mutations or loss of the EGFR T790M mutation are found in resistant clones. Resistant tumors grown under continuous osimertinib pressure both in humanized and non-humanized mice show aggressive tumor regrowth which is significantly less sensitive to osimertinib as compared with parental tumors. 3-phosphoinositide-dependent kinase 1 (PDK1) is identified as a potential driver of osimertinib acquired resistance, and its selective inhibition by BX795 and CRISPR gene knock out, sensitizes resistant clones. In-vivo inhibition of PDK1 enhances the osimertinib sensitivity against osimertinib resistant xenograft and a patient derived xenograft (PDX) tumors. PDK1 knock-out dysregulates PI3K/Akt/mTOR signaling, promotes cell cycle arrest at the G1 phase. Yes-associated protein (YAP) and active-YAP are upregulated in resistant tumors, and PDK1 knock-out inhibits nuclear translocation of YAP. Higher expression of PDK1 and an association between PDK1 and YAP are found in patients with progressive disease following osimertinib treatment. PDK1 is a central upstream regulator of two critical drug resistance pathways: PI3K/AKT/mTOR and YAP.

Association between changes in having of cancer patients in the family and depression: A longitudinal panel study

BACKGROUND

Cancer diagnosis can cause considerable stress among patients and their families. Both may experience clinical depression and severe anxiety. Therefore, this study investigated the association between the occurrence of cancer patients in the family and the depression among family members.

METHODS

Data from the Korean Longitudinal Study of Aging (2006-2020) were used. A total of 6251 participants who completed the short-form Center for Epidemiologic Studies Depression Scale (CESD-10-D) questionnaire were included. General estimating equations were used to assess the temporal effects of changes on depression in the presence of cancer patients in the family.

RESULTS

Having cancer patients in the family was associated with a high risk of depression among both men and women (men, Odd Ratios (OR):1.78, 95 % Confidence Intervals (CI) 1.13-2.79; women, OR:1.53, 95 % CI 1.06-2.22). Depressive symptoms were particularly high in women, especially when cancer symptoms were more severe than previous surveys (OR: 2.48, 95 % CI 1.18-5.20).

LIMITATIONS

First, non-responders were excluded but this could be affected by underestimation bias. Second, depression was defined as the CESD-10-D score, and the biological risk factors of depression could not be identified because of survey-based database. Third, due to the retrospective design study, confirming the causal relationship clearly is difficult. Finally, residual scheming effects of unmeasured variables could not be eliminated.

CONCLUSION

Our findings support efforts to diagnose and manage depression in the families of cancer patients. Accordingly, healthcare services and supportive interventions to reduce the psychological factors of cancer patients' families are needed.

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes

MOTIVATION

Multilevel molecular profiling of tumors and the integrative analysis with clinical outcomes have enabled a deeper characterization of cancer treatment. Mediation analysis has emerged as a promising statistical tool to identify and quantify the intermediate mechanisms by which a gene affects an outcome. However, existing methods lack a unified approach to handle various types of outcome variables, making them unsuitable for high-throughput molecular profiling data with highly interconnected variables.

RESULTS

We develop a general mediation analysis framework for proteogenomic data that include multiple exposures, multivariate mediators on various scales of effects as appropriate for continuous, binary and survival outcomes. Our estimation method avoids imposing constraints on model parameters such as the rare disease assumption, while accommodating multiple exposures and high-dimensional mediators. We compare our approach to other methods in extensive simulation studies at a range of sample sizes, disease prevalence and number of false mediators. Using kidney renal clear cell carcinoma proteogenomic data, we identify genes that are mediated by proteins and the underlying mechanisms on various survival outcomes that capture short- and long-term disease-specific clinical characteristics.

AVAILABILITY AND IMPLEMENTATION

Software is made available in an R package (https://github.com/longjp/mediateR).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes and genomic phenotypes

BACKGROUND AND AIMS

Although many studies revealed transcriptomic subtypes of HCC, concordance of the subtypes are not fully examined. We aim to examine a consensus of transcriptomic subtypes and correlate them with clinical outcomes.

APPROACH AND RESULTS

By integrating 16 previously established genomic signatures for HCC subtypes, we identified five clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features, but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent β-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high hepatocyte nuclear factor 4A activity. We also developed and validated a robust predictor of consensus subtype with 100 genes and demonstrated that five subtypes were well conserved in patient-derived xenograft models and cell lines. By analyzing serum proteomic data from the same patients, we further identified potential serum biomarkers that can stratify patients into subtypes.

CONCLUSIONS

Five HCC subtypes are correlated with genomic phenotypes and clinical outcomes and highly conserved in preclinical models, providing a framework for selecting the most appropriate models for preclinical studies.

CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts

Anticancer combination therapy has been developed to increase efficacy by enhancing synergy. Patient-derived xenografts (PDXs) have emerged as reliable preclinical models to develop effective treatments in translational cancer research. However, most PDX combination study designs focus on single dose levels, and dose-response surface models are not appropriate for testing synergism. We propose a comprehensive statistical framework to assess joint action of drug combinations from PDX tumor growth curve data. We provide various metrics and robust statistical inference procedures that locally (at a fixed time) and globally (across time) access combination effects under classical drug interaction models. Integrating genomic and pharmacological profiles in non-small-cell lung cancer (NSCLC), we have shown the utilities of combPDX in discovering effective therapeutic combinations and relevant biological mechanisms. We provide an interactive web server, combPDX ( https://licaih.shinyapps.io/CombPDX/ ), to analyze PDX tumor growth curve data and perform power analyses.

Abstract 5354: 3-phosphoinositide-dependent kinase-1 (PDK1, PDPK1) is a driver of osimertinib acquired resistance in EGFR mutant NSCLC

Osimertinib, the only third-generation EGFR-TKI, showed incomplete responses to T790M-mutant NSCLC due to acquired resistance caused by activation of bypass pathways. We developed osimertinib-acquired resistant H1975-OSIR (T790M/L858R mutant) isogenic cells and TC386-OSIR isogenic PDXs. Neither H1975-OSIR nor TC386-OSIR PDXs developed additional mutations in EGFR. The H1975-OSIR clone showed 100 fold higher resistance to osimertinib compared with H1975 cells. TC386-OSIR PDX was developed through continuous in-vivo treatment for 8 months and the residual PDXs were passaged for several generations under continuous osimertinib treatment. TC386-OSIR fourth resistant generation (RG4) showed significantly higher resistance than initial generations (RG1). H1975-OSIR xenografts were developed in non-humanized and humanized NSG mice under osimertinib pressure. H1975-OsiR tumors were significantly less sensitive to osimertinib than their parental counterparts in both mouse models. Dose dependent antitumor activity of osimertinib (5mg/kg and 10mg/kg) was observed in H1975-parental tumors, whereas no treatment effect was observed for H1975-OsiR tumors with increasing doses. The tumor microenvironment was enriched with higher infiltration of tumor associated macrophages (TAM) and lower numbers of tumor infiltrating lymphocytes (TIL) in H1975-OSIR vs H1975 tumors. RPPA analysis of residual tumor tissues showed a distinct set of proteins upregulated in H1975-OsiR vs H1975-parental, among which PDK1 was the most upregulated. PDK1 was also significantly upregulated in H1975-OsiR tumors treated with osimertinib vs controls. PDK1 was not altered in any treatment groups in H1975-parental tumors. PDK1 and pPDK1 expression was many-fold higher in both H1975-OSIR cells and TC386-OSIR PDXs as compared to their parental counterparts by western blot and mass spec proteomics. Selective inhibition by the PDK inhibitor, BX 795, and CRISPR knock-out (KO) restored osimertinib sensitivity in resistant cells. Colony forming assays showed that the PDK1 KO clone was as sensitive as H1975-parental cells whereas a PDK overexpressing clone (OE) restored resistance. In-vivo inhibition of PDK1 by treating mice with BX-795 in both H1975-OSIR xenografts and TC386-OSIR PDXs significantly enhanced the antitumor activity of osimertinib. PDK1 KO dysregulated PI3K/Akt/mTOR signaling by downregulating Akt and mTOR phosphorylation and promoted cell cycle arrest at the G1 phase. NCI-H1975-OSIR and PDK1 OE cells showed a high level of nuclear localization of the activated Yes-associated protein pYAP(Y357). PDK1 KO cells significantly reduced nuclear localization of pYAP(Y357). The level of YAP and pYAP was upregulated in osimertinib resistant xenograft tumors and residual tumor biopsies. Taken together, we identified PDK1 as a drug able target to treat osimertinib acquired resistance.

Citation Format: Ismail M. Meraz, Mourad Majidi, Bingliang Fang, Feng Meng, Lihui Gao, RuPing Shao, Renduo Song, Feng Li, Min Jin Ha, Qi Wang, Jing Wang, Elizabeth Shpall, Sung Yun Jung, Franziska Haderk, Philippe Gui, Jonathan W. Riess, Victor Olivas, Trever G. Bivona, Jack A. Roth. 3-phosphoinositide-dependent kinase-1 (PDK1, PDPK1) is a driver of osimertinib acquired resistance in EGFR mutant NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5354.

TUSC2 immunogene enhances efficacy of chemo-immuno combination on KRAS/LKB1 mutant NSCLC in humanized mouse model

KRAS/LKB1 (STK11) NSCLC metastatic tumors are intrinsically resistant to anti-PD-1 or PD-L1 immunotherapy. In this study, we use a humanized mouse model to show that while carboplatin plus pembrolizumab reduce tumor growth moderately and transiently, the addition of the tumor suppressor gene TUSC2, delivered systemically in nanovesicles, to this combination, eradicates tumors in the majority of animals. Immunoprofiling of the tumor microenvironment shows the addition of TUSC2 mediates: (a) significant infiltration of reconstituted human functional cytotoxic T cells, natural killer cells, and dendritic cells; (b) induction of antigen-specific T cell responses; (c) enrichment of functional central and memory effector T cells; and (d) decreased levels of PD-1⁺ T cells, myeloid-derived suppressor cells, Tregs, and M2 tumor associated macrophages. Depletion studies show the presence of functional central and memory effector T cells are required for the efficacy. TUSC2 sensitizes KRAS/LKB1 tumors to carboplatin plus pembrolizumab through modulation of the immune contexture towards a pro-immune tumor microenvironment.

