The induction of CD11b(+)Gr-1(+) myeloid-derived suppressor cells (MDSCs) is an important immune-evading mechanism used by tumors. However, the exact nature and function of MDSCs remain elusive, especially because they constitute a heterogeneous population that has not yet been clearly defined. Here, we identified 2 distinct MDSC subfractions with clear morphologic, molecular, and functional differences. These fractions consisted of either mononuclear cells (MO-MDSCs), resembling inflammatory monocytes, or low-density polymorphonuclear cells (PMN-MDSCs), akin to immature neutrophils. Interestingly, both MO-MDSCs and PMN-MDSCs suppressed antigen-specific T-cell responses, albeit using distinct effector molecules and signaling pathways. Blocking IFN-gamma or disrupting STAT1 partially impaired suppression by MO-MDSCs, for which nitric oxide (NO) was one of the mediators. In contrast, while IFN-gamma was strictly required for the suppressor function of PMN-MDSCs, this did not rely on STAT1 signaling or NO production. Finally, MO-MDSCs were shown to be potential precursors of highly antiproliferative NO-producing mature macrophages. However, distinct tumors differentially regulated this inherent MO-MDSC differentiation program, indicating that this phenomenon was tumor driven. Overall, our data refine tumor-induced MDSC functions by uncovering mechanistically distinct MDSC subpopulations, potentially relevant for MDSC-targeted therapies.

Identification of discrete tumor-induced myeloid-derived suppressor cell subpopulations with distinct T-CELL suppressive activity

Cancer development and its response to therapy are regulated by inflammation, which either promotes or suppresses tumor progression, potentially displaying opposing effects on therapeutic outcomes. Chronic inflammation facilitates tumor progression and treatment resistance, whereas induction of acute inflammatory reactions often stimulates the maturation of dendritic cells (DCs) and antigen presentation, leading to anti-tumor immune responses. In addition, multiple signaling pathways, such as nuclear factor kappa B (NF-kB), Janus kinase/signal transducers and activators of transcription (JAK-STAT), toll-like receptor (TLR) pathways, cGAS/STING, and mitogen-activated protein kinase (MAPK); inflammatory factors, including cytokines (e.g., interleukin (IL), interferon (IFN), and tumor necrosis factor (TNF)-α), chemokines (e.g., C-C motif chemokine ligands (CCLs) and C-X-C motif chemokine ligands (CXCLs)), growth factors (e.g., vascular endothelial growth factor (VEGF), transforming growth factor (TGF)-β), and inflammasome; as well as inflammatory metabolites including prostaglandins, leukotrienes, thromboxane, and specialized proresolving mediators (SPM), have been identified as pivotal regulators of the initiation and resolution of inflammation. Nowadays, local irradiation, recombinant cytokines, neutralizing antibodies, small-molecule inhibitors, DC vaccines, oncolytic viruses, TLR agonists, and SPM have been developed to specifically modulate inflammation in cancer therapy, with some of these factors already undergoing clinical trials. Herein, we discuss the initiation and resolution of inflammation, the crosstalk between tumor development and inflammatory processes. We also highlight potential targets for harnessing inflammation in the treatment of cancer.

/pdf/inflammation-and-tumor-progression-signaling-pathways-and-45r30f9ce8.pdf

Inflammation and tumor progression: signaling pathways and targeted intervention.

As minimum feature size and pitch spacing further decrease, triple patterning lithography (TPL) is a possible 193nm extension along the paradigm of double patterning lithography (DPL). However, there is very little study on TPL layout decomposition. In this paper, we show that TPL layout decomposition is a more difficult problem than that for DPL. We then propose a general integer linear programming formulation for TPL layout decomposition which can simultaneously minimize conflict and stitch numbers. Since ILP has very poor scalability, we propose three acceleration techniques without sacrificing solution quality: independent component computation, layout graph simplification, and bridge computation. For very dense layouts, even with these speedup techniques, ILP formulation may still be too slow. Therefore, we propose a novel vector programming formulation for TPL decomposition, and solve it through effective semidefinite programming (SDP) approximation. Experimental results show that the ILP with acceleration techniques can reduce 82% runtime compared to the baseline ILP. Using SDP based algorithm, the runtime can be further reduced by 42% with some tradeoff in the stitch number (reduced by 7%) and the conflict (9% more). However, for very dense layouts, SDP based algorithm can achieve 140× speed-up even compared with accelerated ILP.

