Dormant tumors circumvent tumor-specific adaptive immunity by establishing a Treg-dominated niche via DKK3

Approximately 30% of breast cancer survivors deemed free of disease will experience locoregional or metastatic recurrence even up to 30 years after initial diagnosis, yet how residual/dormant tumor cells escape immunity elicited by the primary tumor remains unclear. We demonstrate that intrinsically dormant tumor cells are indeed recognized and lysed by antigen-specific T cells in vitro and elicit robust immune responses in vivo. However, despite close proximity to CD8+ killer T cells, dormant tumor cells themselves support early accumulation of protective FoxP3+ T regulatory cells (Tregs), which can be targeted to reduce tumor burden. These intrinsically dormant tumor cells maintain a hybrid epithelial/mesenchymal state that is associated with immune dysfunction, and we find that the tumor-derived, stem cell/basal cell protein Dickkopf WNT signaling pathway inhibitor 3 (DKK3) is critical for Treg inhibition of CD8+ T cells. We also demonstrate that DKK3 promotes immune-mediated progression of proliferative tumors and is significantly associated with poor survival and immunosuppression in human breast cancers. Together, these findings reveal that latent tumors can use fundamental mechanisms of tolerance to alter the T cell microenvironment and subvert immune detection. Thus, targeting these pathways, such as DKK3, may help render dormant tumors susceptible to immunotherapies.

Combination of a novel heat shock protein 90-targeted photodynamic therapy with PD-1/PD-L1 blockade induces potent systemic antitumor efficacy and abscopal effect against breast cancers

BACKGROUND

We previously demonstrated potent antitumor activity against human breast cancer xenografts using photodynamic therapy (PDT) targeting a novel tumor-specific photosensitizer (HS201), which binds heat shock protein 90 (HS201-PDT). However, induction of systemic antitumor immunity by HS201-PDT alone or by the combination strategy with immune checkpoint blockade has yet to be determined.

METHODS

Using unilateral and bilateral implantation models of syngeneic breast tumors (E0771, MM3MG-HER2, and JC-HER3) in mice, we assessed whether HS201-PDT could induce local and systemic antitumor immunity. In an attempt to achieve a stronger abscopal effect for distant tumors, the combination strategy with anti-PD-L1 antibody was tested. Tumor-infiltrating leukocytes were analyzed by single cell RNA-sequencing and receptor-ligand interactome analysis to characterize in more detailed the mechanisms of action of the treatment and key signaling pathways involved.

RESULTS

HS201-PDT demonstrated greater tumor control and survival in immune competent mice than in immunocompromised mice, suggesting the role of induced antitumor immunity; however, survival was modest and an abscopal effect on distant implanted tumor was weak. A combination of HS201-PDT with anti-PD-L1 antibody demonstrated the greatest antigen-specific immune response, tumor growth suppression, prolonged mouse survival time and abscopal effect. The most significant increase of intratumoral, activated CD8+T cells and decrease of exhausted CD8+T cells occurred following combination treatment compared with HS201-PDT monotherapy. Receptor-ligand interactome analysis showed marked enhancement of several pathways, such as CXCL, GALECTIN, GITRL, PECAM1 and NOTCH, associated with CD8+T cell activation in the combination group. Notably, the expression of the CXCR3 gene signature was the highest in the combination group, possibly explaining the enhanced tumor infiltration by T cells.

CONCLUSIONS

The increased antitumor activity and upregulated CXCR3 gene signature induced by the combination of anti-PD-L1 antibody with HS201-PDT warrants the clinical testing of HS201-PDT combined with PD-1/PD-L1 blockade in patients with breast cancer, and the use of the CXCR3 gene signature as a biomarker.

Sensitizing immune unresponsive colorectal cancers to immune checkpoint inhibitors through MAVS overexpression

Background

The majority of colorectal carcinomas (CRCs) are insensitive to programmed death protein-1/programmed death-ligand 1 (anti-PD-1/PD-L1) immune checkpoint inhibitor (ICI) antibodies. While there are many causes for ICI insensitivity, recent studies suggest that suppression of innate immune gene expression in tumor cells could be a root cause of this insensitivity and an important factor in the evolution of tumor immunosuppression.

Methods

We first assessed the reduction of mitochondrial antiviral signaling gene (MAVS) and related RIG-I pathway gene expression in several patient RNA expression datasets. We then engineered MAVS expressing tumor cells and tested their ability to elicit innate and adaptive anti-tumor immunity using both in vitro and in vivo approaches, which we then confirmed using MAVS expressing viral vectors. Finally, we observed that MAVS stimulated PD-L1 expression in multiple cell types and then assessed the combination of PD-L1 ICI antibodies with MAVS tumor expression in vivo.

Results

MAVS was significantly downregulated in CRCs, but its re-expression could stimulate broad cellular interferon-related responses, in both murine and patient-derived CRCs. In vivo, local MAVS expression elicited significant anti-tumor responses in both immune-sensitive and insensitive CRC models, through the stimulation of an interferon responsive axis that provoked tumor antigen-specific adaptive immunity. Critically, we found that tumor-intrinsic MAVS expression triggered systemic adaptive immune responses that enabled abscopal CD8 +T cell cytotoxicity against distant CRCs. As MAVS also induced PD-L1 expression, we further found synergistic anti-tumor responses in combination with anti-PD-L1 ICIs.

