Jianhua Hu

Loss of PTEN promotes resistance to T cell–mediated immunotherapy

UNLABELLED T cell-mediated immunotherapies are promising cancer treatments. However, most patients still fail to respond to these therapies. The molecular determinants of immune resistance are poorly understood. We show that loss of PTEN in tumor cells in preclinical models of melanoma inhibits T cell-mediated tumor killing and decreases T-cell trafficking into tumors. In patients, PTEN loss correlates with decreased T-cell infiltration at tumor sites, reduced likelihood of successful T-cell expansion from resected tumors, and inferior outcomes with PD-1 inhibitor therapy. PTEN loss in tumor cells increased the expression of immunosuppressive cytokines, resulting in decreased T-cell infiltration in tumors, and inhibited autophagy, which decreased T cell-mediated cell death. Treatment with a selective PI3Kβ inhibitor improved the efficacy of both anti-PD-1 and anti-CTLA-4 antibodies in murine models. Together, these findings demonstrate that PTEN loss promotes immune resistance and support the rationale to explore combinations of immunotherapies and PI3K-AKT pathway inhibitors. SIGNIFICANCE This study adds to the growing evidence that oncogenic pathways in tumors can promote resistance to the antitumor immune response. As PTEN loss and PI3K-AKT pathway activation occur in multiple tumor types, the results support the rationale to further evaluate combinatorial strategies targeting the PI3K-AKT pathway to increase the efficacy of immunotherapy.

Analysis of Immune Signatures in Longitudinal Tumor Samples Yields Insight into Biomarkers of Response and Mechanisms of Resistance to Immune Checkpoint Blockade

UNLABELLED Immune checkpoint blockade represents a major breakthrough in cancer therapy; however, responses are not universal. Genomic and immune features in pretreatment tumor biopsies have been reported to correlate with response in patients with melanoma and other cancers, but robust biomarkers have not been identified. We studied a cohort of patients with metastatic melanoma initially treated with cytotoxic T-lymphocyte-associated antigen-4 (CTLA4) blockade (n = 53) followed by programmed death-1 (PD-1) blockade at progression (n = 46), and analyzed immune signatures in longitudinal tissue samples collected at multiple time points during therapy. In this study, we demonstrate that adaptive immune signatures in tumor biopsy samples obtained early during the course of treatment are highly predictive of response to immune checkpoint blockade and also demonstrate differential effects on the tumor microenvironment induced by CTLA4 and PD-1 blockade. Importantly, potential mechanisms of therapeutic resistance to immune checkpoint blockade were also identified. SIGNIFICANCE These studies demonstrate that adaptive immune signatures in early on-treatment tumor biopsies are predictive of response to checkpoint blockade and yield insight into mechanisms of therapeutic resistance. These concepts have far-reaching implications in this age of precision medicine and should be explored in immune checkpoint blockade treatment across cancer types. Cancer Discov; 6(8); 827-37. ©2016 AACR.See related commentary by Teng et al., p. 818This article is highlighted in the In This Issue feature, p. 803.

Prognostic value of miR-155 in individuals with monoclonal B-cell lymphocytosis and patients with B chronic lymphocytic leukemia

Noncoding RNAs play a pivotal role in the pathogenesis of chronic lymphocytic leukemia (CLL). We hypothesized that microRNAs (miRs) are involved in the transition from monoclonal B-cell lymphocytosis (MBL) to CLL and tested miR-15a/16-1 cluster, miR-21, and miR-155 expression in purified B cells of normal individuals, individuals with MBL, and patients with CLL. When we analyzed 224 samples from 2 independent training and validation cohorts, we found that miR-155 was overexpressed in B cells from individuals with MBL, and even more so in B cells from patients with CLL, when compared with B cells from normal individuals. Furthermore, we were able to identify miR-155 in circulating microvesicles from both individuals with MBL and patients with CLL. Next, to examine the prognostic role of miR-155, we measured its expression level in plasma samples collected before treatment initiation in 228 patients with CLL. We found significantly higher miR-155 expression levels in patients who failed to achieve a complete response compared with those who experienced complete response. Our findings support the use of cellular and plasma levels of miR-155 as biomarkers for the risk of progression in individuals with MBL, as well as to identify patients with CLL who may not respond well to therapy.

Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance

Profiling of melanoma patients treated with checkpoint blockade reveals TCR clonality and copy number loss as correlates of therapeutic response. Checking on checkpoint inhibitors Immune checkpoint blockade has greatly improved the success of treatment in melanoma and other tumor types, but it is expensive and does not work for all patients. To optimize the likelihood of therapeutic success and reduce the risks and expense of unnecessary treatment, it would be helpful to find biomarkers that can predict treatment response. Roh et al. studied patients treated with sequential checkpoint inhibitors targeting CTLA-4 and then PD-1. In these patients, the authors discovered that a more clonal T cell population specifically correlates with response to PD-1 blockade, but not CTLA-4, which may help identify the best candidates for this treatment. In addition, increased frequency of gene copy number loss was correlated with decreased responsiveness to either therapy. Immune checkpoint blockade produces clinical benefit in many patients. However, better biomarkers of response are still needed, and mechanisms of resistance remain incompletely understood. To address this, we recently studied a cohort of melanoma patients treated with sequential checkpoint blockade against cytotoxic T lymphocyte antigen–4 (CTLA-4) followed by programmed death receptor–1 (PD-1) and identified immune markers of response and resistance. Building on these studies, we performed deep molecular profiling including T cell receptor sequencing and whole-exome sequencing within the same cohort and demonstrated that a more clonal T cell repertoire was predictive of response to PD-1 but not CTLA-4 blockade. Analysis of CNAs identified a higher burden of copy number loss in nonresponders to CTLA-4 and PD-1 blockade and found that it was associated with decreased expression of genes in immune-related pathways. The effect of mutational load and burden of copy number loss on response was nonredundant, suggesting the potential utility of a combinatorial biomarker to optimize patient care with checkpoint blockade therapy.

Serum Signature of Hypoxia-Regulated Factors Is Associated with Progression after Induction Therapy in Head and Neck Squamous Cell Cancer

Tumor hypoxia regulates many cytokines and angiogenic factors (CAF) and is associated with worse prognosis in head and neck squamous cell cancer (HNSCC). Serum CAF profiling may provide information regarding the biology of the host and tumor, prognosis, and response to therapy. We investigated 38 CAFs in HNSCC patients receiving induction therapy on a phase II trial of carboplatin, paclitaxel, and cetuximab. CAFs were measured by multiplex bead assay and enzyme-linked immunosorbent assay in 32 patients. Baseline and postinduction CAF levels were correlated with disease progression (PD) and human papilloma virus (HPV) status by Wilcoxon rank sum test. Baseline levels of eight hypoxia-regulated CAFs (the “high-risk signature” including vascular endothelial growth factor, interleukins 4 and 8, osteopontin, growth-related oncogene-α, eotaxin, granulocyte-colony stimulating factor, and stromal cell–derived factor-1α) were associated with subsequent PD. Elevation in ≥6 of 8 factors was strongly associated with shorter time to progression (P = 0.001) and was 73% specific and 100% sensitive for PD. Increasing growth-related oncogene-α from baseline to week 6 was also associated with PD. Progression-free and overall survival were shorter in patients with HPV-negative tumors (P = 0.012 and 0.046, respectively), but no individual CAF was associated with HPV status. However, among 14 HPV-negative patients, the high-risk CAF signature was seen in all 6 patients with PD, but only 2 of 14 without PD. In conclusion, serum CAF profiling, particularly in HPV-negative patients, may be useful for identifying those at highest risk for recurrence. Mol Cancer Ther; 9(6); 1755–63. ©2010 AACR.

A K-fold averaging cross-validation procedure

Cross-validation (CV) type of methods have been widely used to facilitate model estimation and variable selection. In this work, we suggest a new K-fold CV procedure to select a candidate ‘optimal’ model from each hold-out fold and average the K candidate ‘optimal’ models to obtain the ultimate model. Due to the averaging effect, the variance of the proposed estimates can be significantly reduced. This new procedure results in more stable and efficient parameter estimation than the classical K-fold CV procedure. In addition, we show the asymptotic equivalence between the proposed and classical CV procedures in the linear regression setting. We also demonstrate the broad applicability of the proposed procedure via two examples of parameter sparsity regularisation and quantile smoothing splines modelling. We illustrate the promise of the proposed method through simulations and a real data example.

Genomic and immune heterogeneity are associated with differential responses to therapy in melanoma

Appreciation for genomic and immune heterogeneity in cancer has grown though the relationship of these factors to treatment response has not been thoroughly elucidated. To better understand this, we studied a large cohort of melanoma patients treated with targeted therapy or immune checkpoint blockade (n = 60). Heterogeneity in therapeutic responses via radiologic assessment was observed in the majority of patients. Synchronous melanoma metastases were analyzed via deep genomic and immune profiling, and revealed substantial genomic and immune heterogeneity in all patients studied, with considerable diversity in T cell frequency, and few shared T cell clones (<8% on average) across the cohort. Variables related to treatment response were identified via these approaches and through novel radiomic assessment. These data yield insight into differential therapeutic responses to targeted therapy and immune checkpoint blockade in melanoma, and have key translational implications in the age of precision medicine.Melanoma: Tumor differences within a patient may explain heterogeneous responsesPatients with metastatic melanoma display molecular and immune differences across tumor sites associated with differential drug responses. A team led by Jennifer Wargo from the University of Texas MD Anderson Cancer Center, Houston, USA, studied the radiological responses of 60 patients with metastatic melanoma, half of whom received targeted drug therapy and half of whom received an immune checkpoint inhibitor. The majority (83%) showed differences in responses across metastases. The group then profiled tumors in a subset, and found molecular and immune heterogeneity in different tumors within the same patient. Heterogeneity in mutational and immune profiles within tumors from individual patients could explain differences in treatment response. Knowing this, the authors emphasize the importance of acquiring biopsies from more than one tumor site in order to best tailor therapies to the features of metastatic cancer.