/pdf/layout-decomposition-for-triple-patterning-lithography-1bak910stu.pdf

Layout decomposition for triple patterning lithography

Amino acid metabolism is a critical regulator of the immune response, and its modulating becomes a promising approach in various forms of immunotherapy. Insufficient concentrations of essential amino acids restrict T-cells activation and proliferation. However, only arginases, that degrade L-arginine, as well as enzymes that hydrolyze L-tryptophan are substantially increased in cancer. Two arginase isoforms, ARG1 and ARG2, have been found to be present in tumors and their increased activity usually correlates with more advanced disease and worse clinical prognosis. Nearly all types of myeloid cells were reported to produce arginases and the increased numbers of various populations of myeloid-derived suppressor cells and macrophages correlate with inferior clinical outcomes of cancer patients. Here, we describe the role of arginases produced by myeloid cells in regulating various populations of immune cells, discuss molecular mechanisms of immunoregulatory processes involving L-arginine metabolism and outline therapeutic approaches to mitigate the negative effects of arginases on antitumor immune response. Development of potent arginase inhibitors, with improved pharmacokinetic properties, may lead to the elaboration of novel therapeutic strategies based on targeting immunoregulatory pathways controlled by L-arginine degradation.

/pdf/myeloid-cell-derived-arginase-in-cancer-immune-response-4351y0p3t8.pdf

Myeloid Cell-Derived Arginase in Cancer Immune Response

The gut microbiota has been implicated in cancer and shown to modulate anticancer drug efficacy. Altered gut microbiota is associated with resistance to chemo drugs or immune checkpoint inhibitors (ICIs), whereas supplementation of distinct bacterial species restores responses to the anticancer drugs. Accumulating evidence has revealed the potential of modulating the gut microbiota to enhance the efficacy of anticancer drugs. Regardless of the valuable findings by preclinical models and clinical data of patients with cancer, a more thorough understanding of the interactions of the microbiota with cancer therapy helps researchers identify novel strategy for cancer prevention, stratify patients for more effective treatment and reduce treatment complication. In this review, we discuss the scientific evidence on the role of gut microbiota in cancer treatment, and highlight the latest knowledge and technologies leveraged to target specific bacteria that contribute to tumourigenesis. First, we provide an overview of the role of the gut microbiota in cancer, establishing the links between bacteria, inflammation and cancer treatment. Second, we highlight the mechanisms used by distinct bacterial species to modulate cancer growth, immune responses, as well as the efficacy of chemotherapeutic drugs and ICIs. Third, we demonstrate various approaches to modulate the gut microbiota and their potential in translational research. Finally, we discuss the limitations of current microbiome research in the context of cancer treatment, ongoing efforts to overcome these challenges and future perspectives.

https://gut.bmj.com/content/gutjnl/69/10/1867.full.pdf

The role of gut microbiota in cancer treatment: friend or foe?

Mast cells are prominent components of solid tumors and exhibit distinct phenotypes in different tumor microenvironments. However, the nature, regulation, function, and clinical relevance of mast cells in human gastric cancer (GC) are presently unknown. Flow cytometry analyses were performed to examine level and phenotype of mast cells in samples from 114 patients with GC. Multivariate analysis of prognostic factors for overall survival was performed using the Cox proportional hazards model. Kaplan-Meier plots for patient survival were performed using the log-rank test. Mast cells, T cells and tumor cells were isolated or generated, stimulated and/or cultured for in vitro and in vivo function assays. Patients with GC showed a significantly higher mast cell infiltration in tumors. Mast cell levels increased with tumor progression and independently predicted reduced overall survival. These tumor-infiltrating mast cells accumulated in tumors by CXCL12-CXCR4 chemotaxis. Intratumoral mast cells expressed higher immunosuppressive molecule programmed death-ligand 1 (PD-L1), and mast cells induced by tumors strongly express PD-L1 proteins in both time-dependent and dose-dependent manners. Significant correlations were found between the levels of PD-L1+ mast cells and pro-inflammatory cytokine TNF-α in GC tumors, and tumor-derived TNF-α activated NF-κB signaling pathway to induce mast cell expression of PD-L1. The tumor-infiltrating and tumor-conditioned mast cells effectively suppressed normal T-cell immunity through PD-L1 in vitro, and tumor-conditioned mast cells contributed to the suppression of T-cell immunity and the growth of human GC tumors in vivo; the effect could be reversed by blocking PD-L1 on these mast cells. Thus, our results illuminate novel immunosuppressive and protumorigenic roles of mast cells in GC, and also present a novel mechanism in which PD-L1 expressing mast cells link the proinflammatory response to immune tolerance in the GC tumor milieu.

https://jitc.bmj.com/content/jitc/7/1/54.full.pdf

Increased intratumoral mast cells foster immune suppression and gastric cancer progression through TNF-α-PD-L1 pathway.

