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Mutations in KRAS, NRAS, and BRAF (RAS/BRAF) genes are the main predictive biomarkers for the response to anti-EGFR monoclonal antibodies (MAbs) targeted therapy in metastatic colorectal cancer (mCRC). This retrospective study aimed to report the mutational status prevalence of these genes, explore their possible associations with clinicopathological features, and build and validate a predictive model. To achieve these objectives, 500 mCRC Mexican patients were screened for clinically relevant mutations in RAS/BRAF genes. Fifty-two percent of these specimens harbored clinically relevant mutations in at least one screened gene. Among these, 86% had a mutation in KRAS, 7% in NRAS, 6% in BRAF, and 2% in both NRAS and BRAF. Only tumor location in the proximal colon exhibited a significant correlation with KRAS and BRAF mutational status (p-value = 0.0414 and 0.0065, respectively). Further t-SNE analyses were made to 191 specimens to reveal patterns among patients with clinical parameters and KRAS mutational status. Then, directed by the results from classical statistical tests and t-SNE analysis, neural network models utilized entity embeddings to learn patterns and build predictive models using a minimal number of trainable parameters. This study could be the first step in the prediction for RAS/BRAF mutational status from tumoral features and could lead the way to a more detailed and more diverse dataset that could benefit from machine learning methods.

Two-component systems (TCS) are signaling machinery that consist of a histidine kinases (HK) and response regulator (RR). When an environmental change is detected, the HK phosphorylates its cognate response regulator (RR). While cognate interactions were considered orthogonal, experimental evidence shows the prevalence of crosstalk interactions between non-cognate HK–RR pairs. Currently, crosstalk interactions have been demonstrated for TCS proteins in a limited number of organisms. By providing specificity predictions across entire TCS networks for a large variety of organisms, the ELIHKSIR web server assists users in identifying interactions for TCS proteins and their mutants. To generate specificity scores, a global probabilistic model was used to identify interfacial couplings and local fields from sequence information. These couplings and local fields were then used to construct Hamiltonian scores for positions with encoded specificity, resulting in the specificity score. These methods were applied to 6676 organisms available on the ELIHKSIR web server. Due to the ability to mutate proteins and display the resulting network changes, there are nearly endless combinations of TCS networks to analyze using ELIHKSIR. The functionality of ELIHKSIR allows users to perform a variety of TCS network analyses and visualizations to support TCS research efforts.

Aberrant T-cell function is implicated in the pathogenesis of myelodysplastic syndrome (MDS). Monitoring the T-cell receptor (TCR) repertoire can provide insights into T-cell adaptive immunity. Previous studies found skewed TCR repertoires in MDS compared to healthy patients; however these studies that leverage mRNA-based spectratyping have limitations. Furthermore, evaluating the TCR repertoire in context of hypomethylating agents (HMAs) treatment can provide insights into the dynamics of T-cell mediated responses in MDS. We conducted immunosequencing of the CDR3 regions of TCRβ chains in bone marrows of 11 MDS patients prior to treatment (n=11 bone marrows prior to treatment), and in at least 2 timepoints for each patient following treatment (n=26 bone marrow aspirates post-treatment) with (HMA), alongside analyzing bone marrows from 4 healthy donors as controls. TCR repertoires in MDS patients were more clonal and less diverse than healthy donors. However, unlike previous reports, we did not observe significant skewness in CDR3 length or spectratyping. The global metrics of TCR profiling including richness, clonality, overlaps were not significantly changed in responders or non-responders following treatment with HMAs. However, we found an emergence of novel clonotypes in MDS patients who responded to treatment, while non-responders had a higher frequency of contracted clonotypes following treatment. By applying GLIPH2 for antigen prediction, we found rare TCR specificity clusters shared by TCR clonotypes from different patients at pre- or following treatment. Our data show clear differences in TCR repertoires of MDS compared with healthy patients and that novel TCR clonotype emergence in response to HMA therapy was correlated with response. This suggests that response to HMA therapy may be partially driven by T-cell mediated immunity and that the immune-based therapies, which target the adaptive immune system, may play a significant role in select patients with MDS.