Conclusion

These data demonstrate that intratumoral MAVS expression results in local and systemic tumor antigen-specific T cell responses, which could be combined with PD-L1 ICI to permit effective anti-tumor immunotherapy in ICI resistant cancers.

Combination of ultrasound-based mechanical disruption of tumor with immune checkpoint blockade modifies tumor microenvironment and augments systemic antitumor immunity

Background

Despite multimodal adjuvant management with radiotherapy, chemotherapy and hormonal therapies, most surgically resected primary breast cancers relapse or metastasize. A potential solution to late and distant recurrence is to augment systemic antitumor immunity, in part by appropriately presenting tumor antigens, but also by modulating the immunosuppressive tumor microenvironment (TME). We previously validated this concept in models of murine carcinoma treated with a novel predominately microcavitating version of high-intensity focused ultrasound (HIFU), mechanical high-intensity focused ultrasound (M-HIFU). Here we elucidated the mechanisms of enhanced antitumor immunity by M-HIFU over conventional thermal high-intensity focused ultrasound (T-HIFU) and investigated the potential of the combinatorial strategy with an immune checkpoint inhibitor, anti-PD-L1 antibody.

Methods

The antitumor efficacy of treatments was investigated in syngeneic murine breast cancer models using triple-negative (E0771) or human ErbB-2 (HER2) expressing (MM3MG-HER2) tumors in C57BL/6 or BALB/c mice, respectively. Induction of systemic antitumor immunity by the treatments was tested using bilateral tumor implantation models. Flow cytometry, immunohistochemistry, and single-cell RNA sequencing were performed to elucidate detailed effects of HIFU treatments or combination treatment on TME, including the activation status of CD8 T cells and polarization of tumor-associated macrophages (TAMs).

Results

More potent systemic antitumor immunity and tumor growth suppression were induced by M-HIFU compared with T-HIFU. Molecular characterization of the TME after M-HIFU by single-cell RNA sequencing demonstrated repolarization of TAM to the immunostimulatory M1 subtype compared with TME post-T-HIFU. Concurrent anti-PD-L1 antibody administration or depletion of CD4⁺ T cells containing a population of regulatory T cells markedly increased T cell-mediated antitumor immunity and tumor growth suppression at distant, untreated tumor sites in M-HIFU treated mice compared with M-HIFU monotherapy. CD8 T and natural killer cells played major roles as effector cells in the combination treatment.

Conclusions

Physical disruption of the TME by M-HIFU repolarizes TAM, enhances T-cell infiltration, and, when combined with anti-PD-L1 antibody, mediates superior systemic antitumor immune responses and distant tumor growth suppression. These findings suggest M-HIFU combined with anti-PD-L1 may be useful in reducing late recurrence or metastasis when applied to primary tumors.

Development of a fertility risk calculator to predict individualized chance of ovarian failure after chemotherapy

PURPOSE

To develop an innovative machine learning (ML) model that predicts personalized risk of primary ovarian insufficiency (POI) after chemotherapy for reproductive-aged women. Currently, individualized prediction of a patient's risk of POI is challenging.

METHODS

Authors of published studies examining POI after gonadotoxic therapy were contacted, and six authors shared their de-identified data (N = 435). A composite outcome for POI was determined for each patient and validated by 3 authors. The primary dataset was partitioned into training and test sets; random forest binary classifiers were trained, and mean prediction scores were computed. Institutional data collected from a cross-sectional survey of cancer survivors (N = 117) was used as another independent validation set.

RESULTS

Our model predicted individualized risk of POI with an accuracy of 88% (area under the ROC 0.87, 95% CI: 0.77-0.96; p < 0.001). Mean prediction scores for patients who developed POI and who did not were 0.60 and 0.38 (t-test p < 0.001), respectively. Highly weighted variables included age, chemotherapy dose, prior treatment, smoking, and baseline diminished ovarian reserve.

CONCLUSION

We developed an ML-based model to estimate personalized risk of POI after chemotherapy. Our web-based calculator will be a user-friendly decision aid for individualizing risk prediction in oncofertility consultations.

HSP90-specific nIR probe identifies aggressive prostate cancers: translation from preclinical models to a human phase I study

A noninvasive test to discriminate indolent prostate cancers from lethal ones would focus treatment where necessary while reducing over-treatment. We exploited the known activity of heat shock protein 90 (Hsp90) as a chaperone critical for the function of numerous oncogenic drivers, including the androgen receptor and its variants, to detect aggressive prostate cancer. We linked a near infrared fluorescing molecule to an HSP90 binding drug and demonstrated that this probe (designated HS196) was highly sensitive and specific for detecting implanted prostate cancer cell lines with greater uptake by more aggressive subtypes. In a phase I human study, systemically administered HS196 could be detected in malignant nodules within prostatectomy specimens. Single-cell RNA sequencing identified uptake of HS196 by malignant prostate epithelium from the peripheral zone (AMACR+ERG+EPCAM+ cells), including SYP+ neuroendocrine cells that are associated with therapeutic resistance and metastatic progression. A theranostic version of this molecule is under clinical testing.