Meraz et al. explore the antitumor efficacy of TUSC2 tumor suppressor genetherapy via nanovisicles in combination with carboplatin and pembrolizumab against KRAS-LKB1 mutant NSCLC in humanized mouse model. They demonstrate a robust response and perform immune profiling studies, which show the development of a cytotoxic T cell effector response and effector memory cells.

Abstract P1-19-01: Palbociclib plus endocrine therapy significantly enhances overall survival of HR+/HER2- metastatic breast cancer patients compared to endocrine therapy alone - A large institutional study

PURPOSE: Cyclin-dependent kinase 4/6 inhibitor (CDKi) therapy combined with endocrinetherapy is considered standard of care for patients with advanced hormone receptor (HR)-positive, HER2-negative breast cancer (BC). The Breast Medical Oncology Database at MDAnderson Cancer Center (MDACC) was analyzed to assess effectiveness of CDKi+palbociclib. PATIENTS AND METHODS: From a total of 5402 advanced HR+ HER2- BC patients referred toMDACC between 1997 and 2020, we identified eligible patients who received palbociclib incombination with first- (n=778) and second-line (n=410) endocrine therapy. We furtheridentified “control” patients who received endocrine therapy alone in the first- (n=2452) andsecond-line (n=1183) setting. We conducted a propensity score matching analysis to balancethe baseline demographic and clinical characteristics between the palbociclib treated andcontrol cohorts to assess the effect of palbociclib treatment on progression-free survival (PFS)and overall survival (OS). Stratified log-rank test was used to assess the effect of palbociclib inthe matched cohorts. RESULTS: For the propensity-matched cohort in the first-line setting (n=708), the palbociclibgroup had significantly longer median PFS (17.4 vs. 11.1 months; p<0.0001) compared tocontrols. Median OS (44.3 vs. 40.2 months; p =1) did not show any survival benefit in the firstline setting. However, in the second-line setting, with 380 propensity-matched cohort, thepalbociclib group had significantly longer PFS (10 vs 5 months, p<0.0001) as well as OS (33 vs 24months; p < 0.022), compared to controls.2. CONCLUSION: In this single center analysis, of a large cohort of metastatic HR+ HER2- BCpatients, palbociclib in combination with endocrine therapy was associated with improved PFSin both first- and second-line settings and OS in the second-line setting compared withendocrine therapy alone cohort.3

Citation Format: Akshara Singareeka Raghavendra, Min Jin Ha, Nicole M. Kettner, Senthil Damodaran, Rachel Layman, Kelly K Hunt, Yu Shen, Debu Tripathy, Khandan Keyomarsi. Palbociclib plus endocrine therapy significantly enhances overall survival of HR+/HER2- metastatic breast cancer patients compared to endocrine therapy alone - A large institutional study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-19-01.

Palbociclib plus endocrine therapy significantly enhances overall survival of HR+/HER2- metastatic breast cancer patients compared to endocrine therapy alone in the second-line setting-a large institutional study

Cyclin-dependent-kinase-4/6 inhibitor (CDKi) plus endocrine therapy (ET) is standard of care for patients with advanced hormone receptor (HR)-positive, HER2-negative breast cancer (BC). The Breast Medical Oncology database at MD Anderson Cancer Center (MDACC) was analyzed to assess effectiveness of the CDKi palbociclib plus ET compared to ET alone. From a total of 5402 advanced HR+ HER2- BC patients referred to MDACC between 1997 and 2020, we identified eligible patients who received palbociclib in combination with first- (n=778) and second-line (n=410) ET. We further identified "control" patients who received ET alone in the first- (n=2452) and second-line (n=1183) settings. Propensity score matching analysis was conducted to balance baseline demographic and clinical characteristics between palbociclib and control cohorts to assess the effect of palbociclib treatment on progression-free survival (PFS) and overall survival (OS). For propensity-matched-cohort in the first-line setting (n=708), palbociclib group had significantly longer median PFS (17.4 vs. 11.1 months; p<0.0001) compared to controls. Median OS (44.3 vs. 40.2 months) did not show a statistically significant benefit in the first line setting. However, in the second-line setting, with 380 propensity-matched-cohort, the palbociclib group had significantly longer PFS (10 vs 5 months, p<0.0001) as well as OS (33 vs 24 months; p < 0.022), compared to controls. We conclude that in this single center analysis of a large cohort of metastatic HR+ HER2- BC patients, palbociclib in combination with ET was associated with improved PFS in both first- and second-line settings and OS in the second-line setting compared with ET alone cohort.

Sample Selection Bias in Evaluation of Prediction Performance of Causal Models

Causal models are notoriously difficult to validate because they make untestable assumptions regarding confounding. New scientific experiments offer the possibility of evaluating causal models using prediction performance. Prediction performance measures are typically robust to violations in causal assumptions. However prediction performance does depend on the selection of training and test sets. In particular biased training sets can lead to optimistic assessments of model performance. In this work, we revisit the prediction performance of several recently proposed causal models tested on a genetic perturbation data set of Kemmeren [5]. We find that sample selection bias is likely a key driver of model performance. We propose using a less-biased evaluation set for assessing prediction performance and compare models on this new set. In this setting, the causal models have similar or worse performance compared to standard association based estimators such as Lasso. Finally we compare the performance of causal estimators in simulation studies which reproduce the Kemmeren structure of genetic knockout experiments but without any sample selection bias. These results provide an improved understanding of the performance of several causal models and offer guidance on how future studies should use Kemmeren.

Combined MEK/MDM2 inhibition demonstrates antitumor efficacy in TP53 wild-type thyroid and colorectal cancers with MAPK alterations

Most tumors with activating MAPK (mitogen-activated protein kinase) pathway alterations respond poorly to MEK inhibitors alone. Here, we evaluated combination therapy with MEK inhibitor selumetinib and MDM2 inhibitor KRT-232 in TP53 wild-type and MAPK altered colon and thyroid cancer models. In vitro, we showed synergy between selumetinib and KRT-232 on cell proliferation and colony formation assays. Immunoblotting confirmed p53 upregulation and MEK pathway inhibition. The combination was tested in vivo in seven patient-derived xenograft (PDX) models (five colorectal carcinoma and two papillary thyroid carcinoma models) with different KRAS, BRAF, and NRAS mutations. Combination therapy significantly prolonged event-free survival compared with monotherapy in six of seven models tested. Reverse-phase protein arrays and immunohistochemistry, respectively, demonstrated upregulation of the p53 pathway and in two models cleaved caspase 3 with combination therapy. In summary, combined inhibition of MEK and MDM2 upregulated p53 expression, inhibited MAPK signaling and demonstrated greater antitumor efficacy than single drug therapy in both in vitro and in vivo settings. These findings support further clinical testing of the MEK/MDM2 inhibitor combination in tumors of epithelial origin with MAPK pathway alterations.

Abstract P058: Anti-tumor activity of ATR inhibitor BAY 1895344 in patient-derived xenograft (PDX) models with DNA damage response (DDR) pathway alterations

Introduction: The ATR (ataxia-telangiectasia and Rad3 related protein) kinase inhibitor BAY 1895344 is currently in clinical development for the treatment of advanced solid tumors and has demonstrated promising antitumor activity in heavily pretreated patients with various advanced solid tumors, particularly those with ATM deleterious mutations and/or loss of ATM protein. There is further need to identify robust predictive biomarkers to optimize patient selection for ATR inhibitors. For that purpose, we tested the antitumor activity of BAY 1895344 in patient-derived xenograft (PDX) models that are characterized by a variety of DDR alterations. Methods: PDX models were characterized by genomic sequencing and ATM loss by immunohistochemistry (IHC). PDX models with deleterious ATM, BRCA1 or BRCA2 mutations or loss derived from a variety of histologies were tested. BAY1895344 treatment was tested with two monotherapy regimens 20 mg/kg and 40 mg/kg PO BID both 3 days on/4 days off. For in vivo studies, the percent tumor volume change per time point was calculated as a relative level of tumor growth change from baseline: , where is the tumor volume at time and is the tumor volume at baseline. T/C ratio was defined as the ratio of tumor volume change in treated vs control group. An event in each animal was defined as a doubling of tumor volume from initial tumor volume. Event free survival was analyzed by Kaplan-Meier survival analysis. Results: Seventeen PDX models from sixteen patients were treated with BAY 1895344. The PDX models spanned multiple tumor types: breast, colon, pancreas, and cholangiocarcinoma. BAY 1895344 has shown potent and dose-dependent antitumor activity. Strongest activity was observed with BAY 1895344 at 40 mg/kg PO BID applied for 3 days on and 4 days off treatment, achieving a regression or T/C ratio &lt;0.4 in 6 of 17 models. Eleven models showed statistically significant prolongation of event-free survival. BAY 1895344 had anti-tumor activity in PDX models with ATM loss as well as BRCA alterations. Notably BAY 1895344 had antitumor activity in an ATM-deleted PDX model with acquired PARP inhibitor resistance generated in the lab as well as a PDX model generated from a BRCA-mutant patient with clinically acquired PARP resistance. Conclusion: ATR inhibition via treatment with BAY 1895344 shows potent antitumor activity as monotherapy in selected models that are characterized by certain DDR alterations and even those that have developed resistance to PARP inhibition. Further analyses are ongoing to define predictors of sensitivity to BAY 1895344 as well as pharmacodynamic markers of efficacy/response as a single agent or in rational combinations

Citation Format: Christian X. Cruz Pico, Dali Li, Christopher D. Lanier, Kurt Evans, Maria G. Raso, Timothy DiPeri, Yasmeen Rizvi, Min Jin Ha, Huiqin Chen, Ming Zhao, Argun Akcakanat, Xiaofeng Zheng, Gokce Toruner, Erkan Yuca, Stephen Scott, Antje M. Wengner, Timothy A. Yap, Funda Meric-Bernstam. Anti-tumor activity of ATR inhibitor BAY 1895344 in patient-derived xenograft (PDX) models with DNA damage response (DDR) pathway alterations [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P058.