As minimum feature size keeps shrinking, and the next generation lithography (e.g, EUV) further delays, double patterning lithography (DPL) has been widely recognized as a feasible lithography solution in 20nm technology node. However, as technology continues to scale to 14/10nm, DPL begins to show its limitations and usually generates too many undesirable stitches. Triple patterning lithography (TPL) is a natural extension of DPL to conquer the difficulties and achieve a stitch-free layout decomposition. In this paper, we study the standard cell based row-structure layout decomposition problem in TPL. Although the general TPL layout decomposition problem is NP-hard, in this paper we will show that for standard cell based TPL layout decomposition problem, it is polynomial time solvable. We propose a polynomial time algorithm to solve the problem optimally and our approach has the capability to find all stitch-free decompositions. Color balancing is also considered to ensure a balanced triple patterning decomposition. To speed up the algorithm, we further propose a hierarchical algorithm for standard cell based layout, which can reduce the run time by 34.5% on average without sacrificing the optimality. We also extend our algorithm to allow stitches for complex circuit designs, and our algorithm guarantees to find optimal solutions with minimum number of stitches.

A polynomial time triple patterning algorithm for cell based row-structure layout

In today's system-on-chip designs, both digital and analog parts of a circuit will be implemented on the same chip. Parasitic mismatch induced by layout will affect circuit performance significantly for analog designs. Consideration of symmetry and common centroid constraints during placement can help to reduce these errors. Besides these two specific types of placement constraints, other constraints, such as alignment, abutment, preplace, and maximum separation, are also essential in circuit placement. In this paper, we will present a placement methodology that can handle all these constraints at the same time. To the best of our knowledge, this is the first piece of work that can handle symmetry constraint, common centroid constraint, and other general placement constraints, simultaneously. Experimental results do confirm the effectiveness and scalability of our approach in solving this mixed constraint-driven placement problem.

/pdf/simultaneous-handling-of-symmetry-common-centroid-and-47vf02k7zl.pdf

Simultaneous Handling of Symmetry, Common Centroid, and General Placement Constraints

At the 10 nm technology node, the contact layers of integrated circuits (IC) designs are too dense to be printed by single exposure using 193 nm immersion (193i) lithography. Among all the emerging patterning approaches, block copolymer directed self-assembly (DSA) is a promising candidate with high throughput and low cost for sub-20 nm features. Traditionally, the study of DSA has focused on achieving periodic regular patterns over large area. Realizing that long range order is not needed for patterning irregularly distributed contact holes, we use topographical guiding templates to alter the natural symmetry of block copolymer and achieve controlled irregular DSA patterns. However, DSA patterning must satisfy the overlay accuracy requirements while the guiding templates also need to be printable by conventional lithography. This presents a unique opportunity of DSA patterning and layout design co-optimization for improving the manufacturability of DSA. This paper discusses the DSA-aware contact layer optimization problem for 10 nm 1D standard cell library. For the first time we propose a cost function for each DSA template based on its overlay accuracy performance. Then given a standard cell library, we simultaneously optimize the layouts of every cell, such that the contact layer of any cell in the library can be fully patterned by a set of guiding templates, and the total cost of the templates is minimal. This optimization problem is first proved to be NP-hard and formulated as a Weighted Partial Maximum Satisfiability (MAX-SAT) problem, which can be optimally solved with a public SAT solver. Then we propose a bounded approximation algorithm that solves the problem much more efficiently. The experimental results demonstrate that our approach is remarkably promising in practice and validate the proposed optimization problem.

Block copolymer directed self-assembly (DSA) aware contact layer optimization for 10 nm 1D standard cell library

As technology continues to scale to 14nm node, Double Patterning Lithography (DPL) is pushed to near its limit. Triple Patterning Lithography (TPL) is a considerable and natural extension along the paradigm of DPL. With an extra mask to accommodate the features, TPL can be used to eliminate the unresolvable conflicts and minimize the number of stitches, which are pervasive in DPL process, and thus smoothen the layout decomposition step. Considering TPL during routing stage explores a larger solution space and can further improve the layout decomposability. In this paper, we propose the first triple patterning aware detailed routing scheme, and compare its performance with the double patterning version in 14nm node. Experimental results show that, using TPL, the conflicts can be resolved much more easily and the stitches can be significantly reduced in contrast to DPL.

Qiang Ma

Papers

Increased intratumoral mast cells foster immune suppression and gastric cancer progression through TNF-α-PD-L1 pathway.

A polynomial time triple patterning algorithm for cell based row-structure layout

Simultaneous Handling of Symmetry, Common Centroid, and General Placement Constraints

Block copolymer directed self-assembly (DSA) aware contact layer optimization for 10 nm 1D standard cell library

Triple patterning aware routing and its comparison with double patterning aware routing in 14nm technology