HER2 Isoforms Uniquely Program Intratumor Heterogeneity and Predetermine Breast Cancer Trajectories During the Occult Tumorigenic Phase

HER2-positive breast cancers are among the most heterogeneous breast cancer subtypes. The early amplification of HER2 and its known oncogenic isoforms provide a plausible mechanism in which distinct programs of tumor heterogeneity could be traced to the initial oncogenic event. Here a Cancer rainbow mouse simultaneously expressing fluorescently barcoded wildtype (^WTHER2), exon-16 null (^d16HER2), and N-terminally truncated (^p95HER2) HER2 isoforms is used to trace tumorigenesis from initiation to invasion. Tumorigenesis was visualized using whole-gland fluorescent lineage tracing and single-cell molecular pathology. We demonstrate that within weeks of expression, morphologic aberrations were already present and unique to each HER2 isoform. Although ^WTHER2 cells were abundant throughout the mammary ducts, detectable lesions were exceptionally rare. In contrast, ^d16HER2 and ^p95HER2 induced rapid tumor development. ^d16HER2 incited homogenous and proliferative luminal-like lesions which infrequently progressed to invasive phenotypes whereas ^p95HER2 lesions were heterogenous and invasive at the smallest detectable stage. Distinct cancer trajectories were observed for ^d16HER2 and ^p95HER2 tumors as evidenced by oncogene-dependent changes in epithelial specification and the tumor microenvironment. These data provide direct experimental evidence that intratumor heterogeneity programs begin very early and well in advance of screen or clinically detectable breast cancer. IMPLICATIONS: Although all HER2 breast cancers are treated equally, we show a mechanism by which clinically undetected HER2 isoforms program heterogenous cancer phenotypes through biased epithelial specification and adaptations within the tumor microenvironment.

Intratumoral Plasmid IL12 Expands CD8+ T Cells and Induces a CXCR3 Gene Signature in Triple-negative Breast Tumors that Sensitizes Patients to Anti-PD-1 Therapy

PURPOSE

Triple-negative breast cancer (TNBC) is an aggressive disease with limited therapeutic options. Antibodies targeting programmed cell death protein 1 (PD-1)/PD-1 ligand 1 (PD-L1) have entered the therapeutic landscape in TNBC, but only a minority of patients benefit. A way to reliably enhance immunogenicity, T-cell infiltration, and predict responsiveness is critically needed.

PATIENTS AND METHODS

Using mouse models of TNBC, we evaluate immune activation and tumor targeting of intratumoral IL12 plasmid followed by electroporation (tavokinogene telseplasmid; Tavo). We further present a single-arm, prospective clinical trial of Tavo monotherapy in patients with treatment refractory, advanced TNBC (OMS-I140). Finally, we expand these findings using publicly available breast cancer and melanoma datasets.

RESULTS

Single-cell RNA sequencing of murine tumors identified a CXCR3 gene signature (CXCR3-GS) following Tavo treatment associated with enhanced antigen presentation, T-cell infiltration and expansion, and PD-1/PD-L1 expression. Assessment of pretreatment and posttreatment tissue from patients confirms enrichment of this CXCR3-GS in tumors from patients that exhibited an enhancement of CD8⁺ T-cell infiltration following treatment. One patient, previously unresponsive to anti-PD-L1 therapy, but who exhibited an increased CXCR3-GS after Tavo treatment, went on to receive additional anti-PD-1 therapy as their immediate next treatment after OMS-I140, and demonstrated a significant clinical response.

CONCLUSIONS

These data show a safe, effective intratumoral therapy that can enhance antigen presentation and recruit CD8 T cells, which are required for the antitumor efficacy. We identify a Tavo treatment-related gene signature associated with improved outcomes and conversion of nonresponsive tumors, potentially even beyond TNBC.

Abstract PS17-22: Intratumoral delivery of tavokinogene telseplasmid (plasmid IL-12) and electroporation induces an immune signature that predicts successful combination in patients

Interleukin-12 (IL-12) is a pro-inflammatory cytokine involved in the generation of an inflammatory tumor microenvironment and is critical in eliciting a productive anti-tumor immune response. It has been investigated as an anti-cancer therapeutic using various delivery routes, but intratumoral injection of plasmid IL-12 (tavokinogene telseplasmid; TAVO) followed by electroporation is a gene therapy approach that results in more sustained production of IL-12 locally with minimal systemic immune-related toxicity. Here we show that TAVO not only provides protection in the treated triple-negative breast cancer (TNBC) lesion, but also induces a systemic, abscopal effect. Single cell RNAsequencing (scRNAseq) of infiltrating immune cells shows a significant increase in both CD4 and CD8 T cells as well as dendritic cells within the treated lesions, while simultaneously decreasing a granulocytic myeloid derived suppressor population. scRNAseq allows for a detailed look into not only the overall pathway enrichment caused by TAVO treatment, but also the specific receptor-ligand interactions occurring between cell types. A combination of these analyses revealed an enrichment in the IFN-gamma induced PDL1 pathway by TAVO, typified by an increase in the interaction between PDL1 on dendritic cells and PD1 on CD8 T cells. Further, dramatic enrichment of the CXCL9/10/11/CXCR3 axis was observed, consistent with previous studies in melanoma. Analysis of paired TCR alpha and beta chains on T cells additionally demonstrated a dramatic shift in tumor infiltrating T cell (TIL) clonality and frequency. In sum, these preclinical studies identify a signature of increased antigen presentation, T cell infiltration and expansion, and a decrease in the number of granulocytes but also a particular enhancement of the PDL1 immunosuppressive pathway following TAVO treatment. Using this signature, we focus on an in-depth analysis of 2 patients from a single arm, prospective clinical trial of TAVO monotherapy (OMS-I140) in pre-treated advanced TNBC that went on to receive anti-PD-1 as their immediate next therapy with clinical anti-tumor response. Together these data support the combination of TAVO with PD1/PDL1 inhibitors while also identifying other key pathways that may enhance responsiveness in TNBC patients for whom treatment options remain limited.