Cytoplasmic Cyclin E Expression Predicts for Response to Neoadjuvant Chemotherapy in Breast Cancer

BACKGROUND

Pathologic complete response (pCR) has been shown to be associated with favorable outcomes in breast cancer. Predictors of pCR could be useful in guiding treatment decisions regarding neoadjuvant therapy. The objective of this study was to evaluate cyclin E as a predictor of response to neoadjuvant chemotherapy in breast cancer.

METHODS

Patients (n = 285) with stage II-III breast cancer were enrolled in a prospective study and received neoadjuvant chemotherapy with anthracyclines, taxanes, or combination of the two. Pretreatment biopsies from 190 patients and surgical specimens following chemotherapy from 192 patients were available for immunohistochemical analysis. Clinical and pathologic responses were recorded and associated with presence of tumor infiltrating lymphocytes, cyclin E, adipophilin, programmed cell death-ligand 1, and elastase staining and other patient, tumor and treatment characteristics.

RESULTS

The pCR rate was significantly lower in patients with cytoplasmic cyclin E staining compared with those who had no cyclin E expression (16.1% vs 38.9%, P = 0.0005). In multivariable logistic regression analysis, the odds of pCR for patients who had cytoplasmic negative tumors was 9.35 times (P value < 0.0001) that compared with patients with cytoplasmic positive tumors after adjusting for ER, PR, and HER2 status. Cytoplasmic cyclin E expression also predicts long-term outcome and is associated with reduced disease free, recurrence free, and overall survival rates, independent of increased pretreatment tumor infiltrating lymphocytes.

CONCLUSIONS

Cyclin E independently predicted response to neoadjuvant chemotherapy. Hence, its routine immunohistochemical analysis could be used clinically to identify those breast cancer patients expected to have a poor response to anthracycline/taxane-based chemotherapy.

Bayesian Structure Learning in Multi-layered Genomic Networks

Integrative network modeling of data arising from multiple genomic platforms provides insight into the holistic picture of the interactive system, as well as the flow of information across many disease domains including cancer. The basic data structure consists of a sequence of hierarchically ordered datasets for each individual subject, which facilitates integration of diverse inputs, such as genomic, transcriptomic, and proteomic data. A primary analytical task in such contexts is to model the layered architecture of networks where the vertices can be naturally partitioned into ordered layers, dictated by multiple platforms, and exhibit both undirected and directed relationships. We propose a multi-layered Gaussian graphical model (mlGGM) to investigate conditional independence structures in such multi-level genomic networks in human cancers. We implement a Bayesian node-wise selection (BANS) approach based on variable selection techniques that coherently accounts for the multiple types of dependencies in mlGGM; this flexible strategy exploits edge-specific prior knowledge and selects sparse and interpretable models. Through simulated data generated under various scenarios, we demonstrate that BANS outperforms other existing multivariate regression-based methodologies. Our integrative genomic network analysis for key signaling pathways across multiple cancer types highlights commonalities and differences of p53 integrative networks and epigenetic effects of BRCA2 on p53 and its interaction with T68 phosphorylated CHK2, that may have translational utilities of finding biomarkers and therapeutic targets.

Abstract 76: TUSC2 immunogene therapy enhances efficacy of chemo-immune combination therapy and induces robust antitumor immunity in KRAS-LKB1 mutant NSCLC in humanized mice

Oncogenic KRAS-LKB1 (KL)-mutant NSCLC lung cancers are resistant to immune checkpoint blockade (ICB) therapy due to impaired immunogenicity. Carboplatin plus ICB, the first line of treatment for NSCLC, showed limited efficacy on KL subtypes. TUSC2, a novel immunogene delivered systemically via nanovesicles, induces apoptosis in tumor cells and promotes a variety of innate and adaptive immune responses. We recently developed an improved humanized mouse that reconstitutes a human immune system in NSG mice by transplanting fresh human cord blood derived CD34+ stem cells (Hu-mice). In this study, we evaluated the antitumor immune response of a chemo-immunotherapy combination with TUSC2 on highly metastatic KL-mutant human lung cancer in Hu-mice. Hu-mice were challenged with A549 cells (Krasmt/LKB1-) and lung metastases were treated with TUSC2, nivolumab, or the combination. The results showed a synergistic antitumor effect with the combination. When TUSC2 was combined with pembrolizumab (pembro), a significant antitumor effect was also found, which was correlated with significantly higher levels of T, CD69+ active T, NK and CD69+ active NK and significantly lower levels of MDSC and Treg. Pembro alone significantly reduced tumor burden as compared with control whereas no antitumor effect was observed in non-Hu-mice. The chemo-immune (carbo+pembro) combination significantly reduced tumor burden over chemo or ICB alone. When TUSC2 was added to the chemo+immune combination, metastases regression was significantly greater than either TUSC2, TUSC2+pembro or carbo+pembro treatments. The triple combination in Hu-mice showed significant infiltration of cytotoxic T cells, NK cells and less infiltration of Treg into lung metastasis. The triple treatment also induced an antigen-specific T cell response, which was as shown by the presence of a significantly higher percentage of IFN-γ+ T cells in a co-culture with A549 cells. No IFN-γ+ T cells were found in a co-culture with control lung epithelial cells. Downregulation of PD-1 in TILs and upregulation of matured DC (MHCIIhi CD86+) was found in triple treatment. Significant enrichment of central memory (CM;CCR7+CD45RA-) and effector memory (EM;CCR7-CD45RA-) T cells in triple combination was observed. The EM and CM T cells were functionally active, and showed significantly higher capacity of releasing IFN-γ when stimulated with PMA. Similarly, TUSC2 also showed enhanced efficacy with carbo+aPD1 in highly metastatic KRASmt CMT167 in syngeneic mice. The antitumor effect was linked with increased infiltration of CD8+T, CD3+CD44+ and CD8+CD44+ memory T, NK cells and significantly less Treg cells in the tumor. In conclusion, the triple combination showed strong antitumor efficacy and induced robust antitumor immunity in KL-mutant NSCLC in clinically relevant Hu-mice supporting a clinical trial

Citation Format: Ismail M. Meraz, Mourad Majidi, RuPing Shao, Feng Meng, Min Jin Ha, Elizabeth Shpall, Jack A. Roth. TUSC2 immunogene therapy enhances efficacy of chemo-immune combination therapy and induces robust antitumor immunity in KRAS-LKB1 mutant NSCLC in humanized mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 76.

Abstract 3009: A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers

Background: Despite increasing utilization of patient-derived xenografts (PDXs) in early drug development, there are no agreed upon metrics for assessment of PDX growth inhibition for agents given alone or in combination. In the present study, we aim to investigate what metrics are being used in the literature, as well as among the National Cancer Institute PDX Development and Trial Centers Research Network (PDXNet) investigators.

Methods: Relevant PDX literature was identified and retrieved using an information retrieval tool, RetriLite, to search for articles that met following criteria: 1) Published between 01/2018 through 12/2019; 2) Published in a journal with impact factor of 10 or above; 3) Search terms included: Cancer, PDX(s), patient derived xenograft(s), and patient-derived xenograft(s). Exclusion criteria included: 1) Brain tumors; 2) Immune-oncology/non-solid tumors; 3) Studies with no detailed information; 4) studies from PDXNet investigators. In addition, a questionnaire regarding PDX analysis practices was distributed to NCI PDXNet investigators and responses were analyzed.

Results: Sixty-five studies with relevant information were included in this systematic literature review and 15 NCI PDXNet PIs from all six centers responded to the survey representing the general practice in the network. The most commonly used tumor growth assessment metric was comparisons in tumor volumes in different treatment arms, used by 33 (51%) of 65 PDX papers and 13 (87%) of 15 PDXNet investigators. Thirteen different growth metrics were reported in the PDX literature and ten different metrics were used by PDXNet investigators. PDXNet investigators were more likely to use growth metrics analogous to clinical endpoints compared to the PDX literature, including percent change of tumor volume (80% vs 17%), event-free survival (EFS: 40% vs 11%), and overall survival (33% vs 8%). PDXNet investigators were also more likely to assess objective response rate (ORR) compared to the PDX literature (60% vs 12%); several different cutoffs were used for defining response and progression. For combination therapy, most investigators and literature compared tumor volumes across treatment arms, with few looking at measures of synergy or dynamic effects and with variable utilization of other metrics such as OR and EFS. In PDX literature, of the 40 papers with combination therapies presented, at least one monotherapy control arm was missing in 7 (18%), and four (10%) only compared growth with the no treatment control arm.

Conclusions: In summary, there is great variability in growth metrics used in the PDX community. To better use PDXs as preclinical models and increase the reproducibility of treatment effect on PDXs, a joint effort is needed to harmonize approaches in PDX growth assessment.

Citation Format: Dali Li, Min Jin Ha, Yvonne A. Evrard, Huiqin Chen, Lisa M. McShane, Jeffrey Grover, Jing Wang, Bingliang Fang, Timothy DiPeri, Michael T. Lewis, Lawrence Rubinstein, Jack A. Roth, Jeffrey H. Chuang, James H. Doroshow, Jeffrey A. Moscow, Funda Meric-Bernstam. A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3009.