Background Tumour-associated macrophages (TAMs) play an important role in the growth, progression, and metastasis of tumours. Epithelial-mesenchymal transition (EMT) is a mechanism for tumour invasion and metastasis. In this study, we aimed to determine whether TAMs can induce EMT for the invasion and metastasis of Kazakh oesophageal squamous cell cancer (ESCC). Methods CD163 was used as a marker for TAMs, and the density of TAMs in tumour nest and surrounding stroma was quantified using immunohistochemistry (IHC). IHC staining was used to evaluate the expression of E-cadherin (epithelial marker) and vimentin (mesenchymal marker) in Kazakh ESCC and cancer-adjacent normal tissues (CANs). Additionally, 6-well transwell plates (0.4 μm) were used to establish the co-culture system of ESCC (EC109 or EC9706) cells and macrophages. Real-time quantitative polymerase chain reaction (qPCR) and western blot experiments were used to determine whether ESCC cells undergo EMT transformation after co-culture with macrophages. Transwell assays were used to detect the migration and invasion of the ESCC cells. Results The distribution of CD163-positive TAMs in cancer tissues was closely related to EMT in Kazakh ESCC. The expression of vimentin in the ESCC cells was significantly upregulated, the expression of E-cadherin was significantly downregulated, and the invasion and migration of the ESCC cells were significantly enhanced after tumour-associated macrophages were added to the co-culture. Conclusions Tumour-associated macrophages promote EMT in ESCC, which may be one of the important factors involved in the invasion and progression of Kazakh ESCC.

BackgroundThe need for a concise and objective immune-specific gene set database is crucial in the era of immune checkpoint blockade (ICB) and adoptive cell cancer (ACT) treatments. It is essential for immunologists to understand treatment mechanisms, molecular distinctions between responders and non-responders, and drivers underlying better survival. However, the current lack of such gene sets hampers immunological research, as existing immune pathway databases are limited and carelessly exploited. Objectively constructed and immunologically relevant pathways provide immunologists with unbiased enrichment results and greater clinical interpretability.MethodsWe collected 83 Bulk-RNAseq datasets from the Molecular Signature Database C7. These datasets contain samples challenged with infections of different kinds and magnitudes, possessing yet-to-be discovered immune functions that lie beneath the transcriptomic profiles. Using non-negative matrix factorization (NMF), we identified gene sets with coordinated expression, curated robust NMF programs and merged into meta programs based on Jaccard metric. We validated the clinical utilities of these gene sets with Cancer Genome Atlas Program (TCGA) pan-cancer, a melanoma ICB cohort and a 10X Genomics Visium FFPE Human Breast Cancer spatial slide.Results19 lymphoid and 9 myeloid novel gene sets were constructed (table 1), describing diverse range of immune functions. We confirmed their functions with relevant single cell RNA and T cell receptor sequencing data. These gene sets not only recovered the TCGA immune subtypes (figure 1A) but also defined a novel immune-microenvironment subtype (figure 2) with lowest aneuploidy, TCR diversity, and neoantigen loads but significantly preferable survival (figure 1C,D). These gene sets also provided better discriminatory power for ICB response (figure 1E) and alluded that ICB non-response is pre-destined with high activities in these gene sets at baseline, suggesting possible T cell exhaustion that is irreversible by ICB (figure 1F,G). A risk score derived from these gene sets has better prognostic power in TCGA survival data (figure 1H). Lastly, these gene sets accurately delineate the tumor-immune boundaries in the H&E sections in breast cancer spatial data (tables 1 and 2).ConclusionsThe translational utilities of these gene sets in diverse cancer contexts are promising, as gene sets were derived mainly from sepsis experiments, suggesting similarities in immune microenvironment between cancerous and sepsis conditions, assuring the wide applicability of these gene sets in cancer research across various domains. Through the study of gene set activities, immunologists can better understand the immune microenvironment, the drivers behind cancer survival, dissect the ICB treatment mechanism and potentially overcome therapeutic resistance.Abstract 1289 Table 1Annotations for the 9 Myeloid-derived gene sets and 19 Lymphoid-derived gene setsAbstract 1289 Table 2Classification accuracy achieved by using different levels of informationAbstract 1289 Figure 1Translational Implications of these gene sets. (A) Single sample gene set enrichment scores calculated for each TCGA sample across cancer types can well cluster the samples into immunologically quiet, inflammatory, and wound healing/lFN-gamma dominant subtypes. (B) Six clusters were identified by performing kmeans clustering algorithm, cluster 2 (yellow) is a combination of a portion of inflammatory samples all immunologically quiet samples. (C) TCGA signatures stratified by 6 clusters show that cluster 2 has lower aneuploidy score, neoantigen load and intratumor heterogeneity. (D) Kaplan Meier plot with survival curves for different kmeans clusters shows that cluster 2 has significantly better survival in comparison to the rest of the clusters (Log-Rank Test p-value < 0.0001). (E) ROC for ICB response classification accuracy. (F) ICB cohort: comparing gene sets activity levels at different treatment timepoints and for patients with different responding status (PD: Progressive Disease; SD: Stable Disease; CR: Complete Response; PR: Partial Response). (G) Comparing T cell exhaustion signature at baseline between responders (PR+CR) and non-responders (SD+PD). (H) The risk score derived from COX LASSO model separates TCGA patients into 4 percentiles groups with significantly different survival outcomes regardless of cancer types.Abstract 1289 Figure 2Gene sets can well cluster spatial-omics data. The top panel shows a H&E section for breast cancer tumor sample with pathologist annotation (purple: immune spots; green: tumor spots). The bottom panel shows the expression level of three example gene sets (TCR Anchoring, Cell Killing, and Cytokine Signaling Pathway) across the spatial spots

Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either “Unknown” or “Potentially” actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable ( N  = 204) were more likely to be oncogenic than those categorized as Unknown ( N  = 230) (37% vs 13%, p  = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.

Cell–substrate interaction is important in tissue engineering. Vascular smooth muscle cells (VSMCs) cultured on the microgrooved surface of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHHx) showed a distinctive polarized morphology and a high expression level of let-7a compared with the flat substrates. LIMK2, a crucial regulator of actin dynamics, was identified as a new target of let-7a. F-Actin content on flat substrates was significantly higher than that on microgrooved ones. Either overexpression of let-7a on flat substrates or inhibited expression on microgrooved substrates can rescue the difference. In accord with actin dynamics, the expressions of contractile smooth muscle markers, such as SM22 and SMA, decreased in VSMCs cultured on microgrooved substrates compared to those on flat ones, though PHBHHx can induce the synthetic-to-contractile phenotype shift. These results indicate that microgrooved PHBHHx could enhance actin dynamics of VSMCs through let-7a-involved regulation and trigger a synthetic shift.

Richter’s Syndrome (RS) is an aggressive transformation of CLL, usually clonally-related diffuse large B-cell lymphoma (DLBCL), characterized by frequent TP53 mutations, intrinsic chemoresistance and poor survival. TP53-independent treatments are needed. We conducted a single center, phase 2, investigator-initiated study of high dose blinatumomab (maximum 112 mcg/d after initial, weekly dose escalation), NCT03121534, given for an 8-week induction and 4-week consolidation cycle. Responses were assessed by Lugano 2014 criteria. Serial multi-parameter flow cytometry from blood was performed to identify patient-specific biomarkers for response. Nine patients were treated. Patients had received a median of 4 and 2 prior therapies for CLL and RS, respectively. Five of 9 had del(17p) and 100% had complex karyotype. Four patients had reduction in nodal disease, including one durable complete response lasting >1 y. Treatment was well tolerated, with no grade >3 cytokine release syndrome and 1 case of grade 3, reversible neurotoxicity. Immunophenotyping demonstrated the majority of patients expressed multiple immune checkpoints, especially PD1, TIM3 and TIGIT. The patient who achieved CR had the lowest levels of immune checkpoint expression. Simultaneous targeting with immune checkpoint blockade, especially PD1 inhibition, which has already demonstrated single-agent efficacy in RS, could achieve synergistic killing and enhance outcomes.

