Blinatumomab maintenance after allogeneic hematopoietic cell transplantation for B-lineage acute lymphoblastic leukemia.

Patients with B-lineage acute lymphoblastic leukemia (ALL) are at high-risk for relapse after allogeneic hematopoietic cell transplantation (HCT). We conducted a single-center phase 2 study evaluating the feasibility of 4 cycles of blinatumomab administered every 3 months during the first year after HCT in an effort to mitigate relapse in high-risk ALL patients. Twenty-one of 23 enrolled patients received at least 1 cycle of blinatumomab and were included in the analysis. The median time from HCT to the first cycle of blinatumomab was 78 days (range, 44 to 105). Twelve patients (57%) completed all 4 treatment cycles. Neutropenia was the only grade 4 adverse event (19%). Rates of cytokine release (5% G1) and neurotoxicity (5% G2) were minimal. The cumulative incidence of acute graft-versus-host disease (GVHD) grades 2 to 4 and 3 to 4 were 33% and 5%, respectively; 2 cases of mild (10%) and 1 case of moderate (5%) chronic GVHD were noted. With a median follow-up of 14.3 months, the 1-year overall survival (OS), progression-free survival (PFS), and nonrelapse mortality (NRM) rates were 85%, 71%, and 0%, respectively. In a matched analysis with a contemporary cohort of 57 patients, we found no significant difference between groups regarding blinatumomab's efficacy. Correlative studies of baseline and posttreatment samples identified patients with specific T-cell profiles as "responders" or "nonresponders" to therapy. Responders had higher proportions of effector memory CD8 T-cell subsets. Nonresponders were T-cell deficient and expressed more inhibitory checkpoint molecules, including T-cell immunoglobulin and mucin domain 3 (TIM3). We found that blinatumomab postallogeneic HCT is feasible, and its benefit is dependent on the immune milieu at time of treatment. This paper is posted on ClinicalTrials.gov, study ID: NCT02807883.

Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation.

The prediction of protein mutations that affect function may be exploited for multiple uses. In the context of disease variants, the prediction of compensatory mutations that reestablish functional phenotypes could aid in the development of genetic therapies. In this work, we present an integrated approach that combines coevolutionary analysis and molecular dynamics (MD) simulations to discover functional compensatory mutations. This approach is employed to investigate possible rescue mutations of a poly(ADP-ribose) polymerase 1 (PARP1) variant, PARP1 V762A, associated with lung cancer and follicular lymphoma. MD simulations show PARP1 V762A exhibits noticeable changes in structural and dynamical behavior compared with wild-type (WT) PARP1. Our integrated approach predicts A755E as a possible compensatory mutation based on coevolutionary information, and molecular simulations indicate that the PARP1 A755E/V762A double mutant exhibits similar structural and dynamical behavior to WT PARP1. Our methodology can be broadly applied to a large number of systems where single-nucleotide polymorphisms have been identified as connected to disease and can shed light on the biophysical effects of such changes as well as provide a way to discover potential mutants that could restore WT-like functionality. This can, in turn, be further utilized in the design of molecular therapeutics that aim to mimic such compensatory effect.

Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset.

Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior: each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information.

Engineering DNA recognition and allosteric response properties of TetR family proteins by using a module-swapping strategy.

The development of synthetic biological systems requires modular biomolecular components to flexibly alter response pathways. In previous studies, we have established a module-swapping design principle to engineer allosteric response and DNA recognition properties among regulators in the LacI family, in which the engineered regulators served as effective components for implementing new cellular behavior. Here we introduced this protein engineering strategy to two regulators in the TetR family: TetR (UniProt Accession ID: P04483) and MphR (Q9EVJ6). The TetR DNA-binding module and the MphR ligand-binding module were used to create the TetR-MphR. This resulting hybrid regulator possesses DNA-binding properties of TetR and ligand response properties of MphR, which is able to control gene expression in response to a molecular signal in cells. Furthermore, we studied molecular interactions between the TetR DNA-binding module and MphR ligand-binding module by using mutant analysis. Together, we demonstrated that TetR family regulators contain discrete and functional modules that can be used to build biological components with novel properties. This work highlights the utility of rational design as a means of creating modular parts for cell engineering and introduces new possibilities in rewiring cellular response pathways.

ELIHKSIR Web Server: Evolutionary Links Inferred for Histidine Kinase Sensors Interacting with Response Regulators.

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.

Coevolutionary Couplings Unravel PAM-Proximal Constraints of CRISPR-SpCas9.