LMW cyclin E and its novel catalytic partner CDK5 are therapeutic targets and prognostic biomarkers in salivary gland cancers

Salivary gland cancers (SGCs) are rare yet aggressive malignancies with significant histological heterogeneity, which has made prediction of prognosis and development of targeted therapies challenging. In majority of patients, local recurrence and/or distant metastasis are common and systemic treatments have minimal impact on survival. Therefore, identification of novel targets for treatment that can also be used as predictors of recurrence for multiple histological subtypes of SGCs is an area of unmet need. In this study, we developed a novel transgenic mouse model of SGC, efficiently recapitulating the major histological subtype (adenocarcinomas of the parotid gland) of human SGC. CDK2 knock out (KO) mice crossed with MMTV-low molecular weight forms of cyclin E (LMW-E) mice generated the transgenic mouse models of SGC, which arise in the parotid region of the salivary gland, similar to the common site of origin seen in human SGCs. To identify the CDK2 independent catalytic partner(s) of LMW-E, we used LMW-E expressing cell lines in mass spectrometric analysis and subsequent biochemical validation in pull down assays. These studies revealed that in the absence of CDK2, LMW-E preferentially binds to CDK5. Molecular targeting of CDK5, using siRNA, resulted in inhibition of cell proliferation of human SGCs overexpressing LMW-E. We also provide clinical evidence of significant association of LMW-E/CDK5 co-expression and decreased recurrence free survival in human SGC. Immunohistochemical analysis of LMW-E and CDK5 in 424 patients representing each of the four major histological subtypes of human salivary cancers (Aci, AdCC, MEC, and SDC) revealed that LMW-E and CDK5 are concordantly (positive/positive or negative/negative) expressed in 70% of these patients. The co-expression of LMW-E/CDK5 (both positive) robustly predicts the likelihood of recurrence, regardless of the histological classification of these tumors. Collectively, our results suggest that CDK5 is a novel and targetable biomarker for the treatment of patients with SGC presenting with LMW-E overexpressing tumors.

Genetic counselor approaches to BRCA1/2 direct-to-consumer genetic testing results

The National Comprehensive Cancer Network recommends clinical-grade genetic testing to confirm commercial results from direct-to-consumer genetic testing (DTC-GT) companies and third-party interpretation (TPI) services; however, the type of confirmatory testing that genetic counselors (GCs) recommend remains uncharacterized. Therefore, we aimed to describe GCs testing strategies for patients who have already obtained DTC-GT results (23andMe) or TPI data (Promethease) that reported a BRCA1/2 pathogenic variant. We invited GCs specializing in clinical cancer genetics to complete an online survey distributed to members of the National Society of Genetic Counselors. The survey, completed by 80 respondents, contained case scenarios featuring probands with variable personal and family histories of cancer. Our results show that the majority of participating GCs have counseled patients for their health-related commercial test results; 94% have encountered patient DTC-GT reports (3 per year), and 69% have encountered patient TPI data (2 per year). Most participating GCs would recommend confirmatory clinical-grade testing for probands with a positive 23andMe BRCA1/2 result (77/80, 96%). However, there was strong variability between the type of recommended testing. Approximately 20% recommended single-site analysis, 11%-14% recommended the three Ashkenazi Jewish BRCA1/2 founder mutations, 4% recommended BRCA1/2 testing, and 61%-64% recommended multi-gene panel testing. The most commonly recommended panels were split between a breast and gynecological cancer-focused panel and a broad pan-cancer panel. The majority of participants (98%-100%) would also recommend confirmatory testing for patients with positive TPI data for BRCA1/2. Similarly, results were mixed between those who recommended targeted, single-site analysis (10%-15%) compared to a multi-gene panel (72%-83%). These data show that while most GCs were uniform in their practice of recommending confirmatory testing, they are mixed in their approach to the specific type of testing they would select. These results may help inform counseling approaches and consensus for this expanding group of patients.

Compositional zero-inflated network estimation for microbiome data

BACKGROUND

The estimation of microbial networks can provide important insight into the ecological relationships among the organisms that comprise the microbiome. However, there are a number of critical statistical challenges in the inference of such networks from high-throughput data. Since the abundances in each sample are constrained to have a fixed sum and there is incomplete overlap in microbial populations across subjects, the data are both compositional and zero-inflated.

RESULTS

We propose the COmpositional Zero-Inflated Network Estimation (COZINE) method for inference of microbial networks which addresses these critical aspects of the data while maintaining computational scalability. COZINE relies on the multivariate Hurdle model to infer a sparse set of conditional dependencies which reflect not only relationships among the continuous values, but also among binary indicators of presence or absence and between the binary and continuous representations of the data. Our simulation results show that the proposed method is better able to capture various types of microbial relationships than existing approaches. We demonstrate the utility of the method with an application to understanding the oral microbiome network in a cohort of leukemic patients.

CONCLUSIONS

Our proposed method addresses important challenges in microbiome network estimation, and can be effectively applied to discover various types of dependence relationships in microbial communities. The procedure we have developed, which we refer to as COZINE, is available online at https://github.com/MinJinHa/COZINE .

KRT-232 and navitoclax enhance trametinib's anti-Cancer activity in non-small cell lung cancer patient-derived xenografts with KRAS mutations

Activating mutations of the KRAS gene are one of the major genomic alterations associated with tumorigenesis of non-small cell lung cancer (NSCLC). Thus far, treatment of KRAS-mutant NSCLC remains an unmet medical need. We determined the in vivo treatment responses of 13 KRAS mutant and 14 KRAS wild type NSCLC patient-derived xenografts (PDXs) to agents that target known NSCLC vulnerabilities: the MEK inhibitor trametinib, the MDM2 inhibitor KRT-232, and the BCL-X_L/BCL-2 inhibitor navitoclax. The results showed that the tumor regression rate after single agent therapy with KRT-232, trametinib and navitoclax was 11%, 10% and 0%, respectively. Combination therapies of trametinib plus KRT-232 and trametinib plus navitoclax led to improved partial response rates over single-agent activity in a subset of PDX models. Tumor regression was observed in 23% and 50% of PDXs after treatment with trametinib plus KRT-232 and trametinib plus navitoclax, respectively. The disease control rates in KRAS-mutant PDXs tested were 90%-100% after treatment with trametinib plus KRT-232 or plus navitoclax. A correlation analysis of treatment responses and genomic and proteomic biomarkers revealed that sensitivity to KRT-232 was significantly associated with TP53 wild-type or STK11 mutant genotypes (P<0.05). The levels of several proteins, including GSK3b, Nrf2, LKB1/pS334, and SMYD3, were significantly associated with sensitivity to trametinib plus navitoclax. Thus, the combination of trametinib plus KRT-232 or navitoclax resulted in improved efficacy compared with the agents alone in a subgroup of NSCLC PDX model with KRAS mutations. Expanded clinical trials of these targeted drug combinations in NSCLC are warranted.

Estimation of high-dimensional directed acyclic graphs with surrogate intervention

Directed acyclic graphs (DAGs) have been used to describe causal relationships between variables. The standard method for determining such relations uses interventional data. For complex systems with high-dimensional data, however, such interventional data are often not available. Therefore, it is desirable to estimate causal structure from observational data without subjecting variables to interventions. Observational data can be used to estimate the skeleton of a DAG and the directions of a limited number of edges. We develop a Bayesian framework to estimate a DAG using surrogate interventional data, where the interventions are applied to a set of external variables, and thus such interventions are considered to be surrogate interventions on the variables of interest. Our work is motivated by expression quantitative trait locus (eQTL) studies, where the variables of interest are the expression of genes, the external variables are DNA variations, and interventions are applied to DNA variants during the process of a randomly selected DNA allele being passed to a child from either parent. Our method, surrogate intervention recovery of a DAG ($\texttt{sirDAG}$), first constructs a DAG skeleton using penalized regressions and the subsequent partial correlation tests, and then estimates the posterior probabilities of all the edge directions after incorporating DNA variant data. We demonstrate the utilities of $\texttt{sirDAG}$ by simulation and an application to an eQTL study for 550 breast cancer patients.

Abstract 4454: TUSC2 immunogene therapy enhances efficacy of immunotherapy and targeted drugs in human non-small cell lung cancer (NSCLC) in humanized mouse models

TUSC2 is a tumor suppressor gene, whose expression is reduced in almost all NSCLC. Systemic nanovesicle delivery of TUSC2 inhibits cancer cell growth through inhibition of a broad spectrum of kinases and mTOR downregulation as well as stimulation of the immune system through innate activation. We previously reported that TUSC2 downregulates PD-L1 expression in NSCLC and synergizes with anti-PD1 in inhibiting tumor growth in Kras mutant syngeneic mouse models through upregulation of NK and cytotoxic T cells. We developed an improved CD34-derived humanized mouse model (Hu-mice), with faster and higher human immune reconstitution than other available humanized mice, to evaluate immune responses in lung cancer. In this study, we tested whether TUSC2 immunogene therapy would enhance response to standard checkpoint blockade immunotherapy, chemotherapy and targeted therapies in humanized NSG mice implanted with highly metastatic Krasmt/LKB1− A549 cells. A significantly increased antitumor effect was found when TUSC2 was combined with pembrolizumab. Pembrolizumab alone reduced tumor burden as compared with an untreated control, whereas no antitumor effect was observed in non-Hu-mice implanted with A549 cells. The observed antitumor effect correlated with increased levels of CD8+ T and CD8+CD69+ active T, and decreased levels of MDSC and regulatory T cells in the combination group. A significantly higher percentages of CD56+ NK and CD56+CD69+ active NK cells were found in the TUSC2 alone and combination groups indicating TUSC2 related NK activation. Next, we tested whether TUSC2 enhances efficacy to carboplatin+pembrolizumab. The level of antitumor effect of carboplatin+pembrolizumab was similar to that of TUSC2 alone. However, when TUSC2 was combined with carboplatin+pembrolizumab, metastases regression was significantly greater than either TUSC2 alone or carboplatin+pembrolizumab treatments. Significantly fewer or no visible tumor nodules were found in dissected lungs in the TUSC2 combination as compared with other groups. Immune analysis of the triple combination in CMT167 syngeneic mice showed increased infiltration of CD3+ T, CD8+ T, NK cells and significantly less Treg cells into tumor, which was associated with significant tumor inhibition by the treatments. A higher percentage of CD3+CD44+ and CD8+CD44+ memory T cells were found in tumors after carbo+aPD1+TUSC2 treatment, as compared with either Carbo+aPD1 or control groups. The antitumor activity of Carbo+aPD1+TUSC2 was further enhanced when MEKi (Trametinib) was added. Moreover, we also combined TUSC2 with the anti-angiogenic agent, bevacizumab (anti-VEGF) to enhance efficacy in the highly angiogenic 786-O renal cell carcinoma. Synergistic antitumor activity was found with the combination, which was significantly stronger than either single agent. In conclusion, the addition of TUSC2 immunogene therapy with checkpoint blockade, chemotherapy, and targeted therapies showed enhanced antitumor efficacy.