Coevolution plays a fundamental role in determining folding, structure, interactions and functionality of proteins. Structural or functional related residues coevolve during the evolutionary history to maintain similar structures, interactions and functional properties among the same protein families. Direct coupling models for coevolutionary analysis have demonstrated outstanding performances in predicting contacting residues of proteins and thereby have commonly used to predict protein structures and interactions. In this dissertation, a global statistical inference framework, direct coupling analysis (DCA) was used to infer coevolutionary couplings in datasets including protein-protein interactions and protein modular-modular compatibility. The couplings were then used to build different computational models, i.e. a Hamiltonian energy function H(S) and compatibility score C(S). The Hamiltonian energy function successfully predicts the specificity strength of protein-protein interactions in two component systems and proposed a novel cross-talk model between different sets of two-component system (TCS), VanRS and CroRS, to explain strain specific antibiotic phenotypes in Enterococcus faecalis. On the other hand, the C(S) score predicts the compatibility between two protein subdomains in terms of allosteric communication and function between DNA-binding and ligand-binding modules originated from different proteins in the LacI protein family. This model facilitates screening out functional hybrids from different LacI homologs used to engineer and rewire the connection between signal sensing and genetic output. The compatibility score is also able to predict the mutational effect for hybrid proteins, aiming to improve the functionality of a hybrid protein. Moreover, the application of DCA framework was extended into nonsequence datasets, including pharmacogenomics and clinicopathological data, for the first time. The study has demonstrated that direct coupling approach could capture important connectivities between gene mutations and drug responses, as well as between different clinicopathological features. The direct coupling approach provides new means in pharmacogenomics and clinicopathological data analysis and thereby offers new insights in personalized medicine.

BackgroundThe use of immune checkpoint inhibitors (ICIs) has led to a paradigm change in cancer management. Many patients may have inherent primary resistance to ICIs or develop secondary resistance after initial response. The impact of using novel therapeutic combinations of checkpoint blockade (avelumab) with immune stimulating agonists such as anti-OX40 and/or anti-4-1BB on the tumor microenvironment and modulation of the immune response is an intriguing strategy to evaluate how these agents interact and whether the hypothetical rationale for combinations can be translated into augmentation of anti-tumor immunity in solid tumors.MethodsWe performed whole exome sequencing (WES), bulk RNAseq, multiplex immunofluorescence (mIF) and chromogenic assay immunohistochemistry (IHC) on tumor tissue and flow cytometry of the peripheral blood to study changes between post and pre-treatment longitudinal changes following the combination of avelumab with utomilumab (a 4-1BB agonist) (arm A), PF-04518600 (an OX40 agonist) (arm B), utomilumab and PF-04518600 (arm C) and utomilumab and radiotherapy (arm D) in phase I/II study (NCT03217747). Wilcoxon signed rank test was applied.ResultsWe observed low tumor mutation burden (TMB<6) (median: 1.88), alteration of RTK-RAS, TP53, PI3K and WNT pathways across the cohorts. Mutations in TP53, TTN and KRAS (mostly p.G12C, p.G12D) genes and copy number variations (CNV) were found in PIK3CA, CCNE1 and KRAS. Interferon gamma signaling pathway was only enriched early on-treatment after immune stimulating agonists in tumors from patients with colorectal and pancreatic cancers with in arm C. Patients deriving clinical benefit (CR/PR/SD≥4 months) displayed higher T- cell lymphocytes frequencies at baseline (p=0.0157), C1D15 (p=0.0086), and C3D15 (p=0.0070) than patients without clinical benefit in mIF data.ConclusionsOur findings, though limited, highlight genomic differences between histologic subsets and outcome as well as the need for combination strategies that drive the recruitment and/or priming of anti-tumor T cells and address low immune permissive tumor states in patients with advanced solid tumors.Trial RegistrationNCT03217747AcknowledgementsThe study was financially supported by Pfizer as part of a previous alliance between Pfizer and the healthcare business of Merck KGaA, Darmstadt, Germany (CrossRef Funder ID:10.13039/100009945)Ethics ApprovalThe study was approved by the institutional review board at The University of Texas MD Anderson Cancer Center.