Tony W. Keller (1937-2023).

Tony Keller, a pioneer in the field of Nuclear Magnetic Resonance (NMR) spectroscopy, passed away on October 27, 2023, at the age of 86 in Spiez, Switzerland. His work and vision were essential to the development and commercialization of NMR spectrometers for many areas of scientific research.

Large-Scale Interlaboratory DI-FT-ICR MS Comparability Study Employing Various Systems.

Ultrahigh resolution mass spectrometry (UHR-MS) coupled with direct infusion (DI) electrospray ionization offers a fast solution for accurate untargeted profiling. Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers have been shown to produce a wealth of insights into complex chemical systems because they enable unambiguous molecular formula assignment even if the vast majority of signals is of unknown identity. Interlaboratory comparisons are required to apply this type of instrumentation in quality control (for food industry or pharmaceuticals), large-scale environmental studies, or clinical diagnostics. Extended comparisons employing different FT-ICR MS instruments with qualitative direct infusion analysis are scarce since the majority of detected compounds cannot be quantified. The extent to which observations can be reproduced by different laboratories remains unknown. We set up a preliminary study which encompassed a set of 17 laboratories around the globe, diverse in instrumental characteristics and applications, to analyze the same sets of extracts from commercially available standard human blood plasma and Standard Reference Material (SRM) for blood plasma (SRM1950), which were delivered at different dilutions or spiked with different concentrations of pesticides. The aim of this study was to assess the extent to which the outputs of differently tuned FT-ICR mass spectrometers, with different technical specifications, are comparable for setting the frames of a future DI-FT-ICR MS ring trial. We concluded that a cluster of five laboratories, with diverse instrumental characteristics, showed comparable and representative performance across all experiments, setting a reference to be used in a future ring trial on blood plasma.

Questions to guide cancer evolution as a framework for furthering progress in cancer research and sustainable patient outcomes.

We appear to be faced with 'two truths' in cancer-one of major advances and successes and another one of remaining short-comings and significant challenges. Despite decades of research and substantial progress in treating cancer, most patients with metastatic cancer still experience great suffering and poor outcomes. Metastatic cancer, for the vast majority of patients, remains incurable. In the context of advanced disease, many clinical trials report only incremental advances in progression-free and overall survival. At the same time, the breadth and depth of new scientific discoveries in cancer research are staggering. These discoveries are providing increasing mechanistic detail into the inner workings of normal and cancer cells, as well as into cancer-host interactions; however, progress remains frustratingly slow in translating these discoveries into improved diagnostic, prognostic, and therapeutic interventions. Despite enormous advances in cancer research and progress in progression-free survival, or even cures, for certain cancer types-with earlier detection followed by surgical, adjuvant, targeted, or immuno- therapies, we must challenge ourselves to do even better where patients do not respond or experience evolving therapy resistance. We propose that defining cancer evolution as a separate domain of study and integrating the concept of evolvability as a core hallmark of cancer can help position scientific discoveries into a framework that can be more effectively harnessed to improve cancer detection and therapy outcomes and to eventually decrease cancer lethality. In this perspective, we present key questions and suggested areas of study that must be considered-not only by the field of cancer evolution, but by all investigators researching, diagnosing, and treating cancer.

The evolution of evolutionary processes in organismal and cancer evolution.

The evolution of early life and of contemporary viruses has been driven in significant part by random genetic mutations, while modern unicellular and organismal evolution primarily leverages evolved, efficient and active cell biology processes for adaptive changes prior to selection. Random mutations are often buffered by cell homeostasis, or they have a negative role, e.g., by causing death or monogenic diseases, or by triggering real-time cancer evolution. Accordingly, the Modern Synthesis theory no longer adequately describes the efficient, often punctuated and at times directionally adaptive natural genetic engineering (NGE) processes deduced from the DNA record of evolution. Similarly, the somatic mutation theory (SMT) of cancer describes driver mutations that can trigger oncogenesis, and passenger mutations characteristic of periods of genetic microevolution in cancer. At the precancerous stage, most somatic mutations are repaired or buffered in the cell, aberrant cells are removed, or organismal bioelectric tissue signals or other physiological functional networks maintain control of rogue, mutated cells. However, the SMT is not sufficient to describe the observed punctuated macroevolution of cancer-cell genes, chromosomes, karyotypes and epigenomes, nor of expressed cancer-cell transcriptomes, proteomes and epiproteomes, which include non-DNA-templated post-translational modifications, protein-protein interactions and metabolites. Moreover, punctuated cancer cell macroevolution often culminates in macro-effects, which include epithelial-mesenchymal transitions (EMT), cancer cell polyploidies and even giant multinucleated cancer cells that drive cancer progression, therapy resistance and metastasis. All of this cancer-cell evolution competes in a molecular and cellular arms race with host immune cells and antibodies, as well as with the host tumor microenvironment. Empirically observed punctuated, multilevel and multiclonal cancer macroevolution, and the concomitant, rapid co-development of the host immune system and tumor microenvironment, can occur with the efficiency, speed and lethality of cancer that is enabled by evolved, active natural genetic engineering (NGE) mechanisms. NGE affects both vertical cancer-cell genomic inheritance and evolution towards therapy resistance and metastasis, as well as viral or cancer-cell exosome vector-driven horizontal gene transfers that contributes to cancer cell cooperation, or to transforming previously non-cancerous somatic cells into destabilized cancer cells during metastasis. In addition, externally driven, irreversible and transferable (EDIT) adaptations are exemplified by mitotically heritable, non-templated cancer cell epigenetics, and by mitotically heritable cancer-cell surface protein and lipid glycosylation, as important examples of fast time-scale molecular evolution mechanisms in which genes are followers, similar to evo-devo processes in organismal evolution.

An Enhanced Isotopic Fine Structure Method for Exact Mass Analysis in Discovery Metabolomics: FIA-CASI-FTMS.

A major bottleneck in metabolomics is the annotation of a molecular formula as a first step to a tentative structure assignment of known and unknown metabolites. The direct observation of an isotopic fine structure (IFS) provides the ability to confidently assign an unknown's molecular formula out of a complex mass spectrum. However, the majority of mass spectrometers deployed for metabolomic studies do not have sufficient resolving power and high-fidelity isotope ratios in the mass range of interest to determine molecular formulas from IFS data. To increase the number of unknowns for which IFS can be determined, a segmented "boxcar" approach using a selection quadrupole as a broadband mass filter is used. In this longer, enhanced dynamic range discovery experiment, selected ions in a specific mass range are accumulated before detection by the analyzer cell. The mass filter window is then moved across the entire mass range resulting in a composite mass spectrum covering the m/z range of interest for phenomics research. The effectiveness of the FIA-CASI-FTMS workflow utilizing IFS for molecular formula assignment is realized with the implementation of the dynamically harmonized cell, which distinguishes the approach from other segmented workflows because of the analytical properties of the cell. The discovery approach was applied to a human plasma sample to confidently assign an unknown molecular formula as part of the quest to illuminate its metabolic "dark matter" via high-fidelity IFS ratio determinations. The FIA-CASI-FTMS workflow showed a 2.6-fold increase in both matching with the Human Metabolome Database and an increase in the IFS pattern.