Citation Format: Ismail M. Meraz, Mourad Majidi, Meng Feng, RuPing Shao, Min Jin Ha, Elizabeth J. Shpall, Jack A. Roth. TUSC2 immunogene therapy enhances efficacy of immunotherapy and targeted drugs in human non-small cell lung cancer (NSCLC) in humanized mouse models [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4454.

Abstract 557: Novel targeted combination therapies active in KRAS mutant non-small cell lung cancer (NSCLC) identified using patient-derived xenografts (PDX)

PDXs recapitulate histologic features, gene expression patterns, and genomic alterations in human primary tumors, and thus have emerged as robust preclinical models for drug development, molecular characterization of cancers, identification of biomarkers, and strategic development of precision therapy. We tested multiple combinations of small molecule targeted drugs selected on the basis of known NSCLC vulnerabilities for efficacy in NSCLC PDXs with known genotypes. We determined in vivo treatment responses to single agent and combination therapies for pathway targeted therapeutic agents, including the MEK inhibitor trametinib, the MDM2 inhibitor KRT-232, the BCL2/BCL-XL inhibitor navitoclax, and their combinations in 8-23 molecularly annotated NSCLC PDX models. Mice (n=3-5/group) were enrolled into treatment individually when tumors reached 200 mm3 in size, and were treated 5 days/week for 3 weeks. Tumor growth was monitored 2-3 times/week. We used the following criteria to determine treatment responses: 1) Tumor Regression (or partial response): tumor regression ≥ -30% based on tumor volume changes calculated by AUC0-21day or at day 21 after treatment start when compared with baseline (beginning of treatment at day 0); 2) Tumor Growth Inhibition (or stable disease): Tumor growth was significantly suppressed when compared with control (P &lt; 0.05), but no tumor regression was observed, or tumor regression was less than -30% based on tumor volume changes calculated by AUC0-21day or at day 21 after treatment start when compared with baseline; 3) Resistance: Tumor volume changes calculated by AUC0-21day was not significantly different from control group (P&gt;0.05). Our results showed that KRT-232 alone resulted in 15.8% (3/19) tumor regression and 26.3% (5/19) tumor growth inhibition, all in TP53 wild type PDXs. Trametinib alone induced 10% (2/20) tumor regression and 50% (10/20) growth inhibition, respectively. 80% (8/10) of KRAS mutant PDXs responded to trametinib treatment with tumor regression (1/10) or growth inhibition (7/10). Combination therapies of trametinib plus KRT-232 and trametinib plus navitoclax led to improved in vivo anticancer activity over single agent activity in a subset PDX models with KRAS mutations. Tumor regression was observed in 26% (6/23) and 50% (5/10) of trametinib plus KRT-232 and trametinib plus navitoclax treatment groups, respectively. Navitoclax alone did not induce tumor regression in 8 PDX models tested, and navitoclax plus KRT-232 did not lead to significant improvement in activity over single agents in 11 PDXs. Our results show that combination therapies of trametinib plus KRT-232 or navitoclax result in improved efficacy in a subgroup of NSCLC PDX models with KRAS mutations. Clinical trials with these targeted drug combinations in NSCLC are warranted.

Citation Format: Xiaoshan Zhang, Ran Zhang, Huiqin Chen, Li Wang, Chenghui Ren, Shuhong Wu, Min Jin Ha, Jeffrey Morris, Yuanxin Xi, Jing Wang, Don L. Gibbons, John V. Heymach, Funda Meric-Bernstam, John Minna, Stephen G. Swisher, Jack A. Roth, Bingliang Fang. Novel targeted combination therapies active in KRAS mutant non-small cell lung cancer (NSCLC) identified using patient-derived xenografts (PDX) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 557.

Intravenous Immunoglobulin G Suppresses Heat Shock Protein (HSP)-70 Expression and Enhances the Activity of HSP90 and Proteasome Inhibitors

Intravenous immunoglobulin G (IVIgG) is approved for primary immunodeficiency syndromes but may induce anti-cancer effects, and while this has been attributed to its anti-inflammatory properties, IgG against specific tumor targets may play a role. We evaluated IVIgG alone, and with a Heat shock protein (HSP)-90 or proteasome inhibitor, using multiple myeloma and mantle cell lymphoma (MCL) cells in vitro, and with the proteasome inhibitor bortezomib in vivo. IVIgG inhibited the growth of all cell lines tested, induced G₁ cell cycle arrest, and suppressed pro-tumor cytokines including Interleukin (IL)-6, IL-8, and IL-10. Genomic and proteomic studies showed that IVIgG reduced tumor cell HSP70-1 levels by suppressing the ability of extracellular HSP70-1 to stimulate endogenous HSP70-1 promoter activity, and reduced extracellular vesicle uptake. Preparations of IVIgG were found to contain high titers of anti-HSP70-1 IgG, and recombinant HSP70-1 reduced the efficacy of IVIgG to suppress HSP70-1 levels. Combining IVIgG with the HSP90 inhibitor AUY922 produced superior cell growth inhibition and correlated with HSP70-1 suppression. Also, IVIgG with bortezomib or carfilzomib was superior to each single agent, and enhanced bortezomib's activity in bortezomib-resistant myeloma cells. Moreover, IVIgG reduced transfer of extracellular vesicles (EVs) to cells, and blocked transfer of bortezomib resistance through EVs. Finally, IVIgG with bortezomib were superior to the single agents in an in vivo myeloma model. These studies support the possibility that anti-HSP70-1 IgG contained in IVIgG can inhibit myeloma and MCL growth by interfering with a novel mechanism involving uptake of exogenous HSP70-1 which then induces its own promoter.

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome

PURPOSE

Personalized network inference on diverse clinical and in vitro model systems across cancer types can be used to delineate specific regulatory mechanisms, uncover drug targets and pathways, and develop individualized predictive models in cancer.

METHODS

We developed TransPRECISE (personalized cancer-specific integrated network estimation model), a multiscale Bayesian network modeling framework, to analyze the pan-cancer patient and cell line interactome to identify differential and conserved intrapathway activities, to globally assess cell lines as representative models for patients, and to develop drug sensitivity prediction models. We assessed pan-cancer pathway activities for a large cohort of patient samples (> 7,700) from the Cancer Proteome Atlas across ≥ 30 tumor types, a set of 640 cancer cell lines from the MD Anderson Cell Lines Project spanning 16 lineages, and ≥ 250 cell lines' response to > 400 drugs.

RESULTS

TransPRECISE captured differential and conserved proteomic network topologies and pathway circuitry between multiple patient and cell line lineages: ovarian and kidney cancers shared high levels of connectivity in the hormone receptor and receptor tyrosine kinase pathways, respectively, between the two model systems. Our tumor stratification approach found distinct clinical subtypes of the patients represented by different sets of cell lines: patients with head and neck tumors were classified into two different subtypes that are represented by head and neck and esophagus cell lines and had different prognostic patterns (456 v 654 days of median overall survival; P = .02). High predictive accuracy was observed for drug sensitivities in cell lines across multiple drugs (median area under the receiver operating characteristic curve > 0.8) using Bayesian additive regression tree models with TransPRECISE pathway scores.

CONCLUSION

Our study provides a generalizable analytic framework to assess the translational potential of preclinical model systems and to guide pathway-based personalized medical decision making, integrating genomic and molecular data across model systems.

Hepatic resection for breast cancer liver metastases: Impact of intrinsic subtypes

INTRODUCTION

The role of surgery for breast cancer liver metastases (BCLM) remains controversial. This study aimed to analyze survival in patients treated with hepatectomy plus systemic therapy or systemic therapy alone for BCLM and to determine selection factors to guide surgical therapy.

MATERIALS AND METHODS

Patients who underwent hepatectomy plus systemic therapy (n = 136) and systemic therapy alone for isolated BCLM (n = 763) were compared. Overall survival (OS) was analyzed after propensity score matching. Intrinsic subtypes were defined as: luminal A (estrogen receptor [ER]+ and/or progesterone receptor positive [PR]+, human epidermal growth factor receptor 2 [HER2]-), luminal B (ER and/or PR+, HER2+), HER2-enriched (ER and PR-, HER2+), and basal-like (ER, PR, HER2-).

RESULTS

After hepatectomy, independent predictors of poor OS were number and size of liver metastases, and intrinsic subtype (hazard ratios, 1.11, 1.16, and 4.28, respectively). Median OS was 75 and 81 months among patients with luminal B and HER2-enriched subtypes, compared with 17 and 53 months among patients with basal-like and luminal A subtypes (P < .001). Median progression-free survival (PFS) was 60 months with the HER2-enriched subtype, compared with 17, 16, and 5 months with luminal A, luminal B, and basal-like subtypes, respectively (P < .001). After propensity score matching, 5-year OS rates were 56% vs. 40% in the surgery vs. systemic therapy alone groups (P = .018).

CONCLUSION

Surgical resection of BCLM yielded higher OS compared with systemic therapy alone and prolonged PFS among patients with the HER2-enriched subtype. These findings support the use of surgical therapy in appropriately selected patients, based on intrinsic subtypes.

