Unlocking cancer vaccine potential: What are the key factors?

Cancer is a global health challenge, with changing demographics and lifestyle factors producing an increasing burden worldwide. Screening advancements are enabling earlier diagnoses, but current cancer immunotherapies only induce remission in a small proportion of patients and come at a high cost. Cancer vaccines may offer a solution to these challenges, but they have been mired by poor results in past decades. Greater understanding of tumor biology, coupled with the success of vaccine technologies during the COVID-19 pandemic, has reinvigorated cancer vaccine development. With the first signs of efficacy being reported, cancer vaccines may be beginning to fulfill their potential. Solid tumors, however, present different hurdles than infectious diseases. Combining insights from previous cancer vaccine clinical development and contemporary knowledge of tumor immunology, we ask: who are the 'right' patients, what are the 'right' targets, and which are the 'right' modalities to maximize the chances of cancer vaccine success?

Combining Chemical Protein Synthesis and Random Nonstandard Peptides Integrated Discovery for Modulating Biological Processes.

Chemical manipulation of naturally occurring peptides offers a convenient route for generating analogs to screen against different therapeutic targets. However, the limited success of the conventional chemical libraries has urged chemical biologists to adopt alternative methods such as phage and mRNA displays and create libraries of a large number of variants for the screening and selection of novel peptides. Messenger RNA (mRNA) display provides great advantages in terms of the library size and the straightforward recovery of the selected polypeptide sequences. Importantly, the integration of the flexible in vitro translation (FIT) system with the mRNA display provides the basis of the random nonstandard peptides integrated discovery (RaPID) approach for the introduction of diverse nonstandard motifs, such as unnatural side chains and backbone modifications. This platform allows the discovery of functionalized peptides with tight binding against virtually any protein of interest (POI) and therefore shows great potential in the pharmaceutical industry. However, this method has been limited to targets generated by recombinant expression, excluding its applications to uniquely modified proteins, particularly those with post-translational modifications.Chemical protein synthesis allows a wide range of changes to the protein's chemical composition to be performed, including side chain and backbone modifications and access to post-translationally modified proteins, which are often inaccessible or difficult to achieve via recombinant expression methods. Notably, d-proteins can be prepared via chemical synthesis, which has been used in mirror image phase display for the discovery of nonproteolytic d-peptide binders.Combining chemical protein synthesis with the RaPID system allows the production of a library of trillions of cyclic peptides and subsequent selection for novel cyclic peptide binders targeting a uniquely modified protein to assist in studying its unexplored biology and possibly the discovery of new drug candidates.Interestingly, the small post-translational modifier protein ubiquitin (Ub), with its various polymeric forms, regulates directly or indirectly many biochemical processes, e.g., proteasomal degradation, DNA damage repair, cell cycle regulation, etc. In this Account, we discuss combining the RaPID approach against various synthetic Ub chains for selecting effective and specific macrocyclic peptide binders. This offers an advancement in modulating central Ub pathways and provides opportunities in drug discovery areas associated with Ub signaling. We highlight experimental approaches and conceptual adaptations required to design and modulate the activity of Lys48- and Lys63-linked Ub chains by macrocyclic peptides. We also present the applications of these approaches to shed light on related biological activities and ultimately their activity against cancer. Finally, we contemplate future developments still pending in this exciting multidisciplinary field.

Selective macrocyclic peptide modulators of Lys63-linked ubiquitin chains disrupt DNA damage repair.

Developing an effective binder for a specific ubiquitin (Ub) chain is a promising approach for modulating various biological processes with potential applications in drug discovery. Here, we combine the Random Non-standard Peptides Integrated Discovery (RaPID) method and chemical protein synthesis to screen an extended library of macrocyclic peptides against synthetic Lys63-linked Di-Ub to discover a specific binder for this Ub chain. Furthermore, next-generation binders are generated by chemical modifications. We show that our potent cyclic peptide is cell-permeable, and inhibits DNA damage repair, leading to apoptotic cell death. Concordantly, a pulldown experiment with the biotinylated analog of our lead cyclic peptide supports our findings. Collectively, we establish a powerful strategy for selective inhibition of protein-protein interactions associated with Lys63-linked Di-Ub using cyclic peptides. This study offers an advancement in modulating central Ub pathways and provides opportunities in drug discovery areas associated with Ub signaling.