Bypassing STAT3-mediated inhibition of the transcriptional regulator ID2 improves the antitumor efficacy of dendritic cells

Blocking tumor-derived cytokine signaling in dendritic cells enables engineered dendritic cells to function as an antitumor vaccine. Engineering antitumor activity Dendritic cells are critical mediators of the immune response to infection. Despite their potential, antitumor vaccines based on injecting dendritic cells have not been effective. Using mouse models of melanoma, Li et al. found that tumor cells release cytokines that suppress the ability of tumor-infiltrating dendritic cells to mount an antitumor response. The cytokines released from melanoma cells activated the transcription factor STAT3, which repressed the expression of the gene encoding the transcription regulator ID2. Constitutively expressing ID2 dampened production of proinflammatory cytokines in dendritic cells and promoted dendritic cell–mediated immunostimulatory lymphocyte responses. Vaccination experiments in tumor-bearing mice suggested that engineering dendritic cells to overcome or prevent the tumor-derived cytokine response in the injected dendritic cells, by either deleting STAT3 or overexpressing ID2, might prove an effective immunotherapy strategy in cancer patients. Despite the potent ability of dendritic cells (DCs) to stimulate lymphocyte responses and host immunity, granulocyte-macrophage colony-stimulating factor–derived DCs (GM-DCs) used as antitumor vaccines have demonstrated relatively modest success in cancer immunotherapy. We found that injecting GM-DCs into melanoma tumors in mice, or culturing GM-DCs with melanoma-secreted cytokines or melanoma-conditioned medium, rapidly suppressed DC-intrinsic expression of the gene encoding inhibitor of differentiation 2 (ID2), a transcriptional regulator. Melanoma-associated cytokines repressed Id2 transcription in murine DCs through the activation of signal transducer and activator of transcription 3 (STAT3). Enforced expression of ID2 in GM-DCs (ID2–GM-DCs) suppressed their production of the proinflammatory cytokine tumor necrosis factor–α (TNF-α). Vaccination with ID2–GM-DCs slowed the progression of melanoma tumors and enhanced animal survival, which was associated with an increased abundance of tumor-infiltrating interferon-γ–positive CD4+ effector and CD8+ cytotoxic T cells and a decreased number of tumor-infiltrating regulatory CD4+ T cells. The efficacy of the ID2–GM-DC vaccine was improved by combinatorial treatment with a blocking antibody to programmed cell death protein–1 (PD-1), a current immunotherapy that overcomes suppressive immune checkpoint signaling. Collectively, our data reveal a previously unrecognized STAT3-mediated immunosuppressive mechanism in DCs and indicate that DC-intrinsic ID2 promotes tumor immunity by modulating tumor-associated CD4+ T cell responses. Thus, inhibiting STAT3 or overexpressing ID2 selectively in DCs may improve the efficiency of DC vaccines in cancer therapy.

Identification of Differential Aberrations in Multiple-Sample Array CGH Studies

Most existing methods for identifying aberrant regions with array CGH data are confined to a single target sample. Focusing on the comparison of multiple samples from two different groups, we develop a new penalized regression approach with a fused adaptive lasso penalty to accommodate the spatial dependence of the clones. The nonrandom aberrant genomic segments are determined by assessing the significance of the differences between neighboring clones and neighboring segments. The algorithm proposed in this article is a first attempt to simultaneously detect the common aberrant regions within each group, and the regions where the two groups differ in copy number changes. The simulation study suggests that the proposed procedure outperforms the commonly used single-sample aberration detection methods for segmentation in terms of both false positives and false negatives. To further assess the value of the proposed method, we analyze a data set from a study that identified the aberrant genomic regions associated with grade subgroups of breast cancer tumors.

Estimation of Expression Indexes for Oligonucleotide Arrays Using the Singular Value Decomposition

Multiprobe oligonucleotide arrays are a widely used type of expression microarray with the attractive feature that numerous probes are used to represent each transcript. An “expression index” is a statistic used to represent expression level for a particular gene that is estimated from the probe hybridization intensities. We show that a popular model-based expression index proposed by Li and Wong has an interpretation as a component of the singular value decomposition (SVD) of the probe intensity matrix. Following this observation, we propose a new SVD model that accounts for differing variance structure across probes. We also propose that nonlinearity in intensity response to expression can be corrected to some extent through a data transformation, which is guided by an SVD entropy measure. The methods are demonstrated with simulation and applications to two real datasets.