Abstract A75: Efficacy of novel immunogene combinations for Kras and LKB1 mutant NSCLC in a humanized mouse model

Due to lack of suitability of current preclinical models for immunotherapy research, we recently developed an improved humanized mouse by reconstituting a human immune system in NSG mice by transplanting fresh human cord blood-derived CD34+ stem cells (Hu-mice). The Hu-mice show functional representation of human T, B, natural killer (NK), dendritic cells (DC), myeloid-derived suppressor cells (MDSC), and responsiveness to checkpoint blockade. TUSC2 has recently been recognized as a novel immunogene that induces apoptosis in tumor cells and promotes a wide spectrum of tumor-specific innate and adaptive immune responses. We previously reported that TUSC2 delivered systemically by nanovesicles downregulates PD-L1 expression in NSCLC and synergizes with anti-PD1 in inhibiting tumor growth in Kras-mutant syngeneic mouse models through upregulating NK and cytotoxic T cells. In this study, we aimed to evaluate the antitumor efficacy of TUSC2 in combination with standard immunotherapy on highly metastatic Kras and LKB1 mutant human lung cancer in Hu-mice. Hu-mice were challenged with A549 cells (Krasmt/LKB1-) and lung metastases were treated with TUSC2, nivolumab, or the combination. The results showed a synergistic antitumor effect with the combination. A significantly increased antitumor effect was found when TUSC2 was combined with pembrolizumab in Hu-mice. Pembrolizumab alone significantly reduced tumor burden as compared with an untreated control, whereas no antitumor effect was observed in non-Hu-mice implanted with A549 cells. The antitumor effect was correlated with significantly higher levels of CD8+ T and CD8+CD69+ active T and significantly lower levels of MDSC and regulatory T cells in the combination group. A significantly higher percentage of CD56+ NK and CD56+CD59+ active NK cells was found in the TUSC2 alone and combination groups, indicating TUSC2 related NK activation. We tested whether TUSC2 enhances efficacy to carboplatin+pembrolizumab in Hu-mice implanted with A549-luc metastatic cells. The results showed that the level of antitumor effect of carboplatin+pembrolizumab was similar to that of TUSC2 alone, but when TUSC2 was combined with carboplatin+pembrolizumab, metastases regression was significantly greater than either TUSC2 alone or carboplatin+pembrolizumab treatments. Significantly fewer or no visible tumor nodules were found in dissected lungs in the TUSC2 combination as compared with other groups. In conclusion, TUSC2 immunogene therapy in combination with pembrolizumab and carboplatin+pembrolizumab showed strong antitumor efficacy in metastatic human NSCLC in a clinically relevant humanized mouse model, supporting a clinical trial.

Citation Format: Ismail M. Meraz, Mourad Majidi, Meng Feng, RuPing Shao, Min Jin Ha, Jeffrey Morris, Elizabeth J. Shpall, Jack A. Roth. Efficacy of novel immunogene combinations for Kras and LKB1 mutant NSCLC in a humanized mouse model [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr A75.

Abstract P6-04-12: STAT3 as a therapeutic target in estrogen receptor positive breast cancer patients refractory to CDK4/6 inhibition

Background: CDK4/6 inhibitors (i.e. palbociclib) in combination with endocrine therapy (ET) are currently standard of care for estrogen receptor (ER) positive breast cancer patients with advanced/metastatic disease. While this combination has proven successful in delaying progression, no improvement in long-term survival has been observed to date in the post-menopausal setting. Further, resistance is inevitable as 50-60% of patients’ metastatic lesions progress on CDK4/6 inhibitor therapy within 2-years of treatment. For patients experiencing resistance to CDK4/6 inhibitors, novel treatment strategies are needed to delay progression or to improve survival. Our recently published data shows that palbociclib-resistance is marked by significant upregulation of the IL6- STAT3 signaling pathway in ER-positive breast cancer cells. Knockdown of STAT3 in resistance cancer cells restored sensitivity to palbociclib. Additionally, matched biopsies from advanced ER-positive breast cancer patients who progressed on palbociclib showed upregulation in p-STAT3 as compared to their pre-treatment biopsy samples (14 out of 25 patients; p=0.042). Collectively, these data suggest that STAT3 is viable therapeutic target to overcome palbociclib resistance. Hence, the goal of this study is to translate these findings in vivo and provide pre-clinical rational to the efficacy of TTI-101 (an orally bioavailable STAT3 inhibitor) in PDX models of palbociclib resistance.

Methods: To identify PDX models that recapitulate palbociclib resistance observed in cell line models, we correlated two published RNA-seq data sets of a panel of 64 PDX models from breast cancer patients to our multi-omics analysis of palbociclib resistant cell lines. Four PDXs that recapitulated the resistant-transcriptome expression pattern based on Spearman’s correlation, were narrowed down for future studies. In addition, we have also established PDX models (1st-4th passage) from two sets of patients (1) those who are intrinsically resistant to palbociclib (the patients progressed at 2-3 months while on palbociclib + ET) and (2) those who have developed resistance over time (i.e. acquired resistance-patients progress at 12-18 months while on palbociclib + ET).

Results: We chose PDX model BCX94 for our preliminary studies as it showed baseline induction of p-STAT3 by immunoblot analysis. Using BCX94, we show that TTI-101 at 50mg/kg twice a day potently reduced tumor volume and improved survival of these mice. We also observed a significant reduction in tumor-derived IL-6 in circulation; as assayed by hIL-6 levels in the serum. Further, complete blood count analysis of whole blood collected at endpoint (i.e. 28 days on treatment) showed no drug toxicities. Treatment of intrinsic palbociclib resistant PDX models with TTI-101, on the other hand, showed only a brief delay in tumor progression, but no overall benefit. Conclusions: Collectively, these results indicate that TT1-101 is safely tolerated and efficacious at the dose examined in PDX models and that TTI-101 may be a suitable target for those tumors that are resistant to palbociclib. The differences in response to TTI-101 in the BCX94 versus our intrinsic PDX models, suggest that acquired vs. intrinsic resistance signatures of palbociclib may be mutually exclusive and that the IL-6-STAT3 signaling axis may be a driver in acquired palbociclib resistance, but not the intrinsic setting. Our ongoing studies are therefore geared towards testing the efficacy of IL-6-STAT3 inhibition in both settings (i.e. acquired and intrinsic) and identifying distinct therapeutic vulnerabilities of intrinsic palbociclib resistance that may be unresponsive to STAT3 inhibition.

Citation Format: Nicole M Kettner, Tuyen Bui, Min Jin Ha, T Kris Eckols, David J Tweardy, Funda Meric-Bernstam, Kelly K Hunt, Debu Tripathy, Khandan Keyomarsi. STAT3 as a therapeutic target in estrogen receptor positive breast cancer patients refractory to CDK4/6 inhibition [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-04-12.

Network-Based Matching of Patients and Targeted Therapies for Precision Oncology

The extensive acquisition of high-throughput molecular profiling data across model systems (human tumors and cancer cell lines) and drug sensitivity data, makes precision oncology possible - allowing clinicians to match the right drug to the right patient. Current supervised models for drug sensitivity prediction, often use cell lines as exemplars of patient tumors and for model training. However, these models are limited in their ability to accurately predict drug sensitivity of individual cancer patients to a large set of drugs, given the paucity of patient drug sensitivity data used for testing and high variability across different drugs. To address these challenges, we developed a multilayer network-based approach to impute individual patients' responses to a large set of drugs. This approach considers the triplet of patients, cell lines and drugs as one inter-connected holistic system. We first use the omics profiles to construct a patient-cell line network and determine best matching cell lines for patient tumors based on robust measures of network similarity. Subsequently, these results are used to impute the "missing link" between each individual patient and each drug, called Personalized Imputed Drug Sensitivity Score (PIDS-Score), which can be construed as a measure of the therapeutic potential of a drug or therapy. We applied our method to two subtypes of lung cancer patients, matched these patients with cancer cell lines derived from 19 tissue types based on their functional proteomics profiles, and computed their PIDS-Scores to 251 drugs and experimental compounds. We identified the best representative cell lines that conserve lung cancer biology and molecular targets. The PIDS-Score based top sensitive drugs for the entire patient cohort as well as individual patients are highly related to lung cancer in terms of their targets, and their PIDS-Scores are significantly associated with patient clinical outcomes. These findings provide evidence that our method is useful to narrow the scope of possible effective patient-drug matchings for implementing evidence-based personalized medicine strategies.

An Improved Patient-Derived Xenograft Humanized Mouse Model for Evaluation of Lung Cancer Immune Responses

Human tumor xenograft models do not replicate the human immune system and tumor microenvironment. We developed an improved humanized mouse model, derived from fresh cord blood CD34+ stem cells (CD34+ HSC), and combined it with lung cancer cell line-derived human xenografts or patient-derived xenografts (Hu-PDX). Fresh CD34+ HSCs could reconstitute detectable mature human leukocytes (hCD45+) in mice at four weeks without the onset of graft-versus-host disease (GVHD). Repopulated human T cells, B cells, natural killer (NK) cells, dendritic cells (DC), and myeloid-derived suppressor cells (MDSC) increased in peripheral blood, spleen, and bone marrow over time. Although cultured CD34+ HSCs labeled with luciferase could be detected in mice, the cultured HSCs did not develop into mature human immune cells by four weeks, unlike fresh CD34+ HSCs. Ex vivo, reconstituted T cells, obtained from the tumor-bearing humanized mice, secreted IFNγ upon treatment with phorbol myristate acetate (PMA) or exposure to human A549 lung tumor cells and mediated antigen-specific CTL responses, indicating functional activity. Growth of engrafted PDXs and tumor xenografts was not dependent on the human leukocyte antigen status of the donor. Treatment with the anti-PD-1 checkpoint inhibitors pembrolizumab or nivolumab inhibited tumor growth in humanized mice significantly, and correlated with an increased number of CTLs and decreased MDSCs, regardless of the donor HLA type. In conclusion, fresh CD34+HSCs are more effective than their expanded counterparts in humanizing mice, and do so in a shorter time. The Hu-PDX model provides an improved platform for evaluation of immunotherapy.