Citation Format: Erika J Crosby, Hiroshi Nagata, Melinda L Telli, Chaitanya R Acharya, Irene Wapnir, Kaitlin Zablotsky, Erica Browning, Reneta Hermiz, Lauren Svenson, Donna Bannavong, Kellie Malloy, David A Canton, Chris G Twitty, Takuya Osada, Herbert Kim Lyerly. Intratumoral delivery of tavokinogene telseplasmid (plasmid IL-12) and electroporation induces an immune signature that predicts successful combination in patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS17-22.

Stimulation of Oncogene-Specific Tumor-Infiltrating T Cells through Combined Vaccine and αPD-1 Enable Sustained Antitumor Responses against Established HER2 Breast Cancer

PURPOSE

Despite promising advances in breast cancer immunotherapy, augmenting T-cell infiltration has remained a significant challenge. Although neither individual vaccines nor immune checkpoint blockade (ICB) have had broad success as monotherapies, we hypothesized that targeted vaccination against an oncogenic driver in combination with ICB could direct and enable antitumor immunity in advanced cancers.

EXPERIMENTAL DESIGN

Our models of HER2⁺ breast cancer exhibit molecular signatures that are reflective of advanced human HER2⁺ breast cancer, with a small numbers of neoepitopes and elevated immunosuppressive markers. Using these, we vaccinated against the oncogenic HER2Δ16 isoform, a nondriver tumor-associated gene (GFP), and specific neoepitopes. We further tested the effect of vaccination or anti-PD-1, alone and in combination.

RESULTS

We found that only vaccination targeting HER2Δ16, a driver of oncogenicity and HER2-therapeutic resistance, could elicit significant antitumor responses, while vaccines targeting a nondriver tumor-specific antigen or tumor neoepitopes did not. Vaccine-induced HER2-specific CD8⁺ T cells were essential for responses, which were more effective early in tumor development. Long-term tumor control of advanced cancers occurred only when HER2Δ16 vaccination was combined with αPD-1. Single-cell RNA sequencing of tumor-infiltrating T cells revealed that while vaccination expanded CD8 T cells, only the combination of vaccine with αPD-1 induced functional gene expression signatures in those CD8 T cells. Furthermore, we show that expanded clones are HER2-reactive, conclusively demonstrating the efficacy of this vaccination strategy in targeting HER2.

CONCLUSIONS

Combining oncogenic driver targeted vaccines with selective ICB offers a rational paradigm for precision immunotherapy, which we are clinically evaluating in a phase II trial (NCT03632941).

An age-independent gene signature for monitoring acute rejection in kidney transplantation

Acute rejection (AR) remains a significant problem that negatively impacts long-term renal allograft survival. Numerous therapies are used to prevent AR that differ by center and recipient age. This variability confounds diagnostic methods. Methods: To develop an age-independent gene signature for AR effective across a broad array of immunosuppressive regimens, we compiled kidney transplant biopsy (n=1091) and peripheral blood (n=392) gene expression profiles from 12 independent public datasets. After removing genes differentially expressed in pediatric and adult patients, we compared gene expression profiles from biopsy and peripheral blood samples of patients with AR to those who were stable (STA), using Mann-Whitney U Tests with validation in independent testing datasets. We confirmed this signature in pediatric and adult patients (42 AR and 47 STA) from our institutional biorepository. Results: We identified a novel age-independent gene network that identified AR from both kidney and blood samples. We developed a 90-probe set signature targeting 76 genes that differentiated AR from STA and found an 8 gene subset (DIP2C, ENOSF1, FBXO21, KCTD6, PDXDC1, REXO2, HLA-E, and RAB31) that was associated with AR. Conclusion: We used publicly available datasets to create a gene signature of AR that identified AR irrespective of immunosuppression regimen or recipient age. This study highlights a novel model to screen and validate biomarkers across multiple treatment regimens.

Patient and in vitro fertilization (IVF) cycle characteristics associated with variable blastulation rates: a retrospective study from the Duke Fertility Center (2013–2017)

Background

To evaluate the association of patient and IVF cycle characteristics with blastulation rate and formation of high-quality blastocysts

Results

We analyzed autologous blastocyst cycles from 2013 to 2017. Cycles were subdivided into low (< 33%), intermediate (33–66%), and high (> 66%) blastulation rates. Embryo quality was assigned by embryologists using Gardner Criteria. R statistical package was used, and the blastulation groups were compared using analysis of variance (ANOVA) for continuous variables and chi-squared tests for categorical variables. The Bonferroni correction was used to adjust for multiple comparisons. One hundred seventeen IVF cycles met our inclusion criteria. Of these, 20 (17.1%) had low, 74 (63.2%) had intermediate, and 23 (19.7%) had high blastulation rates. Low blastulation rate was associated with a lower number of blastocysts, including fewer high-quality blastocysts. The mean number of oocytes retrieved was highest (18.1) in the group with the lowest blastulation rate, and lowest (13.4) in those with the highest blastulation rate, although this did not reach statistical significance. There were no significant differences between blastulation rates and age, gravidity, prior live birth, anti-mullerian hormone, estradiol and progesterone levels on the day of ovulation trigger, follicle-stimulating hormone dose, or fertility diagnosis.