The clustered regularly interspaced short palindromic repeats (CRISPR) system, an immune system analog found in prokaryotes, allows a single-guide RNA to direct a CRISPR-associated protein (Cas) with combined helicase and nuclease activity to DNA. The presence of a specific protospacer adjacent motif (PAM) next to the DNA target site plays a crucial role in determining both efficacy and specificity of gene editing. Herein, we introduce a coevolutionary framework to computationally unveil nonobvious molecular interactions in CRISPR systems and experimentally probe their functional role. Specifically, we use direct coupling analysis, a statistical inference framework used to infer direct coevolutionary couplings, in the context of protein/nucleic acid interactions. Applied to Streptococcus pyogenes Cas9, a Hamiltonian metric obtained from coevolutionary relationships reveals, to our knowledge, novel PAM-proximal nucleotide preferences at the seventh position of S. pyogenes Cas9 PAM (5'-NGRNNNT-3'), which was experimentally confirmed by in vitro and functional assays in human cells. We show that coevolved and conserved interactions point to specific clues toward rationally engineering new generations of Cas9 systems and may eventually help decipher the diversity of this family of proteins.

Microgrooved poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) affects the phenotype of vascular smooth muscle cells through let-7a-involved regulation of actin dynamics.

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.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Ex Vivo Expanded Cord Blood Natural Killer Cells Combined with Rituximab and High-Dose Chemotherapy and Autologous Stem Cell Transplantation for B Cell Non-Hodgkin Lymphoma.

Relapse is the major cause of failure of high-dose chemotherapy (HDC) with autologous stem cell transplantation (ASCT) for B cell non-Hodgkin lymphomas (B-NHL). Improvement strategies include use in combination with effective immunotherapies. We hypothesized that the combination of rituximab/HDC/ASCT with expanded cord blood (CB)-derived natural killer (NK) cells is safe and active in B-NHL. Patients with B-NHL age 15 to 70 years and appropriate ASCT candidates were eligible for the study. The CB units were selected without considering HLA match with the recipient. The CB NK cells were expanded from day -19 to day -5. Treatment included rituximab on days -13 and -7, BEAM (carmustine/etoposide/cytarabine/melphalan) on days -13 to -7, lenalidomide on days -7 to -2, CB NK infusion (108/kg) on day -5, and ASCT (day 0). The primary endpoint was 30-day treatment-related mortality (TRM); secondary endpoints included relapse-free survival (RFS), overall survival (OS), and persistence of CB NK cells. We enrolled 20 patients. CB NK cells were expanded a median of 1552-fold with >98% purity and >96% viability. We saw no adverse events attributable to the CB NK cells and 0% 30-day TRM. At median follow-up of 47 months, the RFS and OS rates were 53% and 74%, respectively. CB NK cells were detectable in blood for 2 weeks, independent of HLA-mismatch status. CD16 expression in donor NK cells was correlated favorably with outcome, and homozygosity for the high-affinity CD16 variant (158 V/V) in CB, but not recipient, NK cells was correlated with better outcomes. Our data indicate that the combination of expanded and highly purified CB-derived NK cells with HDC/ASCT for B-NHL is safe. CD16 expression in donor NK cells, particularly if homozygous for the high-affinity CD16 variant, was correlated with better outcomes.

CD28 Costimulation Augments CAR Signaling in NK Cells via the LCK/CD3ζ/ZAP70 Signaling Axis.

Multiple factors in the design of a chimeric antigen receptor (CAR) influence CAR T-cell activity, with costimulatory signals being a key component. Yet, the impact of costimulatory domains on the downstream signaling and subsequent functionality of CAR-engineered natural killer (NK) cells remains largely unexplored. Here, we evaluated the impact of various costimulatory domains on CAR-NK cell activity, using a CD70-targeting CAR. We found that CD28, a costimulatory molecule not inherently present in mature NK cells, significantly enhanced the antitumor efficacy and long-term cytotoxicity of CAR-NK cells both in vitro and in multiple xenograft models of hematologic and solid tumors. Mechanistically, we showed that CD28 linked to CD3ζ creates a platform that recruits critical kinases, such as lymphocyte-specific protein tyrosine kinase (LCK) and zeta-chain-associated protein kinase 70 (ZAP70), initiating a signaling cascade that enhances CAR-NK cell function. Our study provides insights into how CD28 costimulation enhances CAR-NK cell function and supports its incorporation in NK-based CARs for cancer immunotherapy. Significance: We demonstrated that incorporation of the T-cell-centric costimulatory molecule CD28, which is normally absent in mature natural killer (NK) cells, into the chimeric antigen receptor (CAR) construct recruits key kinases including lymphocyte-specific protein tyrosine kinase and zeta-chain-associated protein kinase 70 and results in enhanced CAR-NK cell persistence and sustained antitumor cytotoxicity.

An interpretable ML model to characterize patient-specific HLA-I antigen presentation.