Abstract 4984: Development of an improved humanized patient-derived xenograft, Hu-PDX, mouse model for evaluation of antitumor immune response in lung cancer

Current preclinical models of non-small cell lung cancer (NSCLC) do not recapitulate the human tumor microenvironment. Mice reconstituted with a human immune system and bearing human patient derived xenografts may be advantageous in evaluating human anti-tumor immune response. We developed an improved NOD scid gamma (NSG) mouse model derived from non-expanded CD34+ stem cells, without CD3+ T cell contamination, to evaluate antitumor responses to immunotherapy in NSCLC. Using fresh CD34+ from umbilical cord blood reduced humanization time significantly. Human CD45+ cell reconstitution with increased functional human lymphoid (B, T, monocytes and NK cells) and myeloid (macrophages and MDSCs) lineage repopulation, without the onset of GvHD, was achieved as early as 4 weeks post-stem cell engraftment. Published studies using expanded CD34+ derived humanization reveal compromised purity of CD34+ stem cells with an increasing number of mononuclear cells. Reconstitution of CD8+ and CD4+T cells is not achieved until 12 to 15 weeks post-engraftment at much lower levels than fresh CD34+ humanization. Single cell suspension analysis shows levels of human reconstituted T, B, NK, DC and MDSC cells at 4 weeks, which increased significantly at 6 and 9 weeks in peripheral blood, spleen and bone marrow. Human repopulated T cells were functionally active in secretion of IFN-γ by mitogenic stimuli such as PMA and IL-2 and by allogenic human cancer cells. Antigen specific CTL responses were observed when reconstituted human T cells from PDX bearing humanized mice were challenged with PDX tumor. No non-antigen specific responses were observed when T cells were co-cultured with HLA-matched human bronchial epithelial cells (HBEC). To evaluate the applicability of the humanized mouse in lung cancer translational research, we combined it with Hu-PDX or Hu-xenograft tumors and analyzed tumor growth and treatment response to the anti-PD1 checkpoint inhibitor pembrolizumab. We found that efficient engraftment of PDXs and xenograft tumors were not dependent on donor HLA-status. Similar to the clinical outcome, treatment with pembrolizumab, inhibited tumor growth significantly in both Hu-PDX, and Hu-xenograft mice regardless of donor HLA-types, increasing cytotoxic T cells and decreasing MDSC levels. Pembrolizumab had no effect on the non-humanized NSG controls. In concordance with our previous study with a syngeneic mouse tumor, the antitumor effect of check point blockade was significantly enhanced when combined with nanoparticle systemically deliveredTUSC2, a tumor suppressor and immunomodulatory gene, in a KRAS mutant lung metastasis humanized mouse model. In conclusion, fresh CD34+ are more effective than their expanded counterparts in humanizing mice, do so in much reduced time, and recapitulate the immune response to cancer.

Citation Format: Ismail M. Meraz, Mourad Majidi, Feng Meng, RuPing Shao, Min Jin Ha, Shinya Neri, Bingliang Fang, Steven H. Lin, Peggy T. Tinkey, Elizabeth J. Shpall, Jeffrey Morris, Jack A. Roth. Development of an improved humanized patient-derived xenograft, Hu-PDX, mouse model for evaluation of antitumor immune response in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4984.

Abstract 323: Combined inhibition of STAT-3 & DNA repair in palbociclib resistant breast cancer

The CDK4/6 inhibitor palbociclib is currently being used in combination with endocrine therapy to treat advanced ER positive breast cancer patients. While this treatment has shown great promise in the clinic, about 25-35% of the patients do not respond initially, and almost all patients eventually acquire resistance. Hence, understanding the mechanisms of acquired resistance to CDK4/6 inhibition is crucial to devise alternate treatment strategies.

To identify mechanisms of resistance to CDK4/6 inhibition we developed MCF-7 and T47D palbociclib resistant cells in a step-wise manner by gradually increasing concentrations of palbociclib. These cells are not only resistant to palbociclib, but exhibited resistance to the other approved CDK4/6 inhibitors; ribociclib and abemaciclib. Additionally, we assessed if these resistant cells have an altered response to endocrine therapy and observed that these cells are also resistant to treatment with tamoxifen or fulvestrant by about 16-fold. Multi-omics analyses revealed enrichment of pathways known to regulate EMT and promote stem-like properties, as well as, downregulation of estrogen response and DNA repair pathways.

Palbociclib resistant cells exhibited mammosphere formation and CD44high/CD24low population indicating the presence of increased breast cancer stem cell-like cells (B-CSC-L). Given the recently elucidated role of IL-6/STAT-3 mediated B-CSC-L phenotypes in drug resistance, we examined IL-6 mRNA levels, which increased by &gt;12-fold in the resistant cells. Treatment with STAT-3 inhibitors, napabucasin and C188-9, significantly decreased the B-CSC-L population and mammosphere formation, indicating a crucial role for the IL-6/STAT-3 pathway in driving B-CSC-L phenotype and palbociclib resistance.

Since DNA repair pathways were collectively downregulated in the palbociclib resistant cells, we examined their sensitivity to DNA damaging agents. Results showed that resistant cells were more sensitive to olaparib (PARP inhibition), with no effect on B-CSC-L population. Next, we examined if combined treatment with agents targeting STAT-3 and PARP would be synergistic in palbociclib resistant cells. Results show that combined treatment with olaparib and napabucasin or C-1889 significantly decreased B-CSC-L population, colony formation and increased cell death via apoptosis, when compared to no-treatment or single treatment controls of the palbociclib resistant cells.

Lastly, we interrogated matched tumor samples from breast cancer patients who progressed on palbociclib for deregulation of estrogen receptor, DNA repair, and IL-6/STAT3 signaling and found that these pathways are altered as compared to the pre-treatment samples.

Taken together, the results show that targeting IL-6/STAT-3 mediated cancer stem cells and DNA repair deficiency by PARP inhibitors in combination can effectively treat acquired resistance to palbociclib.

Citation Format: Nicole M. Kettner, Smruthi Vijayaraghavan, Merih Guray Durak, Tuyen Bui, Mehrnoosh Kohansal, Min Jin Ha, Bin Liu, Xiayu Rao, Jing Yang, Min Yi, Jason P. Carey, Xian Chen, T. Kris Eckols, Akshara S. Raghavendra, Nuhad K. Ibrahim, Meghan Karuturi, Stephanie S. Watowich, Aysegul A. Sahin, David J. Tweardy, Kelly K. Hunt, Debu Tripathy, Khandan Keyomarsi. Combined inhibition of STAT-3 & DNA repair in palbociclib resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 323.

Combined Inhibition of STAT3 and DNA Repair in Palbociclib-Resistant ER-Positive Breast Cancer

PURPOSE

Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors are currently used in combination with endocrine therapy to treat advanced hormone receptor-positive, HER2-negative breast cancer. Although this treatment doubles time to progression compared with endocrine therapy alone, about 25%-35% of patients do not respond, and almost all patients eventually acquire resistance. Discerning the mechanisms of resistance to CDK4/6 inhibition is crucial in devising alternative treatment strategies.

EXPERIMENTAL DESIGN

Palbociclib-resistant cells (MCF-7 and T47D) were generated in a step-wise dose-escalading fashion. Whole-exome sequencing, genome-wide expression analysis, and proteomic analysis were performed in both resistant and parental (sensitive) cells. Pathway alteration was assessed mechanistically and pharmacologically. Biomarkers of altered pathways were examined in tumor samples from patients with palbociclib-treated breast cancer whose disease progressed while on treatment.

RESULTS

Palbociclib-resistant cells are cross-resistant to other CDK4/6 inhibitors and are also resistant to endocrine therapy (estrogen receptor downregulation). IL6/STAT3 pathway is induced, whereas DNA repair and estrogen receptor pathways are downregulated in the resistant cells. Combined inhibition of STAT3 and PARP significantly increased cell death in the resistant cells. Matched tumor samples from patients with breast cancer who progressed on palbociclib were examined for deregulation of estrogen receptor, DNA repair, and IL6/STAT3 signaling, and results revealed that these pathways are all altered as compared with the pretreatment tumor samples.

CONCLUSIONS

Palbociclib resistance induces endocrine resistance, estrogen receptor downregulation, and alteration of IL6/STAT3 and DNA damage response pathways in cell lines and patient samples. Targeting IL6/STAT3 activity and DNA repair deficiency using a specific STAT3 inhibitor combined with a PARP inhibitor could effectively treat acquired resistance to palbociclib.

iDINGO-integrative differential network analysis in genomics with Shiny application

Motivation

Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple ‘omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple ‘omics data independently does not account for the hierarchical structure of the data.

Results

We developed the iDINGO R package to estimate group-specific dependencies and make inferences on the integrative differential networks, considering the biological hierarchy among the platforms. A Shiny application has also been developed to facilitate easier analysis and visualization of results, including integrative differential networks and hub gene identification across platforms.

Availability and implementation

R package is available on CRAN (https://cran.r-project.org/web/packages/iDINGO) and Shiny application at https://github.com/MinJinHa/iDINGO.

Supplementary information

Supplementary data are available at Bioinformatics online.

Personalized Integrated Network Modeling of the Cancer Proteome Atlas

Personalized (patient-specific) approaches have recently emerged with a precision medicine paradigm that acknowledges the fact that molecular pathway structures and activity might be considerably different within and across tumors. The functional cancer genome and proteome provide rich sources of information to identify patient-specific variations in signaling pathways and activities within and across tumors; however, current analytic methods lack the ability to exploit the diverse and multi-layered architecture of these complex biological networks. We assessed pan-cancer pathway activities for >7700 patients across 32 tumor types from The Cancer Proteome Atlas by developing a personalized cancer-specific integrated network estimation (PRECISE) model. PRECISE is a general Bayesian framework for integrating existing interaction databases, data-driven de novo causal structures, and upstream molecular profiling data to estimate cancer-specific integrated networks, infer patient-specific networks and elicit interpretable pathway-level signatures. PRECISE-based pathway signatures, can delineate pan-cancer commonalities and differences in proteomic network biology within and across tumors, demonstrates robust tumor stratification that is both biologically and clinically informative and superior prognostic power compared to existing approaches. Towards establishing the translational relevance of the functional proteome in research and clinical settings, we provide an online, publicly available, comprehensive database and visualization repository of our findings ( https://mjha.shinyapps.io/PRECISE/ ).

Bayesian Hierarchical Varying-sparsity Regression Models with Application to Cancer Proteogenomics

Identifying patient-specific prognostic biomarkers is of critical importance in developing personalized treatment for clinically and molecularly heterogeneous diseases such as cancer. In this article, we propose a novel regression framework, Bayesian hierarchical varying-sparsity regression (BEHAVIOR) models to select clinically relevant disease markers by integrating proteogenomic (proteomic+genomic) and clinical data. Our methods allow flexible modeling of protein-gene relationships as well as induces sparsity in both protein-gene and protein-survival relationships, to select ge-nomically driven prognostic protein markers at the patient-level. Simulation studies demonstrate the superior performance of BEHAVIOR against competing method in terms of both protein marker selection and survival prediction. We apply BEHAV-IOR to The Cancer Genome Atlas (TCGA) proteogenomic pan-cancer data and find several interesting prognostic proteins and pathways that are shared across multiple cancers and some that exclusively pertain to specific cancers.