Conclusions

High blastulation rate is associated with a greater number of blastocysts, including a greater number of high-quality blastocysts. Higher oocyte yield, however, is not associated with improved blastulation rates. Blastulation rates, blastocyst number, and quality remain difficult to predict based on cycle characteristics alone, and oocyte yield may not be an accurate predictor of either outcome.

Freezing of all embryos in in vitro fertilization is beneficial in high responders, but not intermediate and low responders: an analysis of 82,935 cycles from the Society for Assisted Reproductive Technology registry

OBJECTIVE

To assess in vitro fertilization (IVF) and pregnancy outcomes in patients having their first frozen embryo transfer (FET) after a freeze-all cycle versus similar patients having their first fresh embryo transfer (ET).

DESIGN

Retrospective cohort study.

SETTING

None.

PATIENT(S)

Registry data on 82,935 patient cycles from the Society for Assisted Reproductive Technology (SART).

INTERVENTION(S)

All first fresh autologous IVF cycles were analyzed and compared to first FET cycles after a freeze-all first IVF stimulation. The cycles were subdivided into cohorts based upon the number of oocytes retrieved (OR): 1-5 (low), 6-14 (intermediate), and 15+ (high responders). Univariate analyses were performed on cycle characteristics, and multivariable regression analyses were performed on outcome data.

MAIN OUTCOME MEASURE(S)

Clinical pregnancy rate (CPR) and live-birth rate (LBR).

RESULTS

Of the 82,935 cycles analyzed, 69,102 patients had their first fresh transfer, and 13,833 had a first FET. High responders were found to have a higher CPR and LBR in the FET cycles compared with the fresh ET cycles (61.5 vs. 57.4%; 52.0 vs. 48.9%). In intermediate responders, both CPR and LBR were higher after fresh ET compared with FET (49.6% vs. 44.2%; 41.2 vs. 35.3%). Similarly, in low responders, CPR and LBR were higher after fresh compared with FET (33.2% vs. 15.9%; 25.9% vs. 11.5%).

CONCLUSION(S)

A freeze-all strategy is beneficial in high responders but not in intermediate or low responders, thus refuting the idea that freeze-all cycles are preferable for all patients.

Mapping eQTL by leveraging multiple tissues and DNA methylation

Background

DNA methylation is an important tissue-specific epigenetic event that influences transcriptional regulation of gene expression. Differentially methylated CpG sites may act as mediators between genetic variation and gene expression, and this relationship can be exploited while mapping multi-tissue expression quantitative trait loci (eQTL). Current multi-tissue eQTL mapping techniques are limited to only exploiting gene expression patterns across multiple tissues either in a joint tissue or tissue-by-tissue frameworks. We present a new statistical approach that enables us to model the effect of germ-line variation on tissue-specific gene expression in the presence of effects due to DNA methylation.

Results

Our method efficiently models genetic and epigenetic variation to identify genomic regions of interest containing combinations of mRNA transcripts, CpG sites, and SNPs by jointly testing for genotypic effect and higher order interaction effects between genotype, methylation and tissues. We demonstrate using Monte Carlo simulations that our approach, in the presence of both genetic and DNA methylation effects, gives an improved performance (in terms of statistical power) to detect eQTLs over the current eQTL mapping approaches. When applied to an array-based dataset from 150 neuropathologically normal adult human brains, our method identifies eQTLs that were undetected using standard tissue-by-tissue or joint tissue eQTL mapping techniques. As an example, our method identifies eQTLs by leveraging methylated CpG sites in a LIM homeobox member gene (LHX9), which may have a role in the neural development.

Conclusions

Our score test-based approach does not need parameter estimation under the alternative hypothesis. As a result, our model parameters are estimated only once for each mRNA - CpG pair. Our model specifically studies the effects of non-coding regions of DNA (in this case, CpG sites) on mapping eQTLs. However, we can easily model micro-RNAs instead of CpG sites to study the effects of post-transcriptional events in mapping eQTL. Our model’s flexible framework also allows us to investigate other genomic events such as alternative gene splicing by extending our model to include gene isoform-specific data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1856-9) contains supplementary material, which is available to authorized users.