Structure-Uptake Relationship Study of DABCYL Derivatives Linked to Cyclic Cell-Penetrating Peptides for Live-Cell Delivery of Synthetic Proteins.

Modifying cyclic cell-penetrating deca-arginine (cR10) peptides with 4-(4-dimethylaminophenylazo)benzoic acid (DABCYL) improves the uptake efficiency of synthetic ubiquitin (Ub) cargoes into living cells. To probe the role of the DABCYL moiety, we performed time-lapse microscopy and fluorescence lifetime imaging microscopy (FLIM) of fluorescent DABCYL-R10 to evaluate the impact on cell entry by the formation of nucleation zones. Furthermore, we performed a structure-uptake relationship study with 13 DABCYL derivatives coupled to CPP to examine their effect on the cell-uptake efficiency when conjugated to mono-Ub through disulfide linkages. Our results show that through structure variations of the DABCYL moiety alone we could reach, at nanomolar concentration, an additional threefold increase in the cytosolic delivery of Ub, which will enable studies on various intracellular processes related to Ub signaling.

Evaporation dynamics of a surrogate respiratory droplet in a vortical environment.

HYPOTHESIS: Vortex droplet interaction is crucial for understanding the route of disease transmission through expiratory jet where several such embedded droplets continuously interact with vortical structures of different strengths and sizes. EXPERIMENTS: A train of vortex rings with different vortex strength, quantified with vortex Reynolds number (Re'=0,53,221,297) are made to interact with an isolated levitated droplet, and the evolution dynamics is captured using shadowgraphy, particle image velocimetry (PIV), and backlight imaging technique. NaCl-DI water solution of 0, 1, 10 and 20 wt% concentrations are used as test fluids for the droplet. FINDINGS: The results show the dependence of evaporation characteristics on vortex strength, while the crystallization dynamics was found to be independent of it. A reduction of 12.23% and 14.6% in evaporation time was seen in case of de-ionized (DI) water and 1% wt NaCl solution respectively in presence of vortex ring train at Re'=221. In contrast to this, a minimal reduction in evaporation time (0.6% and 0.9% for DI water and 1% wt NaCl solution, respectively) is observed when Re' is increased from 221 to 297. The mechanisms for evaporation time reduction due to enhancement of convective heat and mass transfer from the droplet and shearing away of vapor layer by vortex ring interaction are discussed in this work.

Neural ODE to model and prognose thermoacoustic instability.

Thermoacoustic instability in a reacting flow field is characterized by high amplitude pressure fluctuations driven by a positive coupling between the unsteady heat release rate and the acoustic field of the combustor. In a turbulent flow, the transition of a thermoacoustic system from a state of chaos to periodic oscillations occurs via a state of intermittency. During the transition to periodic oscillations, the unsteady heat release rate synchronizes with the acoustic pressure fluctuations. Thermoacoustic systems are traditionally modeled by coupling the model for the heat source and the acoustic subsystem, each estimated independently. The response of the unsteady heat source, i.e., the flame, to acoustic fluctuations is characterized by introducing unsteady external forcing. The forced response of the flame need not be the same in the presence of an acoustic field due to their nonlinear coupling. Instead of characterizing individual subsystems, we introduce a neural ordinary differential equation (neural ODE) framework to model the thermoacoustic system as a whole. The neural ODE model for the thermoacoustic system uses time series of the heat release rate and the pressure fluctuations, measured simultaneously without introducing any external perturbations, to model their coupled interaction. Furthermore, we use the parameters of neural ODE to define an anomaly measure that represents the proximity of system dynamics to limit cycle oscillations and thus provide an early warning signal for the onset of thermoacoustic instability.

Two-dimensional mathematical framework for evaporation dynamics of respiratory droplets.