Bayesian inference of hub nodes across multiple networks

Hub nodes within biological networks play a pivotal role in determining phenotypes and disease outcomes. In the multiple network setting, we are interested in understanding network similarities and differences across different experimental conditions or subtypes of disease. The majority of proposed approaches for joint modeling of multiple networks focus on the sharing of edges across graphs. Rather than assuming the network similarities are driven by individual edges, we instead focus on the presence of common hub nodes, which are more likely to be preserved across settings. Specifically, we formulate a Bayesian approach to the problem of multiple network inference which allows direct inference on shared and differential hub nodes. The proposed method not only allows a more intuitive interpretation of the resulting networks and clearer guidance on potential targets for treatment, but also improves power for identifying the edges of highly connected nodes. Through simulations, we demonstrate the utility of our method and compare its performance to current popular methods that do not borrow information regarding hub nodes across networks. We illustrate the applicability of our method to inference of co-expression networks from The Cancer Genome Atlas ovarian carcinoma dataset.

Cytoplasmic Cyclin E Predicts Recurrence in Patients with Breast Cancer

Purpose: Low molecular weight cyclin E (LMW-E) detected by Western blot analysis predicts for reduced breast cancer survival; however, it is impractical for clinical use. LMW-E lacks a nuclear localization signal that leads to accumulation in the cytoplasm that can be detected by IHC. We tested the hypothesis that cytoplasmic staining of cyclin E can be used as a predictor of poor outcome in different subtypes of breast cancer using patient cohorts with distinct clinical and pathologic features.Experimental Design: We evaluated the subcellular localization of cyclin E in breast cancer specimens from 2,494 patients from 4 different cohorts: 303 from a prospective study and 2,191 from retrospective cohorts [NCI, MD Anderson Cancer Center (MDA), and the United Kingdom (UK)]. Median follow-up times were 8.0, 10.1, 13.5, and 5.7 years, respectively.Results: Subcellular localization of cyclin E on IHC was associated with full-length (nuclear) and low molecular weight isoforms (cytoplasmic) of cyclin E on Western blot analysis. In multivariable analysis, cytoplasmic cyclin E staining was associated with the greatest risk of recurrence compared with other prognostic factors across all subtypes in three (NCI, MDA, and UK) of the cohorts. In the MDA cohort, cytoplasmic cyclin E staining outperformed Ki67 and all other variables as prognostic factors.Conclusions: Cytoplasmic cyclin E identifies patients with the highest likelihood of recurrence consistently across different patient cohorts and subtypes. These patients may benefit from alternative therapies targeting the oncogenic isoforms of cyclin E. Clin Cancer Res; 23(12); 2991-3002. ©2016 AACR.

Beneficial effects of voglibose administration on body weight and lipid metabolism via gastrointestinal bile acid modification

This study was designed with the goal of examining the effects of voglibose administration on body weight and lipid metabolism and underlying mechanism high fat diet-induced obese mice. Male C57BL/6 mice were randomly assigned to one of four groups: a control diet (CTL), high-fat diet (HF), high-fat diet supplemented with voglibose (VO), and high fat diet pair-fed group (PF). After 12 weeks, the following characteristics were investigated: serum lipid and glucose levels, serum polar metabolite profiles, and expression levels of genes involved in lipid and bile acid metabolism. In addition, pyrosequencing was used to analyze the composition of gut microbiota found in feces. Total body weight gain was significantly lower in the VO group than in the CTL, HF, and PF groups. The VO group exhibited improved metabolic profiles including those of blood glucose, triglyceride, and total cholesterol levels. The 12-week voglibose administration decreased the ratio of Firmicutes to Bacteroidetes found in feces. Circulating levels of taurocholic and cholic acid were significantly higher in the VO group than in the HF and CTL groups. Deoxycholic acid levels tended to be higher in the VO group than in the HF group. Voglibose administration downregulated expression levels of CYP8B1 and HNF4α genes and upregulated those of PGC1α, whereas FXRα was not affected. Voglibose administration elicits changes in the composition of the intestinal microbiota and circulating metabolites, which ultimately has systemic effects on body weight and lipid metabolism in mice.

Idelalisib Impacts Cell Growth through Inhibiting Translation-Regulatory Mechanisms in Mantle Cell Lymphoma

PURPOSE

PI3K is a critical node in the B-cell receptor pathway, which is responsible for survival and proliferation of B-cell malignancies. Idelalisib, a PI3Kδ-isoform-specific inhibitor, has been approved to treat B-cell malignancies. Although biological activity of the drug has been evaluated, molecular mechanisms and signaling pathway disruption leading to the biological effects of idelalisib are not yet well defined. Prior laboratory reports have identified transcription and translation as the primary events for attenuation of PI3Kα isoform. We hypothesized that PI3Kδ-isoform inhibition by idelalisib should also affect gene transcription and protein translation.

EXPERIMENTAL DESIGN

Using three mantle cell lymphoma cell lines and primary cells from patients, biological consequences such as apoptosis/cell-cycle analysis, as well as RNA/protein synthesis were evaluated. Proteomics analyses (RPPA and immunoblot assays) defined molecular events downstream of PI3K/AKT cassette.

RESULTS

Idelalisib treatment resulted in inhibition of protein synthesis, which correlated with reduction in cell size and cell growth. A moderate loss of viability without any change in cell-cycle profile was observed. Idelalisib treatment inhibited AKT activation, an immediate downstream PI3K effector, and also reduced phosphorylation levels of downstream AKT/mTOR pathway proteins such as PRAS40. In addition, idelalisib treatment impeded activation of the MAPK pathway, and MEK, ERK and p90RSK phosphorylation levels were reduced. Reduction in AKT, PDK1, and MEK phosphorylation correlated with protein synthesis inhibition.

CONCLUSIONS

Collectively, these results clarify the molecular mechanisms of actions and may provide biomarkers and targets for combination with idelalisib in B-cell malignancies. Clin Cancer Res; 23(1); 181-92. ©2016 AACR.

PenPC: A two-step approach to estimate the skeletons of high-dimensional directed acyclic graphs

Estimation of the skeleton of a directed acyclic graph (DAG) is of great importance for understanding the underlying DAG and causal effects can be assessed from the skeleton when the DAG is not identifiable. We propose a novel method named PenPC to estimate the skeleton of a high-dimensional DAG by a two-step approach. We first estimate the nonzero entries of a concentration matrix using penalized regression, and then fix the difference between the concentration matrix and the skeleton by evaluating a set of conditional independence hypotheses. For high-dimensional problems where the number of vertices p is in polynomial or exponential scale of sample size n, we study the asymptotic property of PenPC on two types of graphs: traditional random graphs where all the vertices have the same expected number of neighbors, and scale-free graphs where a few vertices may have a large number of neighbors. As illustrated by extensive simulations and applications on gene expression data of cancer patients, PenPC has higher sensitivity and specificity than the state-of-the-art method, the PC-stable algorithm.

DINGO: differential network analysis in genomics

MOTIVATION

Cancer progression and development are initiated by aberrations in various molecular networks through coordinated changes across multiple genes and pathways. It is important to understand how these networks change under different stress conditions and/or patient-specific groups to infer differential patterns of activation and inhibition. Existing methods are limited to correlation networks that are independently estimated from separate group-specific data and without due consideration of relationships that are conserved across multiple groups.

METHOD

We propose a pathway-based differential network analysis in genomics (DINGO) model for estimating group-specific networks and making inference on the differential networks. DINGO jointly estimates the group-specific conditional dependencies by decomposing them into global and group-specific components. The delineation of these components allows for a more refined picture of the major driver and passenger events in the elucidation of cancer progression and development.

RESULTS

Simulation studies demonstrate that DINGO provides more accurate group-specific conditional dependencies than achieved by using separate estimation approaches. We apply DINGO to key signaling pathways in glioblastoma to build differential networks for long-term survivors and short-term survivors in The Cancer Genome Atlas. The hub genes found by mRNA expression, DNA copy number, methylation and microRNA expression reveal several important roles in glioblastoma progression.

AVAILABILITY AND IMPLEMENTATION

R Package at: odin.mdacc.tmc.edu/∼vbaladan.

CONTACT

veera@mdanderson.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Prognostic gene signature identification using causal structure learning: applications in kidney cancer

Identification of molecular-based signatures is one of the critical steps toward finding therapeutic targets in cancer. In this paper, we propose methods to discover prognostic gene signatures under a causal structure learning framework across the whole genome. The causal structures are represented by directed acyclic graphs (DAGs), wherein we construct gene-specific network modules that constitute a gene and its corresponding regulators. The modules are then subsequently used to correlate with survival times, thus, allowing for a network-oriented approach to gene selection to adjust for potential confounders, as opposed to univariate (gene-by-gene) approaches. Our methods are motivated by and applied to a clear cell renal cell carcinoma (ccRCC) study from The Cancer Genome Atlas (TCGA) where we find several prognostic genes associated with cancer progression - some of which are novel while others confirm existing findings.

Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation

Motivated by the problem of construction of gene co-expression network, we propose a statistical framework for estimating high-dimensional partial correlation matrix by a three-step approach. We first obtain a penalized estimate of a partial correlation matrix using ridge penalty. Next we select the non-zero entries of the partial correlation matrix by hypothesis testing. Finally we re-estimate the partial correlation coefficients at these non-zero entries. In the second step, the null distribution of the test statistics derived from penalized partial correlation estimates has not been established. We address this challenge by estimating the null distribution from the empirical distribution of the test statistics of all the penalized partial correlation estimates. Extensive simulation studies demonstrate the good performance of our method. Application on a yeast cell cycle gene expression data shows that our method delivers better predictions of the protein-protein interactions than the Graphic Lasso.