A novel integrative risk index of papillary thyroid cancer progression combining genomic alterations and clinical factors

Although the majority of papillary thyroid cancer (PTC) is indolent, a subset of PTC behaves aggressively despite the best available treatment. A major clinical challenge is to reliably distinguish early on between those patients who need aggressive treatment from those who do not. Using a large cohort of PTC samples obtained from The Cancer Genome Atlas (TCGA), we analyzed the association between disease progression and multiple forms of genomic data, such as transcriptome, somatic mutations, and somatic copy number alterations, and found that genes related to FOXM1 signaling pathway were significantly associated with PTC progression. Integrative genomic modeling was performed, controlling for demographic and clinical characteristics, which included patient age, gender, TNM stages, histological subtypes, and history of other malignancy, using a leave-one-out elastic net model and 10-fold cross validation. For each subject, the model from the remaining subjects was used to determine the risk index, defined as a linear combination of the clinical and genomic variables from the elastic net model, and the stability of the risk index distribution was assessed through 2,000 bootstrap resampling. We developed a novel approach to combine genomic alterations and patient-related clinical factors that delineates the subset of patients who have more aggressive disease from those whose tumors are indolent and likely will require less aggressive treatment and surveillance (p = 4.62 × 10-10, log-rank test). Our results suggest that risk index modeling that combines genomic alterations with current staging systems provides an opportunity for more effective anticipation of disease prognosis and therefore enhanced precision management of PTC.

Exploiting expression patterns across multiple tissues to map expression quantitative trait loci

BACKGROUND

In order to better understand complex diseases, it is important to understand how genetic variation in the regulatory regions affects gene expression. Genetic variants found in these regulatory regions have been shown to activate transcription in a tissue-specific manner. Therefore, it is important to map the aforementioned expression quantitative trait loci (eQTL) using a statistically disciplined approach that jointly models all the tissues and makes use of all the information available to maximize the power of eQTL mapping. In this context, we are proposing a score test-based approach where we model tissue-specificity as a random effect and investigate an overall shift in the gene expression combined with tissue-specific effects due to genetic variants.

RESULTS

Our approach has 1) a distinct computational edge, and 2) comparable performance in terms of statistical power over other currently existing joint modeling approaches such as MetaTissue eQTL and eQTL-BMA. Using simulations, we show that our method increases the power to detect eQTLs when compared to a tissue-by-tissue approach and can exceed the performance, in terms of computational speed, of MetaTissue eQTL and eQTL-BMA. We apply our method to two publicly available expression datasets from normal human brains, one comprised of four brain regions from 150 neuropathologically normal samples and another comprised of ten brain regions from 134 neuropathologically normal samples, and show that by using our method and jointly analyzing multiple brain regions, we identify eQTLs within more genes when compared to three often used existing methods.

CONCLUSIONS

Since we employ a score test-based approach, there is no need for parameter estimation under the alternative hypothesis. As a result, model parameters only have to be estimated once per genome, significantly decreasing computation time. Our method also accommodates the analysis of next- generation sequencing data. As an example, by modeling gene transcripts in an analogous fashion to tissues in our current formulation one would be able to test for both a variant overall effect across all isoforms of a gene as well as transcript-specific effects. We implement our approach within the R package JAGUAR, which is now available at the Comprehensive R Archive Network repository.

Immune signatures predict prognosis in localized cancer

The host immune response can impact cancer growth, prognosis, and response to therapy. In colorectal cancer, the presence of cells involved with T-cell-mediated adaptive immunity predicts survival better than the current staging method. We used the expression of genes recently associated with host immune responses (T(H1)-mediated adaptive immunity, inflammation, and immune suppression) to perform hierarchical clustering of multiple large cohorts of cancer specimens to determine if immune-related gene expression resulted in clinical significant groupings of tumors. Microarray data from prostate cancer (n = 79), breast cancer (n = 132), lung cancer (n = 84), glioblastoma multiforme (n = 120), and lymphoma (n = 127) were analyzed. Among adenocarcinomas, the T(H1)-mediated adaptive immunity genes were consistently associated with better prognosis, while genes associated with inflammation and immune suppression were variably associated with outcome. Specifically, increased expression of the T(H1)-mediated adaptive immunity genes was associated with good prognosis in breast cancer patients under 45 years of age (p = .04, hazard ratio [HR] = 0.42) and in prostate cancer patients (p = .03, HR = 0.36) but not in lung cancer patients (p = 0.45, HR = 1.37). In lymphoma, patients with increased expression of inflammation and immune suppression genes had better prognosis than those expressing the T(H1)-mediated adaptive immunity genes (p = .01, HR = 0.43) and in glioblastoma multiforme, the expression of inflammation genes conferred improved prognosis than those expressing immune suppression genes (p = 0.05, HR = 0.62). In aggregate, the gene expression signatures implicating specific components of the immune response hold prognostic import across solid tumors.

Age-Specific Differences in Oncogenic Pathway Dysregulation in Patients With Acute Myeloid Leukemia

Purpose

To define the biology driving the aggressive nature of acute myeloid leukemia (AML) in elderly patients.

Patients and Methods

Clinically annotated microarray data from 425 patients with newly diagnosed de novo AML from two publicly available data sets were analyzed after age-specific cohorts (young ≤ 45 years, n = 175; elderly ≥ 55 years; n = 144) were prospectively identified. Gene expression analysis was conducted utilizing gene set enrichment analysis, and by applying previously defined and tested signature profiles reflecting dysregulation of oncogenic signaling pathways and altered tumor environment.

Results

Elderly AML patients as expected had worse overall survival and event-free survival compared with younger patients. Analysis of oncogenic pathways revealed that older patients had higher probability of RAS, Src, and tumor necrosis factor (TNF) pathway activation (all P < .0001). Hierarchical clustering revealed that younger patients with AML in cluster 2 had clinically worse survival, with high RAS, Src, and TNF pathway activation compared with patients in cluster 1. However, among elderly patients with AML, those in cluster 1 also demonstrated high RAS, Src, and TNF pathway activation but this did not translate into differences in survival.