Personalized immunotherapy holds the promise of revolutionizing cancer prevention and treatment. However, selecting HLA-bound peptide targets that are specific to patient tumors has been challenging due to a lack of patient-specific antigen presentation models. Here, we present epiNB, a white-box, positive-example-only, semi-supervised method based on Naïve Bayes formulation, with information content-based feature selection, to achieve accurate modeling using Mass Spectrometry data eluted from mono-allelic cell lines and patient-derived cell lines. In addition to achieving state-of-the-art accuracy, epiNB yields novel insights into the structural properties, such as interactions of peptide positions, that appear important for modeling personalized, tumor-specific antigen presentation. epiNB uses substantially less parameters than neural networks, does not require hyperparameter tweaking and can efficiently train and run on our web portal (https://epinbweb.streamlit.app/) or a regular PC/laptop, making it easily applicable in translational settings.

Actionability classification of variants of unknown significance correlates with functional effect.

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.

Ponatinib and blinatumomab for Philadelphia chromosome-positive acute lymphoblastic leukaemia: a US, single-centre, single-arm, phase 2 trial.

BACKGROUND: Ponatinib and blinatumomab are effective therapies in patients with Philadelphia chromosome-positive (Ph-positive) acute lymphoblastic leukaemia, and their combination might be a promising treatment option. In this study, we aimed to evaluate this chemotherapy-free strategy. METHODS: We did a single-centre, single-arm, phase 2 study at the University of Texas MD Anderson Cancer Center, Houston, TX, USA, in patients aged 18 years or older with newly diagnosed or relapsed or refractory Ph-positive acute lymphoblastic leukaemia or chronic myeloid leukaemia in lymphoid blast phase. Patients with an ECOG performance status of 2 or less who had a total bilirubin concentration two-times the upper limit of normal (ULN) or less (≤2·4 mg/dL), alanine aminotransferase and aspartate aminotransferase concentration no more than three-times the ULN, and serum lipase and amylase concentrations no more than three-times the ULN were eligible for inclusion. Ponatinib 30 mg orally and continuous intravenous blinatumomab 28 µg over 24 h (for 28 days each cycle) were given in combination for up to five 42-day cycles, followed by ponatinib monotherapy. Patients received 12 doses of intrathecal chemotherapy as CNS prophylaxis. The primary endpoints were complete molecular response (defined as absence of a detectable BCR-ABL1 transcript by PCR at a sensitivity of 0·01%) in patients with newly diagnosed disease and overall response in patients with relapsed or refractory disease or chronic myeloid leukaemia in lymphoid blast phase. All assessments were done according to the intention-to-treat principle. The trial completed its original target accrual and was amended on March 23, 2022, to enrol an additional 30 patients, thus increasing the sample size to 90 patients. The trial is registered with ClinicalTrials.gov, NCT03263572, and it is ongoing. FINDINGS: Between Feb 6, 2018, to May 6, 2022, 60 (83%) of 72 patients assessed were enrolled and received ponatinib and blinatumomab (40 [67%] patients had newly diagnosed Ph-positive acute lymphoblastic leukaemia, 14 [23%] had relapsed or refractory Ph-positive acute lymphoblastic leukaemia, and six [10%] had chronic myeloid leukaemia in lymphoid blast phase). 32 (53%) patients were men and 28 (47%) were women; 51 (85%) patients were White or Hispanic; and the median age of participants was 51 years (IQR 36-68). The median duration of follow-up for the entire cohort was 16 months (IQR 11-24). Of patients with newly diagnosed Ph-positive acute lymphoblastic leukaemia, 33 (87%) of 38 evaluable patients had a complete molecular response. 12 (92%) of 13 evaluable patients with relapsed or refractory Ph-positive acute lymphoblastic leukaemia had an overall response. 11 (79%) had a complete molecular response. Five (83%) of six patients with chronic myeloid leukaemia in lymphoid blast phase had an overall response. Two (33%) had a complete molecular response. The most common grade 3-4 adverse events that occurred in more than 5% of patients were infection (22 [37%] patients), increased amylase or lipase concentration (five [8%] patients), increased alanine aminotransferase or aspartate aminotransferase concentration (four [7%] patients), pain (four [7%] patients), and hypertension (four [7%] patients). One (2%) patient discontinued blinatumomab due to tremor. Three (5%) patients discontinued ponatinib secondary to cerebrovascular ischaemia, portal vein thrombosis, and coronary artery stenosis in one patient each. No treatment-related deaths were observed. INTERPRETATION: The chemotherapy-free combination of ponatinib and blinatumomab resulted in high rates of complete molecular response in patients with newly diagnosed and relapsed or refractory Ph-positive acute lymphoblastic leukaemia. Patients with newly diagnosed Ph-positive acute lymphoblastic leukaemia could be spared the toxicities associated with chemotherapy and the need for allogeneic haematopoietic stem-cell transplantation in first response. FUNDING: Takeda Oncology and Amgen.