In majority of pandemics in human history, respiratory bio-aerosol is the most common route of transmission of diseases. These tiny droplets ejected through mouth and nose from an infected person during exhalation process like coughing, sneezing, speaking, and breathing consist of pathogens and a complex mixture of volatile and nonvolatile substances. A cloud of droplets ejected in such an event gets transmitted in the air, causing a series of coupled thermo-physical processes. Contemplating an individual airborne droplet in the cloud, boundary layers and wakes develop due to relative motion between the droplet and the ambient air. The complex phenomenon of the droplet's dynamics, such as shear-driven internal circulation of the liquid phase and Stefan flow due to vaporization or condensation, comes into effect. In this study, we present a mathematical description of the coupled subprocesses, including droplet aerodynamics, heat, and mass transfer, which were identified and subsequently solved. The presented two-dimensional model gives a complete analysis encompassing the gas phase coupled with the liquid phase responsible for the airborne droplet kinetics in the ambient environment. The transient inhomogeneity of temperature and concentration distribution in the liquid phase caused due to the convective and diffusive transports are captured in the 2D model. The evaporation time and distance traveled by droplets prior to nuclei or aerosol formation are computed for major geographical locations around the globe for nominal-windy conditions. The model presented can be used for determining the evaporation timescale of any viral or bacterial laden respiratory droplets across any geographical location.

Convolutional neural networks to predict the onset of oscillatory instabilities in turbulent systems.

Many fluid dynamic systems exhibit undesirable oscillatory instabilities due to positive feedback between fluctuations in their different subsystems. Thermoacoustic instability, aeroacoustic instability, and aeroelastic instability are some examples. When the fluid flow in the system is turbulent, the approach to such oscillatory instabilities occurs through a universal route characterized by a dynamical regime known as intermittency. In this paper, we extract the peculiar pattern of phase space attractors during the regime of intermittency by constructing recurrence networks corresponding to the phase space topology. We further train a convolutional neural network to classify the periodic and aperiodic structures in the recurrence networks and define a measure that indicates the proximity of the dynamical state to the onset of oscillatory instability. We show that this measure can predict the onset of oscillatory instabilities in three different fluid dynamic systems governed by different physical phenomena.

An opinion on the multiscale nature of Covid-19 type disease spread.

Recognizing the multiscale, interdisciplinary nature of the Covid-19 transmission dynamics, we discuss some recent developments concerning an attempt to construct a disease spread model from the flow physics of infectious droplets and aerosols and the frequency of contact between susceptible individuals with the infectious aerosol cloud. Such an approach begins with the exhalation event-specific, respiratory droplet size distribution (both airborne/aerosolized and ballistic droplets), followed by tracking its evolution in the exhaled air to estimate the probability of infection and the rate constants of the disease spread model. The basic formulations and structure of submodels, experiments involved to validate those submodels, are discussed. Finally, in the context of preventive measures, respiratory droplet-face mask interactions are described.

Precipitation dynamics of surrogate respiratory sessile droplets leading to possible fomites.

HYPOTHESIS: The droplets ejected from an infected host during expiratory events can get deposited as fomites on everyday use surfaces. Recognizing that these fomites can be a secondary route for disease transmission, exploring the deposition pattern of such sessile respiratory droplets on daily-use substrates thus becomes crucial. EXPERIMENTS: The used surrogate respiratory fluid is composed of a water-based salt-protein solution, and its precipitation dynamics is studied on four different substrates (glass, ceramic, steel, and PET). For tracking the final deposition of viruses in these droplets, 100 nm virus emulating particles (VEP) are used and their distribution in dried-out patterns is identified using fluorescence and SEM imaging techniques. FINDINGS: The final precipitation pattern and VEP deposition strongly depend on the interfacial transport processes, edge evaporation, and crystallization dynamics. A constant contact radius mode of evaporation with a mixture of capillary and Marangoni flows results in spatio-temporally varying edge deposits. Dendritic and cruciform-shaped crystals are majorly seen in all substrates except on steel, where regular cubical crystals are formed. The VEP deposition is higher near the three-phase contact line and crystal surfaces. The results showed the role of interfacial processes in determining the initiation of fomite-type infection pathways in the context of COVID-19.