Conclusion

AML in the elderly represents a distinct biologic entity characterized by unique patterns of deregulated signaling pathway variations that contributes to poor survival. These insights should enable development and adjustments of clinically meaningful treatment strategies in the older patient population.

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

Introduction

Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.

Methods

We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies.

Results

We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.

Conclusions

Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.

Young Age at Diagnosis Correlates With Worse Prognosis and Defines a Subset of Breast Cancers With Shared Patterns of Gene Expression

Purpose

Breast cancer arising in young women is correlated with inferior survival and higher incidence of negative clinicopathologic features. The biology driving this aggressive disease has yet to be defined.

Patients and Methods

Clinically annotated, microarray data from 784 early-stage breast cancers were identified, and prospectively defined, age-specific cohorts (young: ≤ 45 years, n = 200; older: ≥ 65 years, n = 211) were compared by prognosis, clinicopathologic variables, mRNA expression values, single-gene analysis, and gene set enrichment analysis (GSEA). Univariate and multivariate analyses were performed.

Results

Using clinicopathologic variables, young women illustrated lower estrogen receptor (ER) positivity (immunohistochemistry [IHC], P = .027), larger tumors (P = .012), higher human epidermal growth factor receptor 2 (HER-2) overexpression (IHC, P = .075), lymph node positivity (P = .008), higher grade tumors (P < .0001), and trends toward inferior disease-free survival (DFS; hazard ratio = 1.32; P = .094). Using genomic expression analysis, tumors arising in young women had significantly lower ERα mRNA (P < .0001), ERβ (P = .02), and progesterone receptor (PR) expression (P < .0001), but higher HER-2 (P < .0001) and epidermal growth factor receptor (EGFR) expression (P < .0001). Exploratory analysis (GSEA) revealed 367 biologically relevant gene sets significantly distinguishing breast tumors arising in young women. Combining clinicopathologic and genomic variables among tumors arising in young women demonstrated that younger age and lower ERβ and higher EGFR mRNA expression were significant predictors of inferior DFS.

Conclusion

This large-scale genomic analysis illustrates that breast cancer arising in young women is a unique biologic entity driven by unifying oncogenic signaling pathways, is characterized by less hormone sensitivity and higher HER-2/EGFR expression, and warrants further study to offer this poor-prognosis group of women better preventative and therapeutic options.

An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer

Background

A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective.

Methods and Results

Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy.

Conclusions

Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.

Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer

CONTEXT

Gene expression profiling may be useful for prognostic and therapeutic strategies in breast carcinoma.

OBJECTIVES

To demonstrate the value in integrating genomic information with clinical and pathological risk factors, to refine prognosis, and to improve therapeutic strategies for early stage breast cancer.

DESIGN, SETTING, AND PATIENTS

Retrospective study of patients with early stage breast carcinoma who were candidates for adjuvant chemotherapy; 964 clinically annotated breast tumor samples (573 in the initial discovery set and 391 in the validation cohort) with corresponding microarray data were used. All patients were assigned relapse risk scores based on their respective clinicopathological features. Signatures representing oncogenic pathway activation and tumor biology/microenvironment status were applied to these samples to obtain patterns of deregulation that correspond with relapse risk scores to refine prognosis with the clinicopathological prognostic model alone. Predictors of chemotherapeutic response were also applied to further characterize clinically relevant heterogeneity in early stage breast cancer.

MAIN OUTCOME MEASURES

Gene expression signatures and clinicopathological variables in early stage breast cancer to determine a refined estimation of relapse-free survival and sensitivity to chemotherapy.

RESULTS

In the initial data set of 573 patients, prognostically significant clusters representing patterns of oncogenic pathway activation and tumor biology/microenvironment states were identified within the low-risk (log-rank P = .004), intermediate-risk (log-rank P = .01), and high-risk (log-rank P = .003) model cohorts, representing clinically important genomic subphenotypes of breast cancer. As an example, in the low-risk cohort, of 6 prognostically significant clusters, patients in cluster 4 had an inferior relapse-free survival vs patients in cluster 1 (log-rank P = .004) and cluster 5 (log-rank P = .03). Median relapse-free survival for patients in cluster 4 was 16 months less than for patients in cluster 1 (95% CI, 7.5-24.5 months) and 19 months less than for patients in cluster 5 (95% CI, 10.5-27.5 months). Multivariate analyses confirmed the independent prognostic value of the genomic clusters (low risk, P = .05; high risk, P = .02). The reproducibility and validity of these patterns of pathway deregulation in predicting relapse risk was established using related but not identical clusters in the independent validation cohort. The prognostic clinicogenomic clusters also have unique sensitivity patterns to commonly used cytotoxic therapies.

CONCLUSIONS

These results provide preliminary evidence that incorporation of gene expression signatures into clinical risk stratification can refine prognosis. Prospective studies are needed to determine the value of this approach for individualizing therapeutic strategies.

Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial

BACKGROUND

We have previously described gene-expression signatures that predict growth inhibitory and cytotoxic effects of common chemotherapeutic drugs in vitro. The aim of this study was to confirm the validity of these gene-expression signatures in a large series of patients with oestrogen-receptor-negative breast tumours who were treated in a phase III neoadjuvant clinical trial.