A phase two study of high dose blinatumomab in Richter's syndrome.

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.

Clinical and Molecular Characterization of POLE Mutations as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors in Advanced Cancers.

PURPOSE: DNA polymerase epsilon is critical to DNA proofreading and replication. Mutations in POLE have been associated with hypermutated tumors and antitumor response to immune checkpoint inhibitor (ICI) therapy. We present a clinicopathologic analysis of patients with advanced cancers harboring POLE mutations, the pattern of co-occurring mutations, and their response to ICI therapy within the context of mutation pathogenicity. METHODS: We conducted a retrospective analysis of next-generation sequencing data at MD Anderson Cancer Center to identify patient tumors with POLE mutations and their co-occurring mutations. The pathogenicity of each mutation was annotated using InterVar and ClinVar. Differences in therapeutic response to ICI, survival, and co-occurring mutations were reported by POLE pathogenicity status. RESULTS: Four hundred fifty-eight patient tumors with POLE mutations were identified from 14,229 next-generation sequencing reports; 15.0% of POLE mutations were pathogenic, 15.9% benign, and 69.1% variant of unknown significance. Eighty-two patients received either programmed death 1 or programmed death ligand-1 inhibitors as monotherapy or in combination with cytotoxic T-cell lymphocyte-4 inhibitors. Patients with pathogenic POLE mutations had improved clinical benefit rate (82.4% v 30.0%; P = .013), median progression-free survival (15.1 v 2.2 months; P < .001), overall survival (29.5 v 6.8 months; P < .001), and longer treatment duration (median 15.5 v 2.5 months; P < .001) compared to those with benign variants. Progression-free survival and overall survival remained superior when adjusting for number of co-occurring mutations (≥ 10 v < 10) and/or microsatellite instability status (proficient mismatch repair v deficient mismatch repair). The number of comutations was not associated with response to ICI (clinical benefit v progressive disease: median 13 v 11 comutations; P = .18). CONCLUSION: Pathogenic POLE mutations were associated with clinical benefit to ICI therapy. Further studies are warranted to validate POLE mutation as a predictive biomarker of ICI therapy.

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions.

Genetic sensors with unique combinations of DNA recognition and allosteric response can be created by hybridizing DNA-binding modules (DBMs) and ligand-binding modules (LBMs) from distinct transcriptional repressors. This module swapping approach is limited by incompatibility between DBMs and LBMs from different proteins, due to the loss of critical module-module interactions after hybridization. We determine a design strategy for restoring key interactions between DBMs and LBMs by using a computational model informed by coevolutionary traits in the LacI family. This model predicts the influence of proposed mutations on protein structure and function, quantifying the feasibility of each mutation for rescuing hybrid repressors. We accurately predict which hybrid repressors can be rescued by mutating residues to reinstall relevant module-module interactions. Experimental results confirm that dynamic ranges of gene expression induction were improved significantly in these mutants. This approach enhances the molecular and mechanistic understanding of LacI family proteins, and advances the ability to design modular genetic parts.

Response to Hypomethylating Agents in Myelodysplastic Syndrome Is Associated With Emergence of Novel TCR Clonotypes.

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 TCRß 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.

KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study.

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.

Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations.

The analysis of coevolutionary signals from families of evolutionarily related sequences is a recent conceptual framework that provides valuable information about unique intramolecular interactions and, therefore, can assist in the elucidation of biomolecular conformations. It is based on the idea that compensatory mutations at specific residue positions in a sequence help preserve stability of protein architecture and function and leave a statistical signature related to residue-residue interactions in the 3D structure of the protein. Consequently, statistical analysis of these correlated mutations in subsets of protein sequence alignments can be used to predict which residue pairs should be in spatial proximity in the native functional protein fold. These predicted signals can be then used to guide molecular dynamics (MD) simulations to predict the three-dimensional coordinates of a functional amino acid chain. In this chapter, we introduce a general and efficient methodology to perform coevolutionary analysis on protein sequences and to use this information in combination with computational physical models to predict the native 3D conformation of functional polypeptides. We present a step-by-step methodology that includes the description and application of software tools and databases required to infer tertiary structures of a protein fold. The general pipeline includes instructions on (1) how to obtain direct amino acid couplings from protein sequences using direct coupling analysis (DCA), (2) how to incorporate such signals as interaction potentials in Cα structure-based models (SBMs) to drive protein-folding MD simulations, (3) a procedure to estimate secondary structure and how to include such estimates in the topology files required in the MD simulations, and (4) how to build full atomic models based on the top Cα candidates selected in the pipeline. The information presented in this chapter is self-contained and sufficient to allow a computational scientist to predict structures of proteins using publicly available algorithms and databases.