On secondary atomization and blockage of surrogate cough droplets in single- and multilayer face masks.

Face masks prevent transmission of infectious respiratory diseases by blocking large droplets and aerosols during exhalation or inhalation. While three-layer masks are generally advised, many commonly available or makeshift masks contain single or double layers. Using carefully designed experiments involving high-speed imaging along with physics-based analysis, we show that high-momentum, large-sized (>250 micrometer) surrogate cough droplets can penetrate single- or double-layer mask material to a significant extent. The penetrated droplets can atomize into numerous much smaller (<100 micrometer) droplets, which could remain airborne for a significant time. The possibility of secondary atomization of high-momentum cough droplets by hydrodynamic focusing and extrusion through the microscale pores in the fibrous network of the single/double-layer mask material needs to be considered in determining mask efficacy. Three-layer masks can effectively block these droplets and thus could be ubiquitously used as a key tool against COVID-19 or similar respiratory diseases.

Role of soft-gel substrates on bouncing-merging transition in drop impact on a liquid film.

Liquid droplets impacting on liquid films is common in many industrial and natural processes. It is crucial to understand the impact of droplets on a liquid film resting on soft deformable substrates in some of the applications including 3D printing of engineering structures, prosthetic implants and tissue engineering. By recognizing the practical relevance of soft-substrates, we present an experimental investigation to assess the role of deformable substrates on bouncing-to-merging transition in droplet impact on the liquid film. First, we prepared polyacrylamide (PAAm) soft-gel substrates with various "softness" (i.e., Young's modulus) by modulating the concentration of a crosslinker, N,N-methylene-bis-acrylamide (BIS). We found that the Young's modulus of PAAm initially increases with the concentration of crosslinker, and subsequently becomes almost constant due to inhomogeneity of crosslinking. Next, through the experiments of droplet impact on the liquid film resting on soft substrates with different Young's moduli, we observe that the early merging and corresponding bouncing-to-merging transitional boundaries remain unaffected by the "softness" since such merging occurs further away from the substrate. However, the late merging, which appears during the retraction process of the deformed droplet, occurs relatively close to the substrate, and hence is found to be significantly affected by its "softness". A scaling analysis is presented to quantify the role of change in Young's modulus of the substrate on late merging, which is supported by the experimental data.

Analyzing the dominant SARS-CoV-2 transmission routes toward an ab initio disease spread model.

Identifying the relative importance of the different transmission routes of the SARS-CoV-2 virus is an urgent research priority. To that end, the different transmission routes and their role in determining the evolution of the Covid-19 pandemic are analyzed in this work. The probability of infection caused by inhaling virus-laden droplets (initial ejection diameters between 0.5 µm and 750 µm, therefore including both airborne and ballistic droplets) and the corresponding desiccated nuclei that mostly encapsulate the virions post droplet evaporation are individually calculated. At typical, air-conditioned yet quiescent indoor space, for average viral loading, cough droplets of initial diameter between 10 µm and 50 µm are found to have the highest infection probability. However, by the time they are inhaled, the diameters reduce to about 1/6th of their initial diameters. While the initially near unity infection probability due to droplets rapidly decays within the first 25 s, the small yet persistent infection probability of desiccated nuclei decays appreciably only by O ( 1000 s ) , assuming that the virus sustains equally well within the dried droplet nuclei as in the droplets. Combined with molecular collision theory adapted to calculate the frequency of contact between the susceptible population and the droplet/nuclei cloud, infection rate constants are derived ab initio, leading to a susceptible-exposed-infectious-recovered-deceased model applicable for any respiratory event-vector combination. The viral load, minimum infectious dose, sensitivity of the virus half-life to the phase of its vector, and dilution of the respiratory jet/puff by the entraining air are shown to mechanistically determine specific physical modes of transmission and variation in the basic reproduction number R 0 from first-principles calculations.

A cellular automata model for expanding turbulent flames.