METHODS

This trial compares a non-taxane regimen (fluorouracil, epirubicin, and cyclophosphamide [FEC] for six cycles) with a taxane regimen (docetaxel for three cycles followed by epirubicin plus docetaxel [TET] for three cycles) in women with oestrogen-receptor-negative breast cancer. The primary endpoint of the study is the difference in progression-free survival based on TP53 status and will be reported later. Predicting response with gene signatures was a planned secondary endpoint of the trial and is reported here. Pathological complete response, defined as complete disappearance of the tumour with no more than a few scattered tumour cells detected by the pathologist in the resection specimen, was used to assess chemosensitivity. RNA was prepared from sections of frozen biopsies taken at diagnosis and hybridised to Affymetrix X3P microarrays. In-vitro single-agent drug sensitivity signatures were combined to obtain FEC and TET regimen-specific signatures. This study is registered on the clinical trials site of the US National Cancer Institute website http://www.clinicaltrials.gov/ct/show/NCT00017095.

FINDINGS

Of 212 patients with oestrogen-receptor-negative tumours assessed, 87 patients were excluded. 125 oestrogen-receptor-negative tumours (55 that showed pathological complete responses) were tested: 66 in the FEC group (28 that showed pathological complete responses) and 59 in the TET group (27 that showed pathological complete responses). The regimen-specific signatures significantly predicted pathological complete response in patients treated with the appropriate regimen (p<0.0001). The FEC predictor had a sensitivity of 96% (27 of 28 patients [95% CI 82-99]), specificity of 66% (25 of 38 patients [50-79]), positive predictive value (PPV) of 68% (27 of 40 patients [52-80]), and negative predictive value (NPV) of 96% (25 of 26 patients [81-99]). The TET predictor had a sensitivity of 93% (25 of 27 patients [77-98]), specificity 69% (22 of 32 patients [51-82]), PPV of 71% (25 of 35 patients [55-84]), and NPV of 92% (22 of 24 patients [74-98]). Analysis of tumour size, grade, nodal status, age, and regimen-specific signatures showed that the genomic signatures were the only independent variables predicting pathological complete response at p<0.01. Selection of patients with these signatures would increase the proportion of patients with pathological complete responses from 44% to around 70% in the patients studied here.

INTERPRETATION

We have validated the use of regimen-specific drug sensitivity signatures in the context of a multicentre randomised trial. The high NPV of both signatures may allow early selection of patients with breast cancer who should be considered for trials with new drugs.

Pharmacogenomic Strategies Provide a Rational Approach to the Treatment of Cisplatin-Resistant Patients With Advanced Cancer

Purpose

Standard treatment for advanced non–small-cell lung cancer (NSCLC) includes the use of a platinum-based chemotherapy regimen. However, response rates are highly variable. Newer agents, such as pemetrexed, have shown significant activity as second-line therapy and are currently being evaluated in the front-line setting. We utilized a genomic strategy to develop signatures predictive of chemotherapeutic response to both cisplatin and pemetrexed to provide a rational approach to effective individualized medicine.

Methods

Using in vitro drug sensitivity data, coupled with microarray data, we developed gene expression signatures predicting sensitivity to cisplatin and pemetrexed. Signatures were validated with response data from 32 independent ovarian and lung cancer cell lines as well as 59 samples from patients previously treated with cisplatin.

Results

Genomic-derived signatures of cisplatin and pemetrexed sensitivity were shown to accurately predict sensitivity in vitro and, in the case of cisplatin, to predict treatment response in patients treated with cisplatin. The accuracy of the cisplatin predictor, based on available clinical data, was 83.1% (sensitivity, 100%; specificity 57%; positive predictive value, 78%; negative predictive value, 100%). Interestingly, an inverse correlation was seen between in vitro cisplatin and pemetrexed sensitivity, and importantly, between the likelihood of cisplatin and pemetrexed response in patients.

Conclusion

The use of genomic predictors of response to cisplatin and pemetrexed can be incorporated into strategies to optimize therapy for advanced solid tumors.

The complete genome sequence of Roseobacter denitrificans reveals a mixotrophic rather than photosynthetic metabolism

Purple aerobic anoxygenic phototrophs (AAPs) are the only organisms known to capture light energy to enhance growth only in the presence of oxygen but do not produce oxygen. The highly adaptive AAPs compose more than 10% of the microbial community in some euphotic upper ocean waters and are potentially major contributors to the fixation of the greenhouse gas CO2. We present the complete genomic sequence and feature analysis of the AAP Roseobacter denitrificans, which reveal clues to its physiology. The genome lacks genes that code for known photosynthetic carbon fixation pathways, and most notably missing are genes for the Calvin cycle enzymes ribulose bisphosphate carboxylase (RuBisCO) and phosphoribulokinase. Phylogenetic evidence implies that this absence could be due to a gene loss from a RuBisCO-containing alpha-proteobacterial ancestor. We describe the potential importance of mixotrophic rather than autotrophic CO2 fixation pathways in these organisms and suggest that these pathways function to fix CO2 for the formation of cellular components but do not permit autotrophic growth. While some genes that code for the redox-dependent regulation of photosynthetic machinery are present, many light sensors and transcriptional regulatory motifs found in purple photosynthetic bacteria are absent.