Cellular automata models based on population dynamics, introduced by Von Neumann in the 1950s, has been successfully used to describe pattern development and front propagation in many applications, such as crystal growth, forest fires, fractal growth in biological media, etc. We, herein, explore the possibility of using a cellular automaton, based on the population dynamics of flamelets, as a low-order model to describe the dynamics of an expanding flame propagating in a turbulent environment. A turbulent flame is constituted by numerous flamelets, each of which interacts with their neighborhood composed of other flamelets, as well as unburned and burnt fluid particles. This local interaction leads to global flame dynamics. The effect of turbulence is simulated by introducing stochasticity in the local interaction and hence in the temporal evolution of the flamefront. Our results show that the model preserves various multifractal characteristics of the expanding turbulent flame and captures several characteristics of expanding turbulent flames observed in experiments. For example, at low turbulence levels, an increase in global burning rate leads to an increase in the turbulence level, while beyond a critical turbulence level, the expanding flame becomes increasingly fragmented, and consequently, the total burning rate decreases with increasing turbulence. Furthermore, at an extremely high turbulence level, the ignition kernel quenches at its nascent state and consequently loses its ability to propagate as an expanding flame.

Universality in spectral condensation.

Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems.

Modeling the role of respiratory droplets in Covid-19 type pandemics.

In this paper, we develop a first principles model that connects respiratory droplet physics with the evolution of a pandemic such as the ongoing Covid-19. The model has two parts. First, we model the growth rate of the infected population based on a reaction mechanism. The advantage of modeling the pandemic using the reaction mechanism is that the rate constants have sound physical interpretation. The infection rate constant is derived using collision rate theory and shown to be a function of the respiratory droplet lifetime. In the second part, we have emulated the respiratory droplets responsible for disease transmission as salt solution droplets and computed their evaporation time, accounting for droplet cooling, heat and mass transfer, and finally, crystallization of the dissolved salt. The model output favourably compares with the experimentally obtained evaporation characteristics of levitated droplets of pure water and salt solution, respectively, ensuring fidelity of the model. The droplet evaporation/desiccation time is, indeed, dependent on ambient temperature and is also a strong function of relative humidity. The multi-scale model thus developed and the firm theoretical underpinning that connects the two scales-macro-scale pandemic dynamics and micro-scale droplet physics-thus could emerge as a powerful tool in elucidating the role of environmental factors on infection spread through respiratory droplets.

Quinine-Based Semisynthetic Ion Transporters with Potential Antiproliferative Activities.

Synthetic ion transporters have attracted tremendous attention for their therapeutic potential against various ion-transport-related diseases, including cancer. Inspired by the structure and biological activities of natural products, we synthesized a small series of squaramide and thiourea derivatives of quinine and investigated their ion transport activities. The involvement of a quinuclidine moiety for the cooperative interactions of Cl- and H+ ions with the thiourea or squaramide moiety resulted in an effectual transport of these ions across membranes. The interference of ionic equilibrium by the potent Cl- ion carrier selectively induced cancer cell death by endorsing caspase-arbitrated apoptosis. In vivo assessment of the potent ionophore showed an efficient reduction in tumor growth with negligible immunotoxicity to other organs.

Sunlight-Mediated Thiol-Ene/Yne Click Reaction: Synthesis and DNA Transfection Efficiency of New Cationic Lipids.

The design of green synthetic reaction conditions is very challenging, especially for biomaterials, but worthwhile if the compounds can be easily synthesized in the aqueous medium. Herein, we report the development of sunlight-mediated thiol-ene/yne click reaction in the presence of a catalytic amount of tert-butyl hydroperoxide (TBHP) in an aqueous medium. The optimized reaction conditions were successfully applied to synthesize a series of small molecules and lipids in a single step in the aqueous medium. The synthetic cationic lipid/co-lipid formed positively charged stable nanosized liposomes that effectually bind with the genetic materials. The in vitro DNA transfection and cellular uptake assays showed that the synthesized cationic lipids have comparable efficiency to commercially available Lipofectamine 2000. This mild synthetic strategy can also be used for smart design of novel or improvement of prevailing lipid-based nonviral gene delivery systems. Such chemical transformations in the aqueous medium are more environment-friendly than other reported thiol-ene/yne click reactions performed in an organic